Projects - User contributions [en]

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-10-20T07:47:47Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has been implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been developed to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Frequency Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
The project considers four individual testbeds to allow for different grid elements to be studied individually:
:* Testbed #1: AC Mains Grid, Load
:* Testbed #2: Generator Grid, Load
:* Testbed #3: Generator Grid, PV, Load
:* Testbed #4: Generator Grid, Battery System, Load

The final experimental testbed 4 shown below consists of a 3.4kVA Portable Synchronous Generator, a DC power simulated Solar PV system, conventional base load, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png|900px]]

== Software Model ==
The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The key challenges of the software model include adjusting the generator governor parameters and calculating inertia parameters to match the characteristics of the physical generator.
:* The software model shown below incorporates all four individual testbeds, simulated via real-time switch control.

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|900px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a trade-off increases overshoot.
:* A 0.5kW Power Injection for a 1kW grid disturbance reduced the frequency dip by ≈ 0.8Hz and RoCoF by ≈ 4Hz/s, which has the effect of increasing the level of system inertia by approximately three times.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF, frequency dip and steady-state recovery time are well matched for both the experimental and simulation test cases, however the experimental results show a larger overshoot due to the governor control characteristics of the portable generator.

[[File:Experimental Plot (with and without PI).jpg|700px]]

[[File:PowerFactory Plot (with and without PI).jpg|700px]]

= Project Conclusion =

''' Key Achievements '''
:* Development of a complete hardware experimental testbed
:* Development of an accuracy verified DAQ Measurement and Processing System
:* Development and validation of a PowerFactory software model

''' Complexities and Solutions '''
:* Frequency measurement limitations due to distorted waveform produced by the portable generator - resulting in two-cycle frequency measurement compensation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using the power swing equation and provided governor models to calculate and match generator parameters

''' Key Outcomes '''

:*Demonstrated that battery storage systems can:
:::- Reduce RoCoF during grid disturbances
:::- Deliver synthetic inertia to a microgrid
:::- Provide Fast Frequency Recovery

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods including optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-10-10T03:27:09Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has been implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been developed to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Frequency Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
The project considers four individual testbeds to allow for different grid elements to be studied individually:
:* Testbed #1: AC Mains Grid, Load
:* Testbed #2: Generator Grid, Load
:* Testbed #3: Generator Grid, PV, Load
:* Testbed #4: Generator Grid, Battery System, Load

The final experimental testbed 4 shown below consists of a 3.4kVA Portable Synchronous Generator, a DC power simulated Solar PV system, conventional base load, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png|900px]]

== Software Model ==
The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The key challenges of the software model include adjusting the generator governor parameters and calculating inertia parameters to match the characteristics of the psychical generator.
:* The software model shown below incorporates all four individual testbeds, simulated via real-time switch control.

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|900px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW grid disturbance reduced the frequency dip by ≈ 0.8Hz and RoCoF by ≈ 4Hz/s, which has the effect of increasing the level of system inertia by approximately three times.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF, frequency dip and steady-state recovery time are well matched for both the experimental and simulation test cases, however the experimental results show a larger overshoot due to the governor control characteristics of the portable generator.

[[File:Experimental Plot (with and without PI).jpg|700px]]

[[File:PowerFactory Plot (with and without PI).jpg|700px]]

= Project Conclusion =

''' Key Achievements '''
:* Development of a complete hardware experimental testbed
:* Development of an accuracy verified DAQ Measurement and Processing System
:* Development and validation of a PowerFactory software model

''' Complexities and Solutions '''
:* Frequency measurement limitations due to distorted waveform produced by the portable generator - resulting in two-cycle frequency measurement compensation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using the power swing equation and provided governor models to calculate and match generator parameters

''' Key Outcomes '''

:*Demonstrated that battery storage systems can:
:::- Reduce RoCoF during grid disturbances
:::- Deliver synthetic inertia to a microgrid
:::- Provide Fast Frequency Recovery

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods including optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

File:Experimental Plot (with and without PI).jpg

2017-10-10T03:23:13Z

A1666810: A1666810 uploaded a new version of "File:Experimental Plot (with and without PI).jpg"

File:PowerFactory Plot (with and without PI).jpg

2017-10-10T03:22:39Z

A1666810: A1666810 uploaded a new version of "File:PowerFactory Plot (with and without PI).jpg"

File:PowerFactory Plot (with and without PI).jpg

2017-10-10T03:06:20Z

A1666810: A1666810 uploaded a new version of "File:PowerFactory Plot (with and without PI).jpg"

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T03:02:36Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has been implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been developed to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Frequency Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
The project considers four individual testbeds to allow for different grid elements to be studied individually:
:* Testbed #1: AC Mains Grid, Load
:* Testbed #2: Generator Grid, Load
:* Testbed #3: Generator Grid, PV, Load
:* Testbed #4: Generator Grid, Battery System, Load

The final experimental testbed 4 shown below consists of a 3.4kVA Portable Synchronous Generator, a DC power simulated Solar PV system, conventional base load, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png|900px]]

== Software Model ==
The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The key challenges of the software model include adjusting the generator governor parameters and calculating inertia parameters to match the characteristics of the psychical generator.
:* The software model shown below incorporates all four individual testbeds, simulated via real-time switch control.

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|900px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW grid disturbance reduced the frequency dip by ≈ 0.8Hz and RoCoF by ≈ 4Hz/s, which has the effect of increasing the level of system inertia by approximately three times.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF, frequency dip and steady-state recovery time are well matched for both the experimental and simulation test cases, however the experimental results show a larger overshoot due to the control characteristics of the portable generator.

[[File:Experimental Plot (with and without PI).jpg|700px]]

[[File:PowerFactory Plot (with and without PI).jpg|700px]]

= Project Conclusion =

''' Key Achievements '''
:* Development of a complete hardware experimental testbed
:* Development of an accuracy verified DAQ Measurement and Processing System
:* Development and validation of a PowerFactory software model

''' Complexities and Solutions '''
:* Frequency measurement limitations due to distorted waveform produced by the portable generator - resulting in two-cycle frequency measurement compensation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using the power swing equation and provided governor models to calculate and match generator parameters

''' Key Outcomes '''

:*Demonstrated that battery storage systems can:
:::- Reduce RoCoF during grid disturbances
:::- Deliver synthetic inertia to a microgrid
:::- Provide Fast Frequency Recovery

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods including optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T02:52:27Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has been implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been developed to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Frequency Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
The project considers four individual testbeds to allow for different grid elements to be studied individually:
:* Testbed #1: AC Mains Grid, Load
:* Testbed #2: Generator Grid, Load
:* Testbed #3: Generator Grid, PV, Load
:* Testbed #4: Generator Grid, Battery System, Load

The final experimental testbed 4 shown below consists of a 3.4kVA Portable Synchronous Generator, a DC power simulated Solar PV system, conventional base load, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png|900px]]

== Software Model ==
The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The key challenges of the software model include adjusting the generator governor parameters and calculating inertia parameters to match the characteristics of the psychical generator.
:* The software model shown below incorporates all four individual testbeds, simulated via real-time switch control.

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|900px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW grid disturbance reduced the frequency dip by ≈ 0.8Hz and RoCoF by ≈ 4Hz/s, which has the effect of increasing the level of system inertia by approximately three times.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF, frequency dip and steady-state recovery time are well matched for both the experimental and simulation test cases, however the experimental results show a larger overshoot due to the control characteristics of the portable generator.

[[File:Experimental Plot (with and without PI).jpg|700px]]

[[File:PowerFactory Plot (with and without PI).jpg|700px]]

= Project Conclusion =

''' Key Achievements '''
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

''' Complexities and Solutions '''
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to calculate and match generator parameters

''' Key Outcomes '''

:*Demonstrated that battery storage systems can:
:::- Provide Fast Frequency Recovery
:::- Deliver synthetic inertia to a microgrid
:::- Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T02:51:07Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has been implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been developed to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Frequency Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
The project considers four individual testbeds to allow for different grid elements to be studied individually:
:* Testbed #1: AC Mains Grid, Load
:* Testbed #2: Generator Grid, Load
:* Testbed #3: Generator Grid, PV, Load
:* Testbed #4: Generator Grid, Battery System, Load

The final experimental testbed 4 shown below consists of a 3.4kVA Portable Synchronous Generator, a DC power simulated Solar PV system, conventional base load, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png|900px]]

== Software Model ==
The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The key challenges of the software model include adjusting the generator governor parameters and calculating inertia parameters to match the characteristics of the psychical generator.
:* The software model shown below incorporates all four individual testbeds, simulated via real-time switch control.

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|900px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW grid disturbance reduced the frequency dip by ≈ 0.8Hz and RoCoF by ≈ 4Hz/s, which has the effect of increasing the level of system inertia by approximately three times.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF and frequency dip are well matched for both experimental and simulation test cases, however the experimental results show a larger overshoot due to the control characteristics of the portable generator.

[[File:Experimental Plot (with and without PI).jpg|700px]]

[[File:PowerFactory Plot (with and without PI).jpg|700px]]

= Project Conclusion =

''' Key Achievements '''
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

''' Complexities and Solutions '''
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to calculate and match generator parameters

''' Key Outcomes '''

:*Demonstrated that battery storage systems can:
:::- Provide Fast Frequency Recovery
:::- Deliver synthetic inertia to a microgrid
:::- Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T02:47:31Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has been implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been developed to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Frequency Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
The project considers four individual testbeds to allow for different grid elements to be studied individually:
:* Testbed #1: AC Mains Grid, Load
:* Testbed #2: Generator Grid, Load
:* Testbed #3: Generator Grid, PV, Load
:* Testbed #4: Generator Grid, Battery System, Load

The final experimental testbed 4 shown below consists of a 3.4kVA Portable Synchronous Generator, a DC power simulated Solar PV system, conventional base load, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png|900px]]

== Software Model ==
The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The key challenges of the software model include adjusting the generator governor parameters and calculating inertia parameters to match the characteristics of the psychical generator.
:* The software model shown below incorporates all four individual testbeds, simulated via real-time switch control.

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|900px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW grid disturbance reduced the frequency dip by ≈ 0.8Hz and RoCoF by ≈ 4Hz/s, which has the effect of increasing the level of system inertia by approximately three times.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF and frequency dip are well matched for both experimental and simulation test cases.

[[File:Experimental Plot (with and without PI).jpg|700px]]

[[File:PowerFactory Plot (with and without PI).jpg|700px]]

= Project Conclusion =

''' Key Achievements '''
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

''' Complexities and Solutions '''
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to calculate and match generator parameters

''' Key Outcomes '''

:*Demonstrated that battery storage systems can:
:::- Provide Fast Frequency Recovery
:::- Deliver synthetic inertia to a microgrid
:::- Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T02:40:00Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has been implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been developed to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Frequency Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
The project considers four individual testbeds to allow for different grid elements to be studied individually:
:* Testbed #1: AC Mains Grid, Load
:* Testbed #2: Generator Grid, Load
:* Testbed #3: Generator Grid, PV, Load
:* Testbed #4: Generator Grid, Battery System, Load

The final experimental testbed 4 shown below consists of a 3.4kVA Portable Synchronous Generator, a DC power simulated Solar PV system, conventional base load, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png|900px]]

== Software Model ==
The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The key challenges of the software model include adjusting the generator governor parameters and calculating inertia parameters to match the characteristics of the psychical generator.
:* The software model shown below incorporates all four individual testbeds, simulated via real-time switch control.

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|900px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW disturbance reduced the frequency dip by 0.8Hz and RoCoF by ≈ 4Hz/s, which is very significant.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF and frequency dip are well matched for both experimental and simulation test cases.

[[File:Experimental Plot (with and without PI).jpg|700px]]

[[File:PowerFactory Plot (with and without PI).jpg|700px]]

= Project Conclusion =

''' Key Achievements '''
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

''' Complexities and Solutions '''
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to calculate and match generator parameters

''' Key Outcomes '''

:*Demonstrated that battery storage systems can:
:::- Provide Fast Frequency Recovery
:::- Deliver synthetic inertia to a microgrid
:::- Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T02:38:19Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has been implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been developed to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Frequency Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
The project considers four individual testbeds to allow for different grid elements to be studied individually:
:* Testbed #1: AC Mains Grid, Load
:* Testbed #2: Generator Grid, Load
:* Testbed #3: Generator Grid, PV, Load
:* Testbed #4: Generator Grid, Battery System, Load

The final experimental testbed 4 shown below consists of a 3.4kVA Portable Synchronous Generator, a DC power simulated Solar PV system, conventional base load, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png|900px]]

== Software Model ==
The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The key challenges of the software model include adjusting the generator governor parameters and calculating inertia parameters to match the characteristics of the psychical generator.
:* The software model shown below incorporates all four individual testbeds, simulated via real-time switch control.

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|900px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW disturbance reduced the frequency dip by 0.8Hz and RoCoF by ≈ 4Hz/s, which is very significant.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF and frequency dip are well matched for both experimental and simulation test cases.

[[File:Experimental Plot (with and without PI).jpg|700px]]

[[File:PowerFactory Plot (with and without PI).jpg|700px]]

= Project Conclusion =

''' Key Achievements '''
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

''' Complexities and Solutions '''
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to calculate and match generator parameters

''' Key Outcomes '''

Demonstrated that battery storage systems can:
:* Provide Fast Frequency Recovery
:* Deliver synthetic inertia to a microgrid
:* Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T02:17:00Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems.

Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development. Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Frequency Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances by providing synthetic inertia.
#:* Provide fast frequency recovery (FFR).

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been implemented to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
:* The project considers four individual testbeds to allow for different grid elements to be studied individually:
:# Testbed #1: AC Mains Grid, Load
:# Testbed #2: Generator Grid, Load
:# Testbed #3: Generator Grid, PV, Load
:# Testbed #4: Generator Grid, Battery System, Load

:* The final experimental testbed shown below consists of a portable synchronous generator, a DC power simulated Solar PV system, conventional loads, variable Dynamic Electronic loads, and a Battery Storage System which has been simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png]]

== Software Model ==
:* The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The software model shown below incorporates all four individual testbeds:

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
:* The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid via control of the Electronic Loads.

[[File:Reverse Power Injection Method.jpg|800px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW disturbance reduced the frequency dip by 0.8Hz and RoCoF by ≈ 4Hz/s, which is very significant.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF and frequency dip are well matched for both experimental and simulation test cases.

[[File:Experimental Plot (with and without PI).jpg|600px]]

[[File:PowerFactory Plot (with and without PI).jpg|600px]]

= Project Conclusion =

== Key Achievements ==
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

== Complexities and Solutions ==
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to match generator parameters

== Key Outcomes ==

Demonstrated that battery storage systems can:
:* Provide Fast Frequency Recovery
:* Deliver synthetic inertia to a microgrid
:* Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T02:00:50Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems. Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development.

Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Provide synthetic inertia
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances
#:* Provide fast frequency recovery (FFR)

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been implemented to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
:* The project considers four individual testbeds to allow for different grid elements to be studied individually:
:# Testbed #1: AC Mains Grid, Load
:# Testbed #2: Generator Grid, Load
:# Testbed #3: Generator Grid, PV, Load
:# Testbed #4: Generator Grid, Battery System, Load

:* The final experimental testbed shown below consists of a portable synchronous generator, a DC power simulated Solar PV system, conventional loads, variable Dynamic Electronic loads, and a Battery Storage System simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png]]

== Software Model ==
:* The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The software model shown below incorporates all four individual testbeds:

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
:* The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid.

[[File:Reverse Power Injection Method.jpg|800px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* A 0.5kW Power Injection for a 1kW disturbance reduced the frequency dip by 0.8Hz and RoCoF by ≈ 4Hz/s, which is very significant.
:* Power Injection thus is shown to provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.
:* Critical factors such as RoCoF and frequency dip are well matched for both experimental and simulation test cases.

[[File:Experimental Plot (with and without PI).jpg|600px]]

[[File:PowerFactory Plot (with and without PI).jpg|600px]]

= Project Conclusion =

== Key Achievements ==
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

== Complexities and Solutions ==
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to match generator parameters

== Key Outcomes ==

Demonstrated that battery storage systems can:
:* Provide Fast Frequency Recovery
:* Deliver synthetic inertia to a microgrid
:* Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T01:43:04Z

A1666810: Significant Project Details Added

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems. Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development.

Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Provide synthetic inertia
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances
#:* Provide fast frequency recovery (FFR)

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been implemented to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
:* The project considers four individual testbeds to allow for different grid elements to be studied individually:
:# Testbed #1: AC Mains Grid, Load
:# Testbed #2: Generator Grid, Load
:# Testbed #3: Generator Grid, PV, Load
:# Testbed #4: Generator Grid, Battery System, Load

:* The final experimental testbed shown below consists of a portable synchronous generator, a DC power simulated Solar PV system, conventional loads, variable Dynamic Electronic loads, and a Battery Storage System simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png]]

== Software Model ==
:* The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The software model shown below incorporates all four individual testbeds:

[[File:PF Complete Model Diagram.JPG|800px]]

== Reverse Power Injection Method ==
:* The following diagram shows the method used to achieve Reserve Power Injection in the Microgrid.

[[File:Reverse Power Injection Method.jpg|800px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* Critical factors such as RoCoF and frequency dip are well matched for both experimental and simulation test cases.
:* Power Injection thus can provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.

[[File:Experimental Plot (with and without PI).jpg|600px]]

[[File:PowerFactory Plot (with and without PI).jpg|600px]]

= Project Conclusion =

== Key Achievements ==
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

== Complexities and Solutions ==
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to match generator parameters

== Key Outcomes ==

Demonstrated that battery storage systems can:
:* Provide Fast Frequency Recovery
:* Deliver synthetic inertia to a microgrid
:* Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

File:Reverse Power Injection Method.jpg

2017-09-21T01:41:22Z

A1666810:

File:PowerFactory Plot (with and without PI).jpg

2017-09-21T01:34:25Z

A1666810:

File:Experimental Plot (with and without PI).jpg

2017-09-21T01:34:06Z

A1666810:

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T00:55:44Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems. Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development.

Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:Microgrid Image.jpg|600px]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Objectives ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Processing System.
# Development and validation of a software model using PowerFactory.
# Through testbed experiments and software simulations, show that added battery storage systems can:
#:* Provide synthetic inertia
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances
#:* Provide fast frequency recovery (FFR)

= Project Design =

== DAQ and Frequency Processing System ==
:* LabVIEW has be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been implemented to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Processing System flow diagram:

[[File:DAQ Measruement and Processing System.jpg|800px]]

== Hardware Testbed ==
:* The project considers four individual testbeds to allow for different grid elements to be studied individually:
:# Testbed #1: AC Mains Grid, Load
:# Testbed #2: Generator Grid, Load
:# Testbed #3: Generator Grid, PV, Load
:# Testbed #4: Generator Grid, Battery System, Load

:* The final experimental testbed shown below consists of a portable synchronous generator, a DC power simulated Solar PV system, conventional loads, variable Dynamic Electronic loads, and a Battery Storage System simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png]]

== Software Model ==
:* The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The software model shown below incorporates all four individual testbeds:

[[File:PF Complete Model Diagram.JPG|800px]]

= Project Results =
:* The frequency response demonstrates that Power Injection reduces the RoCoF, frequency dip and frequency recovery time, but as a tradeoff increases overshoot.
:* Critical factors such as RoCoF and frequency dip are well matched for both experimental and simulation test cases.
:* Power Injection thus can provide Fast Frequency Recovery (FFR) by delivering synthetic inertia to the grid.

= Project Conclusion =

== Key Achievements ==
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

== Complexities and Solutions ==
:* Frequency measurement limitations due to distorted waveform provided by a portable generator - resulting in two-cycle frequency measurement limitation
:* Inverter synchronization complexities - utilization of reverse power injection via electronic load
:* Experimental testbed software modelling – using power swing equation and governor models to match generator parameters

== Key Outcomes ==

Demonstrated that battery storage systems can:
:* Provide Fast Frequency Recovery
:* Deliver synthetic inertia to a microgrid
:* Reduce RoCoF during grid disturbances

= Future Project Recommendations =
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

= References =
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

File:PF Complete Model Diagram.JPG

2017-09-21T00:20:41Z

A1666810: PowerFacory Software Model

PowerFacory Software Model

File:DAQ Measruement and Processing System.jpg

2017-09-21T00:19:57Z

A1666810: Project 106 - System

Project 106 - System

File:Microgrid Image.jpg

2017-09-21T00:19:23Z

A1666810: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017.

"Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017.

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-21T00:14:51Z

A1666810: Details added

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase development of a renewable microgrid experimental testbed at the UoA, featuring microgrid dynamic modelling simulation work using PowerFactory, a sophisticated computer-aided engineering tool for the analysis of electrical power systems. Experimental aspects incorporate battery energy storage into a microgrid to study the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as performing dynamic stabilisation to study the effects in the context of a large mega-grid for future research and development.

Frequency measurement and processing systems have been developed using a combination of sampling hardware and programming software, primarily LabVIEW and MATLAB. Key findings indicate benefits and limitations of battery storage systems in providing Fast Frequency Recovery by means of Fast Power Injection.

Recent developments of the SA Power Grid with one of the highest renewable energy penetration rates in the world, currently at 50%, and the lowest relatively system inertia of the country, highlight the relevance of this project with experimental and simulation model development of battery storage systems and microgrid capabilities. Future projects may explore voltage stability control, improved frequency measurement techniques and further frequency stability control aspects.

Microgrid Example [1]:

[[File:?????.jpg]]

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:* Dr Wai-Kin Wong

= Project =

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 50% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Aims ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
#:* Developing a DAQ Measurement and Processing System.
# Through experimentation, show that added battery storage systems can:
#:* Provide synthetic inertia
#:* Reduce Rate of Change of Frequency (RoCoF) during grid disturbances
#:* Provide fast frequency recovery (FFR)
# Development and validation of a software model using PowerFactory.

== Objectives ==
'''Experimental'''
# Expand the microgrid testbed from previous studies.
# Study the microgrid steady-state and transient response under different loading conditions.
# Demonstrate the synthetic inertia recovery effect of battery storage systems.

'''Software Modelling'''
# Develop and validate a software model using DigSILENT PowerFactory
# Demonstrate synthetic inertia and the fast frequency recovery provided by battery storage systems.
# Perform a range of advanced software test case simulations to compare a range of microgrid transient characteristics

== Project Design ==
'''Hardware Design'''
:* The project considers four individual testbeds to allow for different grid elements to be studied individually:
:# Testbed #1: AC Mains Grid, Load
:# Testbed #2: Generator Grid, Load
:# Testbed #3: Generator Grid, PV, Load
:# Testbed #4: Generator Grid, Battery System, Load

:* The final experimental testbed shown below consists of a portable synchronous generator, a DC power simulated Solar PV system, conventional loads, variable Dynamic Electronic loads, and a Battery Storage System simulated via a Reverse Power Injection system using a Dynamic Electronic load.

[[File:Diagram - P106.png]]

'''Software Design'''
:* The software model was designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory was utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model has been developed and validated to represent the experimental testbed.
:* The software model shown below incorporates all four individual testbeds:

[[File:??????????.jpg]]

'''Control, Sampling and Processing Tools'''
:* LabVIEW has be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards have been utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB has been implemented to aid in the analysis of experimental data and the comparison with software model data.
:* The process model below shows the DAQ Measurement and Processing System flow diagram:

[[File:??????????.jpg]]

== Key Results ==

== Conclusion ==
'''Key Achievements'''
:* Development of a complete hardware experimental testbed
:* Developed an accuracy verified DAQ Measurement and Processing System
:* Developed and validated a PowerFactory software model

'''Key Outcomes'''
Demonstrated that battery storage systems can:
:* Provide Fast Frequency Recovery
:* Deliver synthetic inertia to a microgrid
:* Reduce RoCoF during grid disturbances

== Future Project Recommendations ==
Future project may focus on aspects involving:
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

== References ==
[1]: "Microgrid Technology – Cleanspark". Cleanspark.com. N.p., 2017. Web. 22 Mar. 2017

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-09-19T06:04:55Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase in the development of a renewable microgrid experimental testbed at the UoA. It also features microgrid dynamic modelling simulation work using PowerFactory. The experimental aspects will involve the incorporation of battery energy storage into the microgrid to allow the study of the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as dynamic stabilisation of the microgrid. In parallel, development of dynamic software simulation models will be undertaken to experimentally validate the measured behaviour of the renewable microgrid testbed.

Applications of the models in a larger “megagrid” context will also be undertaken to compare the operational reliability and security characteristics of the two types of renewable power systems, in particular in micro-scale study of future architecture and dynamic control strategies that may be applicable to the South Australia power system which has one of the highest renewable energy penetration rates at 45% in the world.

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:*Dr Wai-Kin Wong

= Project =

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 47% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable energy sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Aims ==
# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
# Through experimentation, show that added battery storage systems can:
#:* Provide a synthetic inertia recovery effect in a microgrid;
#:* Reduce the rate of change of frequency during grid disturbances; and
#:* Provide fast frequency recovery.
# Development and validation of a software model using PowerFactory.

== Objectives ==
'''Experimental'''
# Expand the microgrid testbed from previous studies.
# Study the microgrid steady-state and transient response under different loading conditions.
# Demonstrate the synthetic inertia recovery effect of battery storage systems.

'''Software Modelling'''
# Develop a model to simulate the experimental microgrid testbed.
# Perform simulations of frequency disturbances using simulation terminal.
# Demonstrate the inertia recovery effect and fast frequency recovery provided by battery storage systems.

== Project Design ==
'''Hardware Design'''
:* The final experimental testbed will consist of a portable synchronous generator, a DC power simulated Solar PV system, conventional loads, variable Electronic Loads, and a simulated battery storage system.

[[File:Diagram - P106.png]]

'''Software Design'''
:* The software model will be designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory will be utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model will be modelled to represent the experimental testbed and to validate the experimental inertia characteristics.

'''Control, Sampling and Processing Tools'''
:* LabVIEW will be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards will also be utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB and Microsoft Excel will be implemented to aid in the analysis of experimental data and the comparison with model data.

== Conclusion ==

== Future Project Recommendations ==
'''Future project may focus on aspects involving:'''
:* Grid voltage stability control during power injection
:* Improved frequency processing techniques
:* Further FFR control methods involving optimal fault detection time, power injection duration and ramping levels
:* Upgraded generator capabilities incorporating a pure sine wave output to allow for grid-tied inverter synchronisation

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-07-17T00:00:00Z

A1666810:

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-07-04T04:22:21Z

A1666810:

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase in the development of a renewable microgrid experimental testbed at the UoA. It also features microgrid dynamic modelling simulation work using PowerFactory. The experimental aspects will involve the incorporation of battery energy storage into the microgrid to allow the study of the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as dynamic stabilisation of the microgrid. In parallel, development of dynamic software simulation models will be undertaken to experimentally validate the measured behaviour of the renewable microgrid testbed.

Applications of the models in a larger “megagrid” context will also be undertaken to compare the operational reliability and security characteristics of the two types of renewable power systems, in particular in micro-scale study of future architecture and dynamic control strategies that may be applicable to the South Australia power system which has one of the highest renewable energy penetration rates at 45% in the world.

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:*Dr Wai-Kin Wong

= Project =

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 47% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Aims ==

# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
# Through experimentation, show that added battery storage systems can:
#:* Provide a synthetic inertia recovery effect in a microgrid;
#:* Reduce the rate of change of frequency during grid disturbances; and
#:* Provide fast frequency recovery.
# Development and validation of a software model using PowerFactory.

== Objectives ==

== Project Design ==
'''Hardware Design'''
:* The final experimental testbed will consist of a portable synchronous generator, a DC power simulated Solar PV system, conventional loads, variable Electronic Loads, and a simulated battery storage system.

[[File:Diagram - P106.png]]

'''Software Design'''
:* The software model will be designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory will be utilized as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model will be modelled to represent the experimental testbed and to validate the experimental inertia characteristics.

'''Control, Sampling and Processing Tools'''
:* LabVIEW will be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards will also be utilized for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB and Microsoft Excel will be implemented to aid in the analysis of experimental data and the comparison with model data.

== Conclusion ==

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-07-04T02:25:36Z

A1666810: Added image

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase in the development of a renewable microgrid experimental testbed at the UoA. It also features microgrid dynamic modeling simulation work using PowerFactory. The experimental aspects will involve the incorporation of battery energy storage into the microgrid to allow the study of the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as dynamic stabilisation of the microgrid. In parallel, development of dynamic software simulation models will be undertaken to experimentally validate the measured behaviour of the renewable microgrid testbed.

Applications of the models in a larger “megagrid” context will also be undertaken to compare the operational reliability and security characteristics of the two types of renewable power systems, in particular in micro-scale study of future architecture and dynamic control strategies that may be applicable to the South Australia power system which has one of the highest renewable energy penetration rates at 45% in the world.

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:*Dr Wai-Kin Wong

= Project =

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 47% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Aims ==

# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
# Through experimentation, show that added battery storage systems can:
#:* Provide a synthetic inertia recovery effect in a microgrid;
#:* Reduce the rate of change of frequency during grid disturbances; and
#:* Provide fast frequency recovery.
# Development and validation of a software model using PowerFactory.

== Objectives ==

== Project Design ==
'''Hardware Design'''
:* The final experimental testbed will consist of a portable synchronous generator, a DC power simulated Solar PV system, conventional loads, variable Electronic Loads, and a simulated battery storage system.

[[File:Diagram - P106.png]]

'''Software Design'''
:* The software model will be designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory will be utilised as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model will be modelled to represent the experimental testbed and to validate the experimental inertia characteristics.

'''Control, Sampling and Processing Tools'''
:* LabVIEW will be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards will also be utilised for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB and Microsoft Excel will be implemented to aid in the analysis of experimental data and the comparison with model data.

== Conclusion ==

File:Diagram - P106.png

2017-07-04T02:22:53Z

A1666810:

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-07-04T01:38:27Z

A1666810: Updates

= Introduction =
== Project Description ==
Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-Based Microgrid

This project involves the next phase in the development of a renewable microgrid experimental testbed at the UoA. It also features microgrid dynamic modeling simulation work using PowerFactory. The experimental aspects will involve the incorporation of battery energy storage into the microgrid to allow the study of the steady-state and dynamic properties of energy storage in maintaining demand-supply balance as well as dynamic stabilisation of the microgrid. In parallel, development of dynamic software simulation models will be undertaken to experimentally validate the measured behaviour of the renewable microgrid testbed.

Applications of the models in a larger “megagrid” context will also be undertaken to compare the operational reliability and security characteristics of the two types of renewable power systems, in particular in micro-scale study of future architecture and dynamic control strategies that may be applicable to the South Australia power system which has one of the highest renewable energy penetration rates at 45% in the world.

== Project Team ==
:* Adam Portelli

:* Hosoo Yoon

== Project Supervisors==
'''(University of Adelaide)'''
:* Associate Professor Nesimi Ertugrul

'''(ElectraNet, Sponsor)'''
:*Dr Wai-Kin Wong

= Project =

== Motivation ==

'''South Australia'''
:* Renewable energy penetration ≈ 47% (World Leaders).
:* Currently have the lowest relative system inertia of the country.

'''Renewable sources''' '', such as PV and Wind''
:* Do not provide traditional system Inertia.
:* Intermittent/variable supply.
:* Currently posing power grid stability threats.

'''So, there is a need for a long-term solution...'''
:* Battery storage systems may be a key part of the solution!

== Aims ==

# Next phase development of a Renewable Energy-Based Microgrid
#:* Adding new battery storage system.
# Through experimentation, show that added battery storage systems can:
#:* Provide a synthetic inertia recovery effect in a microgrid;
#:* Reduce the rate of change of frequency during grid disturbances; and
#:* Provide fast frequency recovery.
# Development and validation of a software model using PowerFactory.

== Objectives ==

== Project Design ==
'''Hardware Design'''
:* The final experimental testbed will consist of a portable synchronous generator, a DC power simulated Solar PV system, variable Electronic Loads and a simulated battery storage system.

'''Software Design'''
:* The software model will be designed using PowerFactory by DigSILENT. Power Factory is a sophisticated computer-aided engineering tool for the analysis of transmission, distribution, and industrial electrical power systems, primarily for the analysis of large power systems.
:* PowerFactory will be utilised as it has dynamic power system simulation capabilities which is a key focus in this project.
:* The PowerFactory software model will be modelled to represent the experimental testbed and to validate the experimental inertia characteristics.

'''Control, Sampling and Processing Tools'''
:* LabVIEW will be implemented to form the sampling capability system used in this project to record grid data.
:* National Instrument sampling and I/O cards will also be utilised for data capture and control of the electronic load hardware devices via LabVIEW.
:* Software processing using MATLAB and Microsoft Excel will be implemented to aid in the analysis of experimental data and the comparison with model data.

== Conclusion ==

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-03-30T08:29:01Z

A1666810: /* Project Team */

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-03-30T08:27:50Z

A1666810:

Projects:2017s1-106 Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid

2017-03-28T02:48:36Z

A1666810: Project 106 - Inertia Characterisation and Modelling in a Renewable Energy-based Microgrid - Wiki Page

== Project team ==

Adam Portelli

Hosoo Yoon

== Project supervisors ==
'''(University of Adelaide)''' Associate Professor Nesimi Ertugrul

'''(ElectraNet)''' Dr Wai-Kin Wong

== Introduction ==

== Motivation ==

== Aims ==

== Objectives ==

== Project Design ==

== Conclusion ==

== Future Work ==

== References ==

== Acknowledgements ==

Literature Search Training

2017-02-28T04:12:57Z

A1666810: /* 2017 Semester 1 */

== 2017 Semester 1 ==

Please enter your project group number in the confirmed LST slot.

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