| 引用本文: | 邱 威,张建华,吴 旭,刘力华.采用混沌多目标差分进化算法并考虑协调运行的环境经济调度[J].电力自动化设备,2013,33(11): |
| QIU Wei,ZHANG Jianhua,WU Xu,LIU Lihua.Environmental and economic dispatch based on chaotic multi-objective differential evolution algorithm considering coordinative operation[J].Electric Power Automation Equipment,2013,33(11): |
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| 摘要: |
| 针对传统环境经济调度（EED）策略会导致部分线路运行在重载或过载状态的问题，建立考虑系统协调运行的多目标EED模型，其中协调性指标定义为各支路负载率的标准差。提出一种混沌多目标差分进化（CMODE）算法来求解模型，CMODE算法将基于非支配排序的种群分级机制与差分进化算法有机融合，并引入基于Tent混沌映射的种群初始化和控制参数动态调整策略以提高算法的全局寻优能力。IEEE 30节点测试系统结果表明，与不考虑运行协调性的EED相比，在发电调度模型中计及协调性指标可提高电网安全运行水平。 |
| 关键词: 电力系统 环境经济调度 协调运行 优化 差分进化 Tent映射 模型 |
| DOI： |
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| 基金项目:国家自然科学基金资助项目（51007022） |
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| Environmental and economic dispatch based on chaotic multi-objective differential evolution algorithm considering coordinative operation |
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QIU Wei1, ZHANG Jianhua2, WU Xu2, LIU Lihua1
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1.National Electric Power Dispatching and Control Center，Beijing 100031，China;2.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources，North China Electric Power University，Beijing 102206，China
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| Abstract: |
| Because the traditional EED（Environmental and Economic Dispatch） may cause part of lines operating in heavy or over load condition，a multi-objective EED model considering the coordinative operation of power systems is built，in which，the coordination index is defined as the standard deviation of branch load ratings. CMODE（Chaotic Multi-Objective Differential Evolution） algorithm is applied to solve the model，which combines the population grading mechanism based on non-dominated sorting with the differential evolution algorithm and adopts the population initialization based on Tent chaos mapping and the dynamic control parameter adjustment to improve the global optimization ability. The results of its application in IEEE 30-bus test system show that，compared with the EED without the consideration of coordinative operation，the safe operating level of power system is enhanced. |
| Key words: electric power systems environmental and economic dispatch coordinative operation optimi-zation differential evolution Tent mapping models |
