含光储联合发电系统的配电网双目标拓展无功优化

光储联合发电系统接入配电网给其优化调度带来了新的资源和挑战。分析了光储联合发电系统接入配电网后对配电网电压和网损的影响机理,揭示了光储系统的有功无功调控对配电网调压和降损的重要地位。构建了以系统有功网损最小和电压越限风险最小为优化目标的拓展无功优化模型。该模型在传统无功优化模型的基础上增加储能有功出力和光伏发电功率因数作为控制变量,丰富了有源配电网无功优化的内涵。采用带精英策略的非支配排序多目标优化遗传算法(NSGA-II)求取帕累托前沿,并根据模糊集理论选取最优折衷解。与多种无功优化方案进行仿真比较,结果表明所提出的双目标拓展无功优化模型能够实现含源配电网中有功潮流和无功潮流的协调优化,在充分挖掘系统节能降耗潜力的同时提高配电网电压运行安全裕度。

Double-objective extended reactive power optimization in distribution network with photovoltaic-energy storage hybrid systems

More and more Photovoltaic-Energy Storage Hybrid Systems (PESHS) are embedded to Distribution Networks (DNs), which has brought new resources and challenges to the optimal dispatches of DNs. The influence mechanism of PESHS on voltage and power loss in DNs is presented in this paper, which reveals the important infulence of active and reactive regulating capability of PESHS on voltage regulation and loss reduction for DNs. Therefore, a Double-objective Extended Reactive Power Optimization (DERPO) model that aims at minimum power loss and voltage violation risk for DNs with embedded PESHS is proposed. Unlike traditional reactive power optimization, the active power output of energy storage equipment and power factor of photovoltaic units are added to control variables in this model, which enriches the essence of reactive power optimization of DNs including power supply. Meanwhile, the genetic algorithm NSGA-II is implemented to perform the optimization and the Pareto front of objective function can be worked out. The best compromise solution is achieved by fuzzy method. The results of contrasting simulation between DERPO and other reactive power optimization methods demonstrate that the proposed DERPO model can realize the coordinated optimization of active and reactive power flow and enhance the voltage safety margin while tapping the potential for reducing loss in active DNs. This work is supported by National High-tech R & D Program of China (863 Program) (No. 2015AA050404) and Science and Technology Project of Guangdong Power Grid Co., Ltd (No. GDKJXM20161607).