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Solving economic dispatch in competitive power market using improved particle swarm optimization algorithm

机译:改进粒子群算法求解竞争性电力市场中的经济调度

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Generally the generation units in the traditional structure of the electricity industry try to minimize their costs. However, in a deregulated environment, generation units are looking to maximize their profits in a competitive power market. Optimum generation planning in a such structure is urgent. This paper presents a new method of solving economic dispatch in the competitive electricity market with the aim of maximizing the total contribution profit of power generation. In this regard, with a combination of two intelligent optimization, a new efficient algorithm which called improved particle swarm optimization algorithm is suggested. The simulation of the new approach and conventional PSO algorithm were performed on two case study systems, 10-units and 15-units. According to the results, the suggested method not only resolves the convergence problem, but it also makes more efficient response.
机译:通常,电力行业传统结构中的发电机组试图将其成本降至最低。但是,在放松管制的环境中,发电机组希望在竞争激烈的电力市场中最大化其利润。在这样的结构中优化发电计划是当务之急。本文提出了一种在竞争激烈的电力市场中解决经济调度的新方法,旨在最大化发电的总贡献利润。在这方面,结合两个智能优化,提出了一种新的有效算法,即改进的粒子群算法。在两个案例研究系统(10个单元和15个单元)上对新方法和常规PSO算法进行了仿真。根据结果​​,所提出的方法不仅解决了收敛性问题,而且使响应更加有效。

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