Multi-objective Optimization Of System Combined Wind Power With Pumped Storage Power

Since the oil crisis in 1970s, the wind act as a renewable green energy get more attention increasingly, the wind power technology have been highly developed, its electricity costs has been drastically, having a good social and economic significance and sustainable development significance, with the great development prospects. Along with the development of wind power technology, the wind power industry in China is developing rapidly, a growing number of large and medium-sized wind farm successively get in operation. But the biggest difference between wind power and conventional energy that the wind power is a kind of intermittent energy which can not be stored and predicted accuratly. The wind speed changes cause the fluctuations in the wind power output, getting much trouble to the operation of the power system, making the wind power capacity accepted by the power system limited.The pumped storage power station is a way of storing energy. Through the pumped-storage and water power generation, the wind farms can make use of wind energy in the original time and space redistribution.This paper establishes the combined power supply system of wind-pumped storagepower station. After introducing the basic theory about wind power generation and water power storage, a optimization model combined wind power with pumped storage power is established,aiming at getting most benefits and smoothing the output power of the combined system. Using multi-objective clonal selection algorithm to solve this model to enhance the effectiveness of the system and at the same time smooth the output power. It is helpful to increase the proportion of wind power in power system and finally benefit the development of wind industry in China.