基于精英群引导量子进化算法的电力系统最优经济调度

Sheng Xiang, Yigang He
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引用次数: 2

摘要

随着中国电力系统被划分为五大电网,形成了不同的利益相关者,因此五大电网内部存在竞争。此外,电力工业造成的污染变得严重。因此,电力系统的最优经济调度具有十分重要的意义。通过优化,电网不仅可以通过降低成本来增加收益,还可以减少污染。然而,电力系统优化调度是一个复杂的多目标问题。本文采用精英群体引导的量子启发进化算法。每次迭代的精英群体由当前种群中一定数量的适应度值较好的个体组成,精英群体中的所有个体共同合作影响量子启发门产生后代。作为一种加权状态偏好,它可以推动个体的基因向状态1进化。仿真结果表明,该算法是有效的。
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Optimal Economic Scheduling of Electric Power System Based on Elite Group Guided Quantum-Inspired Evolutionary Algorithms
With the power system in China had been divided into five major power grid, different stakeholders have been formed, so there is internal competition in the five major power grid. Furthermore, the pollution caused by power industry become seriously. So optimal economic scheduling of electric power system is very important. By optimization, the grid can not only increase revenue by reduce costs, but also can reduce pollution. However, power system optimal dispatch is a complicated and multi-object problem. In this paper, elite group guided quantum-inspired evolutionary algorithm has been adopted. The elite group at each iteration is composed of a certain number of individuals with better fitness values in the current population, all the individuals in the elite group cooperate together to affect quantum-inspired gates to produce off spring. As a weighted state preference can push the genes of individuals to evolve toward state '1'. Simulation results show that the new algorithm is effective.
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