| 引用本文: | 王瑞琪,张承慧,李 珂,陈阿莲,杜春水.基于小生境遗传算法的微电网控制与优化[J].电力自动化设备,2013,33(8): |
| WANG Ruiqi,ZHANG Chenghui,LI Ke,CHEN Alian,DU Chunshui.Control and optimization based on niche genetic algorithm for microgrid[J].Electric Power Automation Equipment,2013,33(8): |
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| 基于小生境遗传算法的微电网控制与优化 |
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王瑞琪1,2, 张承慧1,2, 李 珂1,2, 陈阿莲1,2, 杜春水1,2
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1.山东大学 控制科学与工程学院，山东 济南 250061;2.山东大学 电力电子节能技术与装备教育部工程中心，山东 济南 250061
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| 摘要: |
| 提出一种基于小生境遗传算法的微电网控制策略及优化方法。建立整个微电网的小信号动态模型，分析得到影响微电网运行特性的主要控制参数及其优化取值域，有效提高了优化过程的计算效率。为构建准确的优化目标函数，采用PSCAD／EMTDC搭建微电网平台并进行各种工作模式及模式切换的时域仿真。针对传统遗传算法存在的非全局性收敛、收敛速度慢等问题，采用小生境技术和自适应技术改进的遗传算法优化微电网的运行特性。算例分析结果验证了所提微电网控制策略及优化方法的有效性和鲁棒性。 |
| 关键词: 微电网 小信号模型 小生境技术 遗传算法 优化 控制 |
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| 基金项目:国家高技术研究发展计划（863计划）资助项目（2009AA05Z212）；国家自然科学基金资助项目（51107069） |
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| Control and optimization based on niche genetic algorithm for microgrid |
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WANG Ruiqi1,2, ZHANG Chenghui1,2, LI Ke1,2, CHEN Alian1,2, DU Chunshui1,2
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1.School of Control Science and Engineering，Shandong University，Ji’nan 250061，China;2.Engineering Center of Power Electronic Saving Technology and Equipment，Shandong University，Ji’nan 250061，China
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| Abstract: |
| A control strategy and optimization method based on the niche genetic algorithm is proposed for microgrid. In order to effectively improve the optimization efficiency，a small-signal dynamic model of whole microgrid is built and the main control parameters，which influence the operating performance of microgird，and their optimum ranges are obtained by analysis. For establishing the accurate objective function of optimization，the microgrid platform is built based on PSCAD／EMTDC and the time-domain simulation is carried out for different operating modes and corresponding mode switching of microgrid. Aiming at the non-global convergence and slow convergence rate of traditional genetic algorithm，a genetic algorithm improved by niche technique and adaptive technique is adopted to optimize the operating performance of microgrid. The result of example analysis verifies the validity and robustness of the proposed control strategy and optimization method. |
| Key words: microgrid small-signal model niche technology genetic algorithms optimization control |
