| 基于解集动态分析含风电接入的多目标机组组合研究 |
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| 引用本文： | 陈光宇,张仰飞,郝思鹏,张友泉,李军,张小莲. 基于解集动态分析含风电接入的多目标机组组合研究[J]. 电力自动化设备, 2018, 38(7) |
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| 作者姓名： | 陈光宇 张仰飞 郝思鹏 张友泉 李军 张小莲 |
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| 作者单位： | 南京工程学院电力工程学院;国网山东省电力公司发展策划部 |
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| 基金项目： | 国家自然科学基金资助项目(51607083)；江苏省配电网智能技术与装备协同创新中心开放基金资助项目(XTCX201713) |
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| 摘 要： | 风电的大规模接入给多目标节能减排发电调度带来了新的机遇和挑战。由于风电场出力具有随机性,采用置信区间简化风电场景模拟数量,考虑到多目标模型的复杂性,利用Benders分解技术对模型进行降维,设计一种基于解集动态分析的多目标自适应优化算法对降维后的多目标主问题进行求解,并提出一种提高模型整体求解效率的预处理机制加速收敛。仿真结果表明所提方法能够有效求解含风电的多目标机组组合问题,并验证了所提多目标算法和预处理机制在求解模型中的优势。
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| 关 键 词： | 风电；机组组合；Benders分解；多目标优化；预处理机制 |
Multi-objective unit commitment with wind farms based on dynamic analysis of solution set |
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| CHEN Guangyu,ZHANG Yangfei,HAO Sipeng,ZHANG Youquan,LI Jun and ZHANG Xiaolian. Multi-objective unit commitment with wind farms based on dynamic analysis of solution set[J]. Electric Power Automation Equipment, 2018, 38(7) |
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| Authors: | CHEN Guangyu ZHANG Yangfei HAO Sipeng ZHANG Youquan LI Jun ZHANG Xiaolian |
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| Affiliation: | School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China,School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China,School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China,Department of Development and Planning, State Grid Shandong Electric Power Co.,Ltd.,Jinan 250001, China,School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China and School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China |
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| Abstract: | The large-scale access of wind power brings new opportunities and challenges to the multi-objective energy-saving and emission-reduction generation scheduling. The confidence interval is used to simplify the simulation quantity of wind power scenario due to the randomness of wind farm output. Taking into account the complexity of multi-objective model, the Benders decomposition technique is adopted to reduce the dimension of the model. A multi-objective adaptive optimization algorithm based on the dynamic analysis of solution set is proposed to solve the multi-objective master problem after dimension reduction, and a pretreatment mechanism for improving the overall solving efficiency of the model is proposed to speed up the convergence. The simulative results show that the proposed method can effectively solve the multi-objective unit commitment problem with wind power, and verify the advantages of the proposed multi-objective algorithm and pretreatment mechanism in solving the model. |
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| Keywords: | wind power unit commitment Benders decomposition multi-objective optimization pretreatment mechanism07 |
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