Optimal sizing and locating of grid-scale energy storage systems to enhance power grid frequency inertial response

Enhanced frequency inertial response has become an essential requirement requested by many grid transmission system operators around the world to support the frequency stability of power systems after sudden severe disturbance. With current regulations mandate to deploy more renewable generation resources, this prerequisite has become a necessity toward building new decarbonised power systems. Energy storage systems (such as a grid-scale battery energy system) have the advantage of storing energy and providing high power at a rapid rate, which is expected to meet this need.

The research presented in this thesis demonstrates that the battery energy system can improve the dynamic response of the entire large grid. Therefore, it supports the integration of more renewable energy resources to meet the future energy scenarios that set by the British National Grid. The research develops and validates a model of a battery energy storage system for the use at a grid transmission level to support the frequency inertial response. This involves a comprehensive analysis and design of all the electro-mechanical-chemical models of such a system and analysing their impact on the power system overall frequency dynamics. The models were studied through preliminary tests by connecting the proposed developed system to large-scale power grid prototypes. An optimisation method was developed to search for best-required design variables that can improve the grid system frequency response to set points.

Hence, the main contribution is the creation of optimisation methodology to calculate the correct optimised design variables for grid-scale battery energy storage to enhance the rate of change of frequency, provide frequency support and improve the overall power system dynamics. The key outcomes are: (i) design and test a preliminary model of grid-scale battery energy storage system with a set of controllers including inertia response controller that sup-port the frequency response; and (ii) develop an optimisation methodology to search for the optimal size and location of grid-scale energy storage system under different scenarios of operating conditions. Both outcomes have been verified and validated through several simulation cases.