摘要
为最大程度提高光伏系统跟踪计划出力能力,基于短期光伏发电预测功率及预测误差的随机性,提出采用机会约束规划的储能系统控制方法。该方法以光储联合出力在调度计划上下限范围内为目标,考虑储能充放电功率与荷电状态(state of charge,SOC)约束条件,并采用基于蒙特卡罗(Monte Carlo)模拟的改进自适应粒子群优化算法(particle swarm optimization algorithm,PSO)进行求解,进而获得日前各时刻储能的充放电功率值。以典型光伏电站出力为例进行仿真,对比分析了固定系数和变化系数情况下光储跟踪计划出力效果与储能情况,结果验证了该控制策略的有效性与灵活性,并为日前储能充放电控制提供了参考方案。
To maximize the photovoltaic（ PV） system tracking scheduleed output,based on the short-term prediction of PV power generation and the randomness of prediction deviation,this paper proposes an energy storage control method that adopts chance-constrained programming. This method takes the PV /energy storage combined output in the upper and lower of scheduled range as the objective,considers the constraints of charge and discharge power and the state of charge（ SOC）,and adopts improved adaptive particle swarm optimization algorithm（ PSO） based on Monte Carlo simulation to obtain dayahead each time charge and discharge power. Finally,taking a typical PV output for simulation,we compare the PV /energy storage tracking scheduled output effect and energy storage condition in fixed coefficients situation and variation coefficients situation. The results verify the feasibility and flexibility of the proposed strategy,which can provide effective reference scheme for day-ahead energy storage control.
出处
《电力建设》
北大核心
2016年第8期115-121,共7页
Electric Power Construction
基金
北京市科技新星计划项目(Z141101001814094)
国家电网公司科技项目(No.DG71-15-039)~~
