Optimal Energy Storage Capacity Planning in Distribution System via Electron-Drifting Algorithm

• Main Authors: Yung-ShengChuang, 莊詠盛
• Other Authors: Hong-Tzer Yang
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/34978486050757996717

碩士 === 國立成功大學 === 電機工程學系 === 104 === The challenges of increasing power demand and environmental problems have directed extensive attention to the usage of renewable energy, especially photovoltaic (PV) systems. However, high penetration of PV generation drastically affects the voltage of distribution systems, which may limit the growth and the development of PV systems. Consequently, an effective voltage control method is necessary to mitigate overvoltage problems and to increase the hosting capacity of PV systems. This thesis utilizes an energy storage system (ESS) to eliminate voltage rise problems and proposes a dual-loop optimization method to determine the optimal capacities and inverter sizes of ESSs. ESSs can thus reduce feed-in active power curtailment of PV systems. In the inner loop of the optimization, for a specified ESS capacity the daily active and reactive power scheduling, including on-load tap changer, PV, and ESS, are optimized by an electron drifting algorithm (EDA). The outer loop uses an EDA to optimize the ESS capacities and the inverter sizes. To verify the feasibility of the proposed optimization method, real PV power generation data and load profiles are used to analyze the economic benefits of the proposed method. Moreover, three different kinds of electricity tariff structures are used to analyze the economic benefits. With the optimal capacity of energy storage system determined, simulation results also show that the optimized policy produces more economic benefits than other policies produce.