论文标题
分配系统中最佳功率流的二次凸近似，并应用损失分配
A Quadratic Convex Approximation of Optimal Power Flow in Distribution System with Application in Loss Allocation
论文作者
论文摘要
In this paper, a novel quadratic convex optimal power flow model, namely, MDOPF, is proposed to determine the optimal dispatches of distributed generators. Based on the results of MDOPF, two price mechanisms, distribution locational marginal price (DLMP) and distribution locational price (DLP), are analyzed. For DLMP, an explicit method is developed to calculate the marginal loss that does not require a backward/forward sweep algorithm and thus reduces the computational complexity.但是，DLMP中的边际损失成分将导致损失过度收集（OCL）。 To address this issue, DLP is defined, which contains two components, the energy cost component and loss component, where the loss component is determined by the proposed loss allocation method (LAM).数值测试表明，所提出的MDOPF的精度比基于线性功率流程方程的现有OPF模型更好。 In addition, the proposed marginal loss method and DLMP algorithm have satisfactory accuracy compared with benchmarks provided by ACOPF, and the proposed DLP can eliminate OCL.
In this paper, a novel quadratic convex optimal power flow model, namely, MDOPF, is proposed to determine the optimal dispatches of distributed generators. Based on the results of MDOPF, two price mechanisms, distribution locational marginal price (DLMP) and distribution locational price (DLP), are analyzed. For DLMP, an explicit method is developed to calculate the marginal loss that does not require a backward/forward sweep algorithm and thus reduces the computational complexity. However, the marginal loss component in DLMP will cause over-collection of losses (OCL). To address this issue, DLP is defined, which contains two components, the energy cost component and loss component, where the loss component is determined by the proposed loss allocation method (LAM). Numerical tests show that the proposed MDOPF has a better accuracy than existing OPF models based on linear power flow equations. In addition, the proposed marginal loss method and DLMP algorithm have satisfactory accuracy compared with benchmarks provided by ACOPF, and the proposed DLP can eliminate OCL.
