Coordinative optimization of hydro-photovoltaic-wind-battery complementary power stations

The depletion of fossil energy and the deterioration of the ecological environment have severely restricted the development of the power industry. Therefore, it is extremely urgent to transform energy production methods and vigorously develop renewable energy sources. It is therefore important to ensure the stability and operation of a large multi-energy complementary system, and provide theoretical support for the world's largest single complementary demonstration project with hydro-wind-PV power-battery storage in Qinghai Province. Considering all the multiple power supply constraints, an optimization scheduling model is established with the objective of minimizing the volatility of output power. As particle swarm optimization (PSO) has a problem of premature convergence and slow convergence in the latter half, combined with niche technology in evolution, a niche particle swarm optimization (NPSO) is proposed to determine the optimal solution of the model. Finally, the multiple stations' coordinated operation is analyzed taking the example of 10 million kilowatt complementary power stations with hydropower, wind power, PV power, and battery storage in the Yellow River Company Hainan prefecture. The case verifies the rationality and feasibility of the model. It shows that complementary operations can improve the utilization rate of renewable energy and reduce the impact of wind and PV power's volatility on the power grid.