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Analysis of Infeasible Cases in Optimal Power Flow Problem

机译:最优潮流问题中不可行情况分析

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Abstract: In the context of smart grid transformation of existing electricity networks, optimal power flow (OPF) and security-constrained OPF (SCOPF) studies remain to be very important for power system planning, operation and market analysis. OPF study involves finding the (global) optimum solution to a set of nonlinear algebraic equations, subjected to a set of equality and inequality constraints. When the system is heavily stressed, particularly following a severe contingency, the conventional OPF methods may fail due to the problem or solution infeasibility, or inability to select proper initial values. The soft constraint handling approach and repetitive constraint relaxation in finding the causes of infeasibility could be either tedious, or may not be practical for the large-scale problems. This paper presents an alternative approach, based on use of meta-heuristic method, to pinpoint the main reasons for the failure of solution algorithms in nonlinear optimization, in general, and OPF problem, in particular. The presented approach is illustrated on commonly used IEEE 14-bus and 30-bus test networks.
机译:摘要: 在现有电网智能电网转型的背景下,优化潮流(OPF)和安全约束OPF(SCOPF)研究对于电力系统规划、运行和市场分析仍然具有重要意义。OPF 研究涉及找到一组非线性代数方程的(全局)最优解,并受到一组相等和不等式约束。当系统承受巨大压力时,特别是在发生严重意外事件后,传统的OPF方法可能会因问题或解决方案不可行或无法选择适当的初始值而失败。软约束处理方法和重复约束松弛在寻找不可行性原因时可能很乏味,或者对于大规模问题可能不切实际。本文提出了一种基于元启发式方法的替代方法,以查明解算法在非线性优化中失败的主要原因,特别是OPF问题。所提出的方法在常用的IEEE 14总线和30总线测试网络上进行了说明。

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