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Optimal placement and sizing of DG (distributed generation) units in distribution networks by novel hybrid evolutionary algorithm

机译:新型混合进化算法优化配电网中DG(分布式发电)单元的布局和规模

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摘要

This paper presents an interactive fuzzy satisfying method, which is based on Hybrid Modified Shuffled Frog Leaping Algorithm, and should solve the problem of the Multi-objective optimal placement and sizing of DG (distributed generation) units in the distribution network. Minimizing total electrical energy losses, total electrical energy cost and total pollutant emissions produced are the objective functions in this problem. Also, the improvement of the voltage profile is considered as a constraint in determining the optimal placement. In the proposed method, the objective functions are modeled with fuzzy sets. The multi-objective problem is transformed into a mini-max problem, which is then handled by the proposed evolutionary algorithm. Finally, the proposed algorithm is tested on a 69-bus distribution test system based on technical, economical and environmental protection considerations. The simulation results illustrate the good performance and applicability of the proposed method.
机译:本文提出了一种基于混合改进的随机蛙跳算法的交互式模糊满足方法,该方法应解决配电网中DG(分布式发电)机组的多目标最优布置和规模确定问题。使总电能损失,总电能成本和产生的总污染物排放最小化是此问题的目标功能。而且,电压分布的改善被认为是确定最佳放置的约束。在提出的方法中,目标函数用模糊集建模。将多目标问题转换为极大极小问题,然后由提出的进化算法处理。最后,基于技术,经济和环保考虑,在69总线配电测试系统上对提出的算法进行了测试。仿真结果表明了该方法的良好性能和适用性。

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