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首页> 外文期刊>Electric Power Components and Systems >Optimal Contract Capacities for Time-of-Use Rate Industrial Customers Using Stochastic Search Algorithms
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Optimal Contract Capacities for Time-of-Use Rate Industrial Customers Using Stochastic Search Algorithms

机译:使用随机搜索算法的工时费率工业客户的最佳合同能力

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摘要

This paper presents two stochastic search algorithms for optimizing the contract capacities of time-of-use (TOU) rate industrial customers. The proposed genetic algorithm (GA) and evolutionary algorithm (EA) are used to search the optimal contract capacities for the TOU rate customers to minimize the summation of demand and penalty charges. Because of the global search capabilities of the GA and EA, the proposed algorithms can optimize the solutions of the complicated, nondifferentiable, optimal contract capacity problem. The, proposed algorithms have been tested on a three-section TOU rate industrial customer of Taipower system and are compared with the existing method. The test results demonstrate that the proposed algorithms can efficiently optimize the contract capacities for TOU rate customers.
机译:本文提出了两种随机搜索算法,以优化使用时间(TOU)费率的工业客户的合同能力。提出的遗传算法(GA)和进化算法(EA)用于搜索TOU费率客户的最佳合同容量,以最大程度地减少需求和罚款的总和。由于GA和EA具有全局搜索功能,因此所提出的算法可以优化复杂,不可微,最优合同容量问题的解决方案。所提出的算法已经在台电系统的三段式分时电价工业用户上进行了测试,并与现有方法进行了比较。测试结果表明,所提出的算法可以有效地优化TOU费率客户的合同能力。

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