摘要
针对传统的储能调度策略难以取得经济最优的不足,建立了考虑电池寿命损耗的光储充电站储能系统调度模型。首先通过OpenDSS(open distribution system simulation)建立准确的储能、光伏及电动汽车(electric vehicle,EV)充电的底层模型,模拟充电站日运行情况。其次结合雨流计数法求解出不同运行工况下储能系统的运行年限并折算为电池损耗成本计入优化目标,以此实现光储充电站日充电成本最小。最后利用改进后的粒子群优化(particle swarm optimization,PSO)算法对优化问题进行求解得到经济最优的储能容量配置以及该配置下的储能日运营方案,通过算例仿真验证了模型的可行性并分析了不同储能运营方案对收益与组成成本的影响。
Based on the problem that traditional energy storage scheduling strategy is difficult to achieve economic optimization,a scheduling model of energy storage system of photovoltaic-storage charging station considering battery life loss is propoesd.Firstly,the physical models of energy storage,photovoltaic and EV(electric vehicle) charging are established through OpenDSS(open distribution system simulation) to simulate the daily operation of the charging station.Secondly,combined with the rain-flow counting method,the operation life of the energy storage system under different operating conditions is calculated and converted into the battery loss cost,which is included in the optimization goal.In this way,the daily charging cost of photovoltaic-storage charging station can be minimized.Finally,the improved particle swarm optimization(PSO) algorithm is used to solve the optimization problem to obtain the economic optimal energy storage capacity allocation and the daily energy storage operation scheme under this configuration.The feasibility of the model is verified by example simulation and the influence of different energy storage operation schemes on revenue and component cost is analyzed.
作者
王阳
刘希喆
WANG Yang;LIU Xizhe(School of Electric Power Engineering,South China University of Technology,Guangzhou 510641,China)
出处
《南方电网技术》
CSCD
北大核心
2022年第11期1-8,共8页
Southern Power System Technology
基金
国家自然科学基金委员会-国家电网公司智能电网联合基金(U2066212)。
关键词
储能
调度策略
电动汽车
充电站
粒子群优化
OpenDSS
energy storage
scheduling strategy
electric vehicle
charging station
particle swarm optimization(PSO)
OpenDSS
