IASA-Based Capacity Allocation Optimization Study for a Hydro–Pumped Storage–Photovoltaic–Wind Complementary Clean Energy Base - Zhang, Jinliang; Ji, XiaoHong; Ren, Yan; Yang, Jian; Qiao, Yifan; Jin, Xin; Yao, Shuai; Qiao, Ruoyu (Frontiers in Energy Research, 2022)
Photovoltaic and wind power is uncontrollable, while a hydro-pumped storage-photovoltaic-wind complementary clean energy base can ensure stable power transmission in the whole system through power quantity regulation by the hydropower station and the pumped storage station. Reasonable allocation of installed capacities of various power sources in the system can improve the reliability and economy of systematic power supply. A system model was built generalizing the hydropower station and the pumped-storage station as energy storage unit, compensating and regulating the natural output process to match the system output and the load and to establish correlation between installed capacity of the base and the output index. Installed capacity allocation optimization was studied through an optimization model built with initial investment of the base as the objective function, and with power supply guarantee rate, power abandonment rate and installed capacity as restraints, and solved using Improved Artificial Sheep Algorithm (IASA) based on shepherd dog supervision mechanism. A Yellow River Clean Energy Base was selected for case study analyzing the influence of power supply guarantee rate and power abandonment rate on installed capacity allocation and investment. The case study indicates that, sole increase of installed photovoltaic or wind capacity resulted in increase of both power supply guarantee rate and power abandonment rate; appropriate increase of installed capacity of pumped-storage station raised the power supply guarantee rate and lowered the power abandonment rate; and the optimal installed capacity allocation of the photovoltaic, wind, pumped-storage and hydro power under specific load condition of the case project is 4.6:1.4:1.7:1.