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电网技术 2009, 33(5) 48-53 DOI:
ISSN: 1000-3673 CN: 11-2410/TM |
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| 电力系统 |
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基于改进粒子群算法的节能调度下多目标负荷最优分配 |
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苏鹏 刘天琪 赵国波 张炯 |
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四川大学 电气信息学院，四川省 成都市 610065 |
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摘要：
在传统经济负荷分配模型的基础上，结合节能调度的宗旨，建立了系统有功网损最小和机组发电耗煤量最小的多目标负荷分配模型。该模型改进了基于Pareto最优概念的多目标粒子群算法，将其应用于多目标负荷最优分配，能对系统进行整体节能优化。IEEE 57节点系统仿真结果表明，该方法在满足系统的安全约束的同时，能降低系统网损和减少机组煤耗，有效节约能源。通过每次优化求得一组Pareto最优解集能够为决策者提供更多的有效参考，具有实际意义。 |
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关键词：
经济负荷分配
节能调度
粒子群算法
混沌优化
多目标优化
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An Improved Particle Swarm Optimization Based Multi-Objective Load Dispatch Under Energy Conservation Dispatching |
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SU Peng LIU Tian-qi ZHAO Guo-bo ZHANG Jiong |
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School of Electrical Engineering and Information，Sichuan University，Chengdu 610065，Sichuan Province，China |
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Abstract:
On the basis of traditional economic load dispatch and combining with the objectives of energy conservation dispatching, a multi-objective load dispatch model that considers minimum active network loss and minimum coal consumption of generating sets is built. The built model can optimize energy conservation of whole system. In this paper the multi-objective particle swam algorithm based on Pareto optimum is improved and applied to multi-objective optimal load dispatch. Simulation results of IEEE 57-bus test power system show that using the proposed method the network loss of power system and coal consumption of generating sets can be reduced, and energy source can be conserved, meanwhile, the security constraints of power system can be satisfied. Through each time of running of the proposed method, a group of Pareto optimal solution can be achieved, so that more effective references can be offered to decision-makers. |
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Keywords:
economic load dispatch
energy conservation dispatch
particle swarm algorithm
chaos optimization
multi-objective optimization
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收稿日期 2008-07-11 修回日期 1900-01-01 网络版发布日期 |
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DOI: |
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基金项目:
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通讯作者: 苏鹏 |
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作者简介: |
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作者Email: sptop@163.com |
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| 本刊中的类似文章 |
| 1．蒙文川|邱家驹|卞晓猛.电力系统经济负荷分配的人工免疫混沌优化算法[J]. 电网技术, 2006,30(23): 41-44 |
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