Collaborative Optimal Configuration And Control Strategy Of Battery Energy Storage Participating In Peak-shaving And Frequency Regulation

With the annual increase in the scale of renewable energy installations and the changes in load characteristics brought about by industrial development,the imbalance between the source and the load has an impact on the safe and stable operation of the power grid,putting tremendous pressure on the power system’s peak-shaving and frequency regulation(FR).Energy storage has the characteristics of fast response,easy control and two-way output,and is widely used in peak-shaving and FR scenarios.Energy storage applications at this stage are mostly aimed at a single application scenario,and the use of collaborative scenario is of great significance for ameliorating the secure and steady operation of the power grid,improving the utilization rate of energy storage,and increasing operating revenue.Therefore,this theis studies the energy storage selection method for the peak-shaving and FR collaborative scenario,comprehensively considers the economic and technical optimal capacity configuration,and develops a coordinated scenario control strategy that considers the State of Charge(So C)of energy storage.Firstly,based on the load data and frequency data of a province,this theis analyzes the demand and principle of peak-shaving scenario and FR scenario,and further expounds the feasibility of peak-shaving and FR collaborative scenario.According to the scenario analysis,the output characteristics of energy storage in different scenarios and the requirements for the types of energy storage are clarified.Considering the characteristics of safety,environment,technology and economy,the decision-making index system for type selection is established.The weight coefficient of decision-making index is determined by the evaluation method combining subjective analytic hierarchy process with objective CRITIC method,Based on this,the comprehensive scores of different energy storage types are calculated,and the lithium iron phosphate battery with the highest score is selected as the best energy storage selection scheme.Then,the capacity optimization configuration model is established for the peakshaving scenario,and the optimization model is converted into an unconstrained problem to be solved by the interior point method,and a configuration solution that takes into account the best economic and technical aspects is formed.The capacity configuration process of the FR scenario is similar to that of the peak-shaving scenario.According to the working principles and application objectives of the two scenarios,the cooperative work strategy with peak-shaving scenario as the main and FR scenario as the auxiliary is determined on the premise of meeting the rules of power market.After obtaining the energy storage output sequence according to the work strategy,the energy storage configuration scheme in the collaborative scenario is obtained through the capacity configuration calculation method.The simulation shows that the peak-shaving and FR collaborative scenario can effectively improve the utilization rate of energy storage and the annual net income,and improve the economics of energy storage configuration.Finally,the constant power and variable power control strategies and control processes are determined according to the peak-shaving scenario,and the peak-shaving effect evaluation index is constructed.The simulation test shows that the fluctuation range of the variable power control strategy is smaller,and the peak-shaving effect is better.Aiming at the FR scenario,the basic principle and control model of virtual droop and virtual inertia control strategy are analyzed in detail.The two methods are combined to complement each other,and the comprehensive control strategy is obtained.Based on MATLAB/Simulink,the simulation results show that the integrated control strategy has the best FR effect and is better than the other two strategies in reducing the FR pressure of thermal power units.According to the peak-shaving and FR collaborative scenario,the working area of energy storage So C is divided,and the control process of collaborative scenario strategy is proposed.Simulation results show that the control strategy can effectively participate in the FR scenario and improve the utilization rate of energy storage without affecting the peak-shaving effect and beyond the normal range of energy storage So C.The reliability and effectiveness of the proposed strategy are verified.