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Energies 2016, 9(12), 1010; doi:10.3390/en9121010

Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

Department of Electrical Engineering, Inha University, Incheon 22212, Korea
Department of Power Grid Integration of Research and Development (R&D) Center, Hyosung Corporation, Anyang 14080, Korea
Author to whom correspondence should be addressed.
Academic Editor: William Holderbaum
Received: 9 August 2016 / Revised: 6 November 2016 / Accepted: 22 November 2016 / Published: 30 November 2016
(This article belongs to the Special Issue Control of Energy Storage)
View Full-Text   |   Download PDF [2481 KB, uploaded 30 November 2016]   |  


An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge (SOC) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO) method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery. View Full-Text
Keywords: energy storage system (ESS); frequency regulation (FR); optimal scheduling; state-of-charge (SOC); energy management energy storage system (ESS); frequency regulation (FR); optimal scheduling; state-of-charge (SOC); energy management

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Yang, J.-S.; Choi, J.-Y.; An, G.-H.; Choi, Y.-J.; Kim, M.-H.; Won, D.-J. Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation. Energies 2016, 9, 1010.

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