引用本文: | 涂春鸣,董泰青,姜飞,刘子维.基于分层分区的配电网差异化节能规划方法研究[J].电力系统保护与控制,2015,43(14):148-154.[点击复制] |
TU Chunming,DONG Taiqing,JIANG Fei,LIU Ziwei.Research on differentiated energy saving method of partitioned distribution networks based on bi-level planning[J].Power System Protection and Control,2015,43(14):148-154[点击复制] |
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摘要: |
针对配电网节能规划的差异化和系统化问题,提出了一种考虑投资成本和节能效益的分层分区规划模型。上层规划在规定降损目标和总投资成本约束下,实现改造线路的优选及其投资金额的分配。下层规划模型以线路总支出费用最小为目标,满足各种运行约束和改造安装约束,生成节能改造优化组合方案。采用了线损预测和前推回代潮流计算相结合的混合算法对所提模型进行求解。实际对比某市节能技术改造方案的制定结果,验证了所提差异化节能规划方法的合理性和实用性。 |
关键词: 配电网 差异化 节能规划 二层规划模型 线损预测 |
DOI:10.7667/j.issn.1674-3415.2015.14.023 |
投稿时间:2014-09-30修订日期:2014-11-27 |
基金项目:国家自然科学基金项目(51377051) |
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Research on differentiated energy saving method of partitioned distribution networks based on bi-level planning |
TU Chunming,DONG Taiqing,JIANG Fei,LIU Ziwei |
(College of Electrical and Information Engineering, Hunan University, Changsha 410082, China) |
Abstract: |
Based on differentiated and systematic characteristic of energy saving programming in distribution networks, bi-level programming model for partitioned distribution network is established with considering investment cost and energy saving benefit. The determinate loss reduction target and total investment costs are used as the upper programming constraints, which satisfy optimal selection of reconstructive lines and its investment allocation. The follower programming objective is minimization of total expenditures, and its constraints are operation restricts and reconstruction restricts, which let energy saving reconstruction collaborative optimal schemes meet above requirements. Hybrid algorithm which integrates line loss prediction and forward and backward substitution flow calculation method is proposed to solve the above model. The results of examples and energy saving technological reconstruction programs in certain city verify the rationality and practicability of the proposed differentiated planning method. |
Key words: distribution networks differentiated energy saving planning bi-level programming model line loss prediction |