IASA-Based Capacity Allocation Optimization Study for a Hydro–Pumped Storage–Photovoltaic–Wind Complementary Clean Energy Base

Abstract

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 an energy storage unit, compensating and regulating the natural output process to match the system output and the load and to establish a correlation between the installed capacity of the base and the output index. Installed capacity allocation optimization was studied through an optimization model built with an 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 the shepherd dog supervision mechanism. A Yellow River clean energy base was selected for a case study analyzing the influence of power supply guarantee rate and power abandonment rate on installed capacity allocation and investment. For the two most important parameters in the optimization process, that is, the power supply guarantee rate and the power abandonment rate, after qualitative and quantitative analysis, it is found that the power supply guarantee rate has a greater impact on the initial investment. In this study, a combination of the power abandonment rate of 18% and the guaranteed rate of 90% is finally selected for the optimization calculation. The case study indicates that sole increase of installed photovoltaic or wind capacity resulted in the increase of both power supply guarantee rate and power abandonment rate; an appropriate increase in the installed capacity of the 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 hydropower under a specific load condition of the case project is 4.6:1.4:1.7:1.