Genetic algorithm-based power transmission expansion planning
作者： A.R. Abdelaziz
DOI: 10.1109/ICECS.2000.912959
关键词: Enumeration 、 Genetic algorithm 、 Power transmission 、 Transformer 、 Population 、 Nonlinear system 、 Reliable transmission 、 Optimization problem 、 Mathematics 、 Mathematical optimization
摘要: Large-scale combinatorial problems such as the network expansion problem present an amazingly high number of alternative configurations with practically same investment, but substantially different structures (configurations obtained sets circuit/transformer additions). This paper presents a development genetic algorithm (GA) and its application to least-cost reliable transmission expansion-planning (TEP) problem. TEP is concerned highly constrained nonlinear dynamic optimization that can only be fully solved by complete enumeration, process computationally impossible in real-world In this paper, GA incorporating stochastic reproduction technique artificial initial population scheme are developed provide faster search mechanism. The objective optimize system adequacy (cost, reliability). proposed string represents reinforcement ways, which limited certain ways for each line system, subjected total prespecified maximum reinforcements well project budget. Excellent performance reported test results.
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