Study On The Smoothing Of Wind Power Fluctuation By Hybrid Energy Storage System

With the environmental problems in the world become more and more serious, the research on clean energy and renewable energy power has been increasingly paid attention to. Wind power industry in recent years is developing rapidly in our country. However, since the wind power generation has randomness and volatility, its power integration would produce large impact on the power network, and causes seriously damage to the security and stability of the system as the impact is beyond the permissible limit. By energy storage technology, the volatility of wind power can be well controlled and the output power would meet the design requirements. Recently the Energy storage technologies get great development, as the different kinds of energy storage technologies play their respective advantages, the technologies combination would greatly improve the power, extend the service life and reduce the device cost. Therefore, the power distribution of Hybrid Energy Storage System (HESS) has very important significance in the power integration.The main work is presented as follow:(1) Compute the target output power based on the predicted wind speed. Under the premise of accurate prediction of power output, we use PSO algorithm or other optimal algorithms to calculate the optimal target output power, both as much as possible close to the prediction power which can reduce the demand for devices, and satisfied to the two time scales of indexes.(2) The power configuration of hybrid energy storage system. The difference between the target output power and actual output power is the expected output of hybrid energy storage system. Based on the fundamental properties of the battery, we summarized the battery’s working constraints, then find the optimal solution. We also define the storage battery charging and discharging state equations and state transitions sum within24hours, and add it to the target function, so that the calculation results can take the service life of the battery into consideration.(3) A low-pass filtering algorithm with variable filter coefficient is used to calculating the output power of the target in real time. Then we use PSO algorithm to allocate the output power of super capacitor and battery power in real-time, and take the constraint conditions of the equipment into account as much as possible. In order to extend the life of the battery and reduce environmental pollution at the same time, we make it a priority to super capacitor to absorb or release energy. If the capacity of super capacitor isn’t enough, battery will participate in the work. Through the simulation, we can find the super capacitor can complete most of the power tasks; the usage of battery is relatively low. This can reduce the burden of the energy storage equipment, and reduce the cost. Moreover, as the change of super capacitors’ charge state, power allocation strategy will adjust in real time. Both maximize the advantages of the devices, and get better stabilization quality.