Projects:2019s2-25201 Evaluating the Capabilities of the Existing Synchronous Generators for Ancillary Services Provision in the NEM in various Renewable Penetration Scenarios

Abstract here

Introduction

Our power system is going through dramatic changes. With renewable generation resources in the grid, more synchronous generators are retiring. Traditionally, the synchronous machines were the main sources of ancillary services to compensate imbalances between generation and demand in order to keep the frequency within the acceptable range. However, renewable resources (such as photovoltaic and wind) are very uncertain, unpredictable, and representing huge up and down ramping events. In this study, we want to see if the existing synchronous generators of different types and properties (such as coal- and gas-fired and hydro power plants) are able to provide the kind of AS that is needed in different penetration levels of renewables. We use the information from AEMO to identify the existing synchronous machines, their availability for AS (eight FCAS markets), and specific characteristics related to providing AS. We also analyse the ramping requirements under various renewable (PV + wind) generation scenarios.

Project team

Project students

• Khairul Azwari Adnan
• Aina Afrina Hasram
• Wenkang Li

Supervisors

• Dr Ali Pourmousavi Kani
• David Vowles

Objectives

• Analyze the ramping requirements of under various intermittent generation scenarios.
• Study technical characteristics of existing synchronous generators available in the market.
• Quantifying the ancillary services requirements of the system under different scenarios of intermittent renewable generation.

Background

Supply & Demand

Basically, the electric supply is from renewable and non-renewable sources. Electricity demand is the electricity used by the consumers and the amount is varies. The balancing of supply and demand is very important to make sure the performance of the power system is in stable state. Frequency is one of the important parameters in the power system and it is totally depending on the balancing of supply and demand. The standard frequency limit in the power system is ±50 Hz. As the supply is higher than demand, the frequency is lower and vice versa.

Ancillary Services

Ancillary service is functioning to help in maintaining the performance of the power system. There are three types of ancillary services, Frequency Control Ancillary Service (FCAS), Network Support Control Ancillary Service (NSCAS) and System Restart Ancillary Service (SRAS). For this project, the team is focusing on the FCAS only.

Frequency Control Ancillary Services (FCAS)

Frequency control is necessary in order to guarantee that the system frequency in the grid system is in the nominal frequency. FCAS is required to get back the frequency to its standard frequency and make sure the frequency is always in the range. Other than that, Australia has a huge number of intermittent sources such as wind and solar, that supply electricity to the power system in the grid. These intermittent sources have affected the performance of the frequency in the power system.

There are two types of FCAS services, regulation services and contingency services. Regulation services is provided by the participated generators based on the Automatic Generator Control (AGC) while contingency is provided based on the frequency deviation in the power system. From these two services, there are eight products in the FCAS market, Raise Regulation, Raise 6-Second, Raise 60-Second, Raise 5-Minute, Lower Regulation, Lower 6-Second, Lower 60-Second, and Lower 5-Minute. All these products perform a different services. Table 1 shows the description of each product in the FCAS market.

Method

Figure 1: Project Planning

Figure 1 shows the project planning of the project. Date retrieving is taken from NEMreview apps https://app.nemreview.info/index.html#/ for 3 years of all FCAS products. The data for regulation services is observe in the whole NEM, South Australia, Victoria, New South Wales, Queensland, and Tasmania, while for contingency, the observation is only focus in the South Australia since the contingency services is being controlled by local generator. Correlation testing of the data is done by using price parameters and intermittent sources. Based on this two parameters, only intermittent sources have the correlation with the requirement and availability of the FCAS products. Matlab software is used to perform the correlation testing. Figure 2 and Figure 3 show the correlation between requirement and availability of raise contingency.

Figure 2: Correlation on Intermittent Sources and FCAS (Requirement)

Figure 3: Correlation on Intermittent Sources and FCAS (Availability)

The next step in this project is calculate the critical factor of each FCAS services. Then, data sorting is done based on the correlation parameters. This sorting process is done using Python. Figure 4 shows the coding that is used to sort the data. The critical time interval is determine by sorting the highest critical factor. This data is used in the risk assessment method to fine the safe zone and critical zone. The critical time interval is determine by sorting the highest critical zone of each FCAS products.

Figure 4: Coding to Sort the Data

After that, create a data modelling based on the highest critical zone for each products. This data modelling is create by applying a linear function to the 3 years average data. Figure 5 shows the graph with the linear equation for one of the product. This linear equation is used to predict the future requirement of FCAS products and observe whether availability in the FCAS still can support when the penetration of intermittent increase until 70%.

Figure 5: The Linear Graph

Results

Table 2 shows the result of prediction for requirement based on the linear equation of 3 years data. The prediction is done by using the data of availability for 2019. So, as the penetration of intermittent sources increase, the requirement also increase. The percentage of how many the FCAS availability can support the requirement is based on the assumption of area under the distribution curve minus the area of histogram. Figure 6 shows the distribution curve for requirement of FCAS that has been plot on the histogram of availability.

Table 2: Result on Prediction of Requirement Based on the 3 Years Data

Figure 6: Distribution Plot of Requirement Prediction on Histogram Availability in 2019 (Raise 60-Second)

References

To be added