Optimal Configuration Of Energy Storage In Distributed Generation System

The essential reasons of problems caused by grid-connected distributed generation (DG) are the intermittent and random power. With fast power compensation and flexible four-quadrant operation, the energy storage can not only promote the application of renewable energy, but also maintain the security of power system. Currently, the capacity optimization of energy storage was mostly from the economic point of view or the cumulative forecasting error. Few scholars have researched the relationship between prediction and smoothed power of DG, to optimize the capacity and control the charging/discharging of different type of energy storage in coordination control.First of all, the power prediction model based on least square support vector machine (LSSVM) is constructed by factors which impact the power output. Secondly, instead of the traditional capacity construction case, the smoothed case that used energy storage to compensate the difference between actual and smoothed power is considered. On the one hand, in order to compensate the forecasting error, a new method that taking the energy storage to compensate the difference between actual and prediction power, has been proposed. On the other hand, in order to minimize the randomness, a new smoothed method that using the ramp rate of clear-sky photovoltaic (PV) power to smooth the actual power has also been put forward. Furthermore, combination the advantages of supercapacitor and battery, a new control strategy based on power prediction to generate conference signal of energy storage output has been designed, which taking into account the state of charge(SOC) of the battery and voltage limits of supercapacitor. Finally, the algorithm of LSSVM is realized in MATLAB and DG power forecasting error are minimized with energy storage. The controller of a hybrid energy storage system and capacity optimization case is confirmed to be effective by the simulation results in EMTDC/PSCAD.