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EFFECTS OF EQUALITY CONSTRAINT HANDLING ON ECONOMIC DISPATCH USING DIFFERENTIAL EVOLUTION ALGORITHMS

机译:运用差分进化算法处理平等约束对经济分配的影响

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摘要

Heuristic optimization is an efficient method to solve non-convex economic dispatch (ED) problems. In the past decade, several heuristic algorithms have been developed to improve quality of the ED result. However, those improvements are still inconclusive whether they are contributed to the power of the optimization algorithm itself or the influence of the constraint handling technique. In this paper, the hypothesis is that the strategy for dealing with the power balance (equality) constraint has the greater influence to the solution quality than the optimization algorithm. Therefore, this paper investigates the effects of this strategy on reliability and accuracy of the ED result. Four different DE algorithms are applied as the optimizers. The simulation results on a 15-generator power system confirm that the formulated hypothesis is true. It is also found out that with such a strategy a greedy algorithm searching around the local best converges faster than other algorithms.
机译:启发式优化是解决非凸经济调度(ED)问题的有效方法。在过去的十年中,已经开发了几种启发式算法来提高ED结果的质量。但是,无论这些改进是对优化算法本身的力量还是对约束处理技术的影响,这些改进仍然是不确定的。本文的假设是,与优化算法相比,处理功率平衡(均等)约束的策略对解决方案质量的影响更大。因此,本文研究了该策略对ED结果的可靠性和准确性的影响。四种不同的DE算法被用作优化器。在15发电机电力系统上的仿真结果证实了所提出的假设是正确的。还发现,使用这种策略,搜索局部最佳的贪婪算法比其他算法收敛更快。

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