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Research on a two-stage optimization algorithm for multi-objective reactive power optimization of distribution network

机译:配电网多目标无功优化的两阶段优化算法研究

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This paper proposes a two-stage optimization algorithm for multi-objective reactive power optimization of distribution network. In the first stage, an approximate Pareto solution set is obtained using traditional multi-objective optimization algorithm. Then the preferred area for searching is calculated with the preference information of Decision Maker (DM) and the approximate Pareto solutions. In the second stage, an improved dominance relation is proposed to guide the particles of multi-objective particle swarm optimization(MOPSO) to focus on a deep searching in preferred area, with a high calculation efficiency. The case in IEEE 33-node system verifies that compared with the traditional multi-objective reactive power optimization, the method proposed in this paper has a large improvement in generation distance(GD), spacing(SP), error ration(ER) and reduce the optimization time.
机译:提出了配电网多目标无功优化的两阶段优化算法。在第一阶段,使用传统的多目标优化算法获得近似的Pareto解集。然后,使用决策者(DM)的偏好信息和近似的Pareto解计算首选的搜索区域。在第二阶段中,提出了一种改进的优势关系,以指导多目标粒子群优化算法(MOPSO)的粒子聚焦于优选区域的深度搜索,具有较高的计算效率。以IEEE 33节点系统为例,验证了与传统的多目标无功优化方法相比,本文提出的方法在发电距离(GD),间距(SP),误码率(ER)上有较大的提高,降低了优化时间。

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