论文标题
一种基于灵敏度的方法,用于最佳分布式能源资源
A Sensitivity-based Approach for Optimal Siting of Distributed Energy Resources
论文作者
论文摘要
本文提出了一种基于灵敏度的方法,用于放置电力系统中分布式能源(DER)。该方法基于以下事实:大多数计划研究都利用某种形式的优化,而解决这些优化问题的解决方案为许多系统变量对操作条件和约束的敏感性提供了见解。但是,大多数基于灵敏度的计划标准并未捕获这些解决方案的有效性范围(即,Lagrange乘数的有效性范围)。所提出的方法检测到拉格朗日乘数的有效性的范围,并使用它们来确定最佳解决方案替代方案。考虑到现有发电和负载以及传输约束的轮廓。所提出的方法用于在存在随机元素(负载变异性)的情况下确定不同位置的DER的影响。此方法包括针对所有负载方案的各种负载总线的优化问题的双重解决方案的Lagrange乘数。根据主动约束的有效性,以顺序确定资源的最佳大小和资源位点。通过对各种测试系统(包括IEEE可靠性测试系统(IEEE RTS),IEEE 14和30 BUS系统)的几个案例研究,该方法的有效性证明了所提出的方法的有效性。与传统的基于灵敏度的方法相比(即,不考虑拉格朗日乘数的有效性范围),该方法为主动约束提供了更准确的结果。
This paper presents a sensitivity-based approach for the placement of distributed energy resources (DERs) in power systems. The approach is based on the fact that most planning studies utilize some form of optimization, and solutions to these optimization problems provide insights into the sensitivity of many system variables to operating conditions and constraints. However, most of the existing sensitivity-based planning criteria do not capture ranges of effectiveness of these solutions (i.e., ranges of the effectiveness of Lagrange multipliers). The proposed method detects the ranges of the effectiveness of Lagrange multipliers and uses them to determine optimal solution alternatives. Profiles for existing generation and loads, and transmission constraints are taken into consideration. The proposed method is used to determine the impacts of DERs at different locations, in the presence of a stochastic element (load variability). This method consists of sequentially calculating Lagrange multipliers of the dual solution of the optimization problem for various load buses for all load scenarios. Optimal sizes and sites of resources are jointly determined in a sequential manner based on the validity of active constraints. The effectiveness of the proposed method is demonstrated through several case studies on various test systems including the IEEE reliability test system (IEEE RTS), the IEEE 14, and 30 bus systems. In comparison with conventional sensitivity-based approaches (i.e., without considering ranges of validity of Lagrange multipliers), the proposed approach provides more accurate results for active constraints.