Research On Capacity Planning And Optimal Control Of BESS In A High Photovoltaic Penetration Power Grid

Photovoltaic power generation has already gotten a rapid development as a clean and green power in recent years.However,the power output of photovoltaic plants varies dramatically incurred by the random of solar radiation,temperature,and so on.Therefore,some measures must be taken to smooth the photovoltaic power in a high penetration photovoltaic power grid.Installation of large scale battery energy storage system(BESS)provides a new way to solve that problem with its fast charging and discharging characteristics.However,the price of BESS is relatively high nowadays.In view of those,research topic of this thesis is capacity optimization and real-time control method of battery energy system in high penetration photovoltaic power grid,and the research contents of this thesis are as follows:In terms of capacity optimization,an optimization method considering the control of photovoltaic output power ramp-rate using Lithium-ion battery is proposed.Firstly,control policy of BESS is proposed in order to smooth the big photovoltaic power fluctuations and support the following capacity optimization model.Then,the mathematical programming model with maximum of grid profit after applying battery energy storage was established considering the mutual restriction relation between frequency control spare capacity and BESS capacity.Finally,genetic algorithm(GA)is used to solve the optimization algorithm,and the effectiveness of this method is verified using simulation results based on a high penetration photovoltaic grid.In term of real-time control of BESS,a control strategy based on model predictive control(MPC)is proposed.Given the prediction errors of photovoltaic power prediction,MPC is used to smooth the photovoltaic power because of its good robust and stability.Firstly,charge-discharge status of BESS is determined by its state of charging and photovoltaic power ramp-rate.Then,optimization model is established paying attention to the relationship between grid frequency regulation capacity demand and BESS charging adjustment,with the aim of minimizing overall cost including grid frequency control payment,battery energy storage cost and over-charge or over-discharge penalty fee.Meanwhile,PV ramp-rate,BESS power,BESS capacity and AGC units regulation rate should be guaranteed within their limitations.At each optimization process,a BESS control schedule across the MPC optimization time horizon is gotten,and only the first step of the schedule is executed.Then,the optimization process is repeated to get next BESS control schedule through updating the information.Finally,the simulation results show the ability of this method to cope with the PV power fluctuation in real-time.