Optimal sizing of a utility-scale energy storage system in transmission networks to improve frequency response

Abstract

The frequency response of a large power system is affected by the penetration of renewable energy sources (RESs), where a utility-scale energy storage system (ESS) can alleviate the problem. This paper presents a strategy for sizing an ESS to improve frequency response of transmission networks. The location of the ESS in the transmission network is determined through a sensitivity analysis targeting minimum line loading around a bus. The ESS sizing strategy considers the minimization of frequency deviation as well as rate of change of frequency (ROCOF) after generator or load tripping events. The tuning of PQ controller parameters of the ESS (active power part) is also performed for frequency response improvement. The proposed approach is tested in a modified IEEE-39 bus power system considering a variety of scenarios where RESs are integrated as four different schemes for peak and off-peak load conditions. DIgSILENT PowerFactory is used for developing, testing, and analyzing the system models. A fitness-scaled chaotic artificial bee colony (FSCABC) optimization algorithm (a hybrid meta-heuristic approach) is used for optimization through a Python script automating simulation events in PowerFactory. The results obtained from the FSCABC approach are verified through the application of a particle swarm optimization algorithm. The simulation results suggest that the proposed ESS sizing technique including ESS controller tuning can successfully improve the frequency response of a transmission network.