Projects:2017s1-140 Energy Storage Requirements for the SA Grid
Contents
Introduction
Project Description
Project 140 - Energy Storage Requirements for the SA Grid
The aim of this project is to determine the requirements for energy storage in South Australia, so that the power generated in renewable energy generation may be delivered to consumers consistently and reliably. This is explored by the development of software tools and a database, to obtain, store and maintain energy data. The potential uses of this database is explored, both how it can be used broadly, and how it can be used in the context this project. Finally, a case study is undertaken in which the obtained data is used to explore the effect of battery storage on the output of a wind farm; and how intelligently managing the battery energy storage system can improve results.
Project Group Members
- Daniel Bondarenko
- Ryan Standing
Project Supervisors
- Professor Derek Abbott
- Mr David Vowles
Aim and Motivation
Renewable energy sources are becoming increasingly prevalent in South Australia. Although having many benefits, they also have their drawbacks. Chief among these is their intermittency.
Intermittency refers to the fact that renewable energy sources vary in intensity, depending on the time of day or season of the year, to the point that they are unable to provide continuous, reliable energy generation on their own. Renewable energy sources are also unable to respond dynamically to changes in demand as renewable energy generators are totally reliant on the energy that nature can provide at that moment.
In order to alleviate the intermittency inherent in renewable generators, energy storage systems such as batteries and pumped-hydro can be used. These storage systems are used to store energy when renewable generators are producing more energy than there is demand for. As such, when energy generation falls below demand, the energy stored in the energy storage systems is used to meet demand.
Method
In order to explore an energy storage solution, a package of software tools was created. These tools enable data to be intuitively and automatically downloaded (initially from AEMO, but is expandable to other sources), formed into a dataset, and manipulated and used to form smaller datasets and plots.
Once this data had been obtained, it was decided to perform a case study to preliminarily explore the effect of energy storage on renewable generation output in SA. For the study, generation data from the Hornsdale wind farm was used to investigate the use of a battery energy storage system to minimise the output variance of the wind generators at Hornsdale. The battery currently being constructed by Tesla at the Hornsdale site will be modelled, to explore the effect that a soon-to-be existing battery can have on smoothing the wind generation output of a generation site.
Methods of controlling the charging and discharging of the battery were explored. These involved the use of genetic algorithms. Genetic algorithms are a type of search algorithm which aim to solve optimisation problems by using the mechanisms of natural selection and population genetics.
