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文章摘要
基于改进多目标粒子群算法的微网双层优化调度策略
Bilevel Optimization Scheduling Strategy Based on Improved MOPSO
Received:April 17, 2017
Revised:April 17, 2017
DOI：
中文关键词
:
微网
多目标优化
双层优化
栅格法
拥挤度
组合赋权法
英文关键词
:
microgrid
multi-objective optimization
bilevel optimization
grid method
digree of congestion
combinatorial weighting method
基金项目
:
Author Name
Affiliation
E-mail
Li Xuesong
*
Intelligent Electric Power Grid Key Laboratory of Sichuan Province (Sichuan University)
songerbuer@163.com
Teng Huan
Intelligent Electric Power Grid Key Laboratory of Sichuan Province (Sichuan University)
13308027191@163.com
Guo Ning
Intelligent Electric Power Grid Key Laboratory of Sichuan Province (Sichuan University)
879861360@qq.com
Liang Mengke
Intelligent Electric Power Grid Key Laboratory of Sichuan Province (Sichuan University)
1347289030@qq.com
Wu Zeqiong
Intelligent Electric Power Grid Key Laboratory of Sichuan Province (Sichuan University)
519129907@qq.com
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中文摘要
:
本文综合考虑微网经济成本、环保成本和系统运行风险程度,建立了多目标优化调度模型,并在迭代末期引入了双层优化,解决了传统优化模型容易漏选最佳解的问题。针对传统多目标粒子群算法的缺陷,提出了基于“栅格-拥挤度”协同筛选策略的多目标粒子群算法。当外部档案中粒子较少时,采用栅格法筛选出全局最优值,当外部档案中粒子较多时,改用拥挤度排序法,从而增强了解集的收敛性和多样性。在下层模型中,建立了基于相对熵组合赋权法的决策算法,综合了主/客观赋权法的优势,使最终结果更加合理。最后以一小型微网为例,验证了考虑双层优化的必要性和改进MOPSO的优越性。
英文摘要
:
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