Enhancing flexibility and resilience of future power grids with energy storage and electric springs

Abstract

With the raising standard of safe and reliable operation of power system and integrating more fluctuating renewables, operational flexibility and resilience become challenges for power system operation. At the same time, the structures of power grids have greatly changed. Unidirectional and coal-fired generators dominated power grids are gradually replaced by the bidirectional power grids with renewables, distributed generators, controllable loads, and energy storage with more powerful communication abilities. In this thesis, the research is focused on enhancing the operational flexibility and resilience for power grids. These targets are achieved by facilitating the energy balancing with innovative control strategies and devices. In particular, energy storage and electric springs (ES) as the new smart load technology are used. The main studies are as follows. For bulk power grids, the power ramps generated during the switching of operating modes for pumped storage units are proposed to improve operational flexibility by facilitating frequency regulation under the event of net load ramping up and down. For microgrids, battery energy storage system (BESS) is proposed to enhance the resilience of an islanded microgrid, which contains conventional generators with limited ramping ability and fluctuating renewables, by facilitating regulating frequency and voltage. A dynamic model is proposed to evaluate the SOC of BESS accurately, that is essential for regulating frequency with the BESS of small energy capacity. ESs are also proposed to improve the operational flexibility and resilience for islanded microgrids in this thesis. By installing ESs, the non-critical loads (NCLs) can be treated as a controllable operating resource to enhance the operational flexibility and resilience for islanded microgrids with limited operating resources. The feasible operating region of ES is obtained in closed form by deriving the physical model of an individual ES. By associating the physical models of individual ES with AC power flows, the control ability of an ES can be well addressed in this thesis while considering the interactions with other devices in a power grid. In order to adequately address the dynamic process and constraints of different physical system and devices, model predictive control (MPC) method is applied for the proposed control strategies of pumped storage unit, BESS and ES. A graphics processing unit (GPU) based computing platform is proposed to solve the optimal switching time for a pumped storage unit within seconds. The orders of computational complexity with the size of AGC system and the length of control horizons can be reduced by the parallel computing based structure on the GPU platform. The pumped storage units, ESs, and BESSs can effectively contribute on enhancing the operational flexibility and resilience of future power grids with these methods and technologies. Based on the above works in this thesis, new technologies, devices, and strategies are proposed to overcome the major challenges, flexibility and resilience, for future power grids. With the development of smart grid, the increasing number of smart devices with powerful communication and control ability will make implementation of advanced strategies easier and offer a safe, reliable, and efficient future power grid.