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Security-and time-constrained OPF applications

机译:受安全和时间限制的OPF应用程序

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Optimal power flow (OPF) and security-constrained OPF (SCOPF) studies are important tools for both planning and operation of power supply systems. Conventional gradient-based SCOPF methods are commonly used for that purpose, but when analysed system is overstressed with severe multiple contingencies, conventional SCOPF methods may fail to converge. In such cases, meta-heuristic SCOPF methods can be used to identify “critical constraints” and help the convergency of conventional methods. As the time available for devising emergency control actions is typically limited, the paper first evaluates computational performance of used meta-heuristic SCOPF method (particle swarm optimization method) and then demonstrates how a suitable handling of constraints, i.e. penalization of objective function, can improve efficiency and practical value of the solutions found by the meta-heuristic SCOPF method. This approach is denoted as “time-constrained SCOPF analysis” and is illustrated by considering thermal limits of overloaded lines in a widely-used IEEE 14-bus test network.
机译:最佳潮流(OPF)和受安全约束的OPF(SCOPF)研究是电源系统规划和运行的重要工具。常规的基于梯度的SCOPF方法通常用于该目的,但是当分析的系统因严重的多种意外事件而承受过重压力时,常规的SCOPF方法可能无法收敛。在这种情况下,元启发式SCOPF方法可用于识别“关键约束”并帮助传统方法的收敛性。由于通常可用于制定应急控制措施的时间有限,因此本文首先评估所使用的元启发式SCOPF方法(粒子群优化方法)的计算性能,然后论证如何适当地处理约束(即对目标函数的惩罚)亚启发式SCOPF方法发现的解的效率和实用价值。这种方法被称为“时间受限的SCOPF分析”,并通过在广泛使用的IEEE 14总线测试网络中考虑过载线路的热极限来进行说明。

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