考虑水–光–荷不确定性条件下配电网协调优化

Coordination Optimization of Distribution Network Considering Hydro-photovoltaic-load Uncertainty

  • 摘要: 目前,高比例的可再生能源接入配电网,配电网的经济性和可靠性问题亟待解决。为此,该文建立一个考虑水–光–荷不确定性的配电网协调优化模型。首先,采用蒙特卡罗抽样方法生成光伏、径流式小水电和负荷场景,然后使用后向场景缩减法得到典型输出场景。其次,通过采用二阶锥松弛和大M方法,将混合整数非线性非凸模型转化为混合整数二阶锥规划问题。最后,通过使用Gurobi求解器求解该问题,算例采用四川省某含有径流式小水电和光伏的区域配电网数据,在IEEE33节点系统上进行实验验证。结果表明,所提模型有效降低了经济成本,提升了配电网的供电可靠性。

     

    Abstract: At present, the economic and reliability issues of power distribution networks urgently need to be solved due to the high proportion of renewable energy sources connected to them. To address this, this paper proposes a coordinated optimization model for power distribution networks that takes into account the uncertainty of hydro-photovoltaic-load. First, the Monte Carlo sampling method is used to generate scenarios for photovoltaic, hydro, and load, and then a backward scenario reduction method is used to obtain typical output scenarios. Second, the mixed integer nonlinear nonconvex model is transformed into a mixed integer second order cone programming problem using the second-order cone relaxation and big M method. Finally, the Gurobi solver is used to solve the problem, and the case study uses power distribution network data from a region in Sichuan Province containing hydro and photovoltaic power, which is verified on the IEEE33 node system. The results show that the proposed model effectively reduces economic costs and improves the supply reliability of the power distribution network.

     

/

返回文章
返回