Energy Storage Mix Optimization Based on Time Sequence Analysis Methodology for Surplus Renewable Energy Utilization

Jaegul Lee, Solyoung Jung, Yongseung Lee and Gilsoo Jang ()
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Jaegul Lee: School of Electrical Engineering, Korea University, Anam-ro, Sungbuk-gu, Seoul 02841, Republic of Korea
Solyoung Jung: Korea Electric Power Research Institute (KEPRI), Munji-ro, Yuseong-gu, Daejeon 34056, Republic of Korea
Yongseung Lee: Korea Electric Power Research Institute (KEPRI), Munji-ro, Yuseong-gu, Daejeon 34056, Republic of Korea
Gilsoo Jang: School of Electrical Engineering, Korea University, Anam-ro, Sungbuk-gu, Seoul 02841, Republic of Korea

Energies, 2023, vol. 16, issue 16, 1-25

Abstract: Increasing the proportion of carbon-free power sources, such as renewable energy, is essential for transitioning to a zero-carbon power system. However, when the rate of grid expansion and flexibility cannot match the rate of renewable energy increase, surplus energy is the result. Surplus energy can be discarded through curtailment or stored and utilized when required. The optimal equipment configuration of the storage system should be determined based on the surplus energy characteristics. This study proposes an optimal energy storage mix configuration method by considering long-term forecasts of surplus energy in the South Korean renewable energy supply and power grid expansion plan. The surplus energy by time slot is comprehensively analyzed considering renewable energy power output, power demand, and power system operation constraints. We calculate the required power and energy of storage devices. Furthermore, we construct a long-term optimal energy storage mix using surplus energy generation patterns and technical and economical characteristics of storage technologies. The total cost minimization was considered as the objective function, comprising three elements: initial construction, equipment replacement, and loss costs for charging and discharging. We propose a time sequence analysis (TSA) method that enables chronological analysis from the starting year to the final target year. The TSA method provides an energy storage mix configuration roadmap that can utilize surplus energy for various years over the entire period, considering the annual increase in surplus energy and commercialization timing of each storage technology. We compare the difference between our proposed TSA method and the method that analyzes only the final target year to validate the superiority of this methodology.

Keywords: energy storage mix; energy storage system; surplus renewable energy; time sequence analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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