基于改进和声搜索算法的电网多目标差异化规划

发布时间：2018-11-15 20:27

【摘要】：为提高电网的抗灾能力需对电网进行差异化规划。用全寿命周期内的新增成本和减损效益对规划的经济性和可靠性进行量化,建立了多目标差异化规划优化模型。根据Pareto支配关系制定寻优准则,以效益成本比最大为目标从Pareto解集中选择最优的差异化规划方案。将和声搜索算法应用于模型的求解,引入混沌映射、动态参数设置、改进的音高调整策略以及和声寻优信息共享机制使其能够解决0-1规划问题,并提高其搜索性能。对IEEE 30节点算例的分析表明,该模型正确合理,能得到最优规划方案。与常规的遗传算法和粒子群优化算法进行对比,改进和声搜索算法收敛速度快,具有较好的适应性和鲁棒性。
[Abstract]:In order to improve the disaster-resistant ability of the power grid, it is necessary to carry on the differentiation planning to the power grid. The optimization model of multi-objective differential programming is established by quantifying the economy and reliability of the program by using the added cost and reduced benefit in the whole life cycle. According to the Pareto dominance relationship, the optimization criterion is established, and the optimal differential programming scheme is selected from the Pareto solution set with the maximum ratio of benefit to cost as the goal. The harmonic search algorithm is applied to the solution of the model, and chaotic mapping, dynamic parameter setting, improved pitch adjustment strategy and information sharing mechanism of harmonic optimization are introduced to solve the 0-1 programming problem and improve its search performance. The analysis of IEEE 30-node example shows that the model is correct and reasonable, and the optimal programming scheme can be obtained. Compared with the conventional genetic algorithm and particle swarm optimization algorithm, the improved harmonic search algorithm has fast convergence speed, good adaptability and robustness.
【作者单位】：武汉大学电气工程学院;
【基金】：国家自然科学基金资助项目(51207114) 国家电网公司大电网重大专项资助项目课题(SGCC-MPLG029-2012)~~
【分类号】：TM715

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