| 引用本文: | 靳绍珍,毛志忠,李鸿儒.考虑不确定性因素的微电网经济运行的优化[J].控制理论与应用,2018,35(9):1357~1370.[点击复制] |
| JIN Shao-zhen,MAO Zhi-zhong,LI Hong-ru.Economic operation optimization of smart micro grid considering the uncertainty[J].Control Theory and Technology,2018,35(9):1357~1370.[点击复制] |
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| 考虑不确定性因素的微电网经济运行的优化 |
| Economic operation optimization of smart micro grid considering the uncertainty |
| 摘要点击 2223 全文点击 1231 投稿时间：2017-11-23 修订日期：2018-06-28 |
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| DOI编号 10.7641/CTA.2018.70862 |
| 2018,35(9):1357-1370 |
| 中文关键词 微电网 经济运行 场景束 动态规划 |
| 英文关键词 smart micro grid economic operation optimization scenario bundling dynamic programming algorithm |
| 基金项目 国家自然科学基金项目(61164015, 61305132)资助, 辽宁省自然科学基金项目资助. |
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| 中文摘要 |
| 本文针对微电网经济运行优化问题, 考虑分布式可再生能源的输出功率具有随机性特点, 提出了一种基于场景
分解及场景策略聚合机制的优化方法. 该方法针对所提出的优化问题中, 统计信息不足以建立一个随机规划模型的难
点, 首先进行了场景分析, 将原优化问题分解为多个场景子优化问题; 其次引入场景束约束, 将场景策略分为可容许策
略、可实现策略和偶然策略, 依照可用信息的进化机制, 迭代修正每个场景子优化问题, 并且采用动态规划方法求解每
个场景子优化问题. 然后, 统计分析子优化问题最优解的主要特征和趋势, 最终得到微电网经济运行优化问题的最优解.
通过仿真验证了所提出方法的有效性. |
| 英文摘要 |
| According to economic dispatch problem of smart micro grid considering the uncertainty, a methodology
based on scenarios and policy aggregation was associated. The difficulty lies in the fact that statistical information was
not really enough to support a stochastic programming model. In the presented method, a number of scenarios were analyzed;
meanwhile, sub-problems were derived from the optimization problems considering the uncertainty. Moreover, an
information structure by scenario bundling was introduced. At the same time, the policies were divided into admissible
policies, implementable policies, and contingent policies; iterative adjustments according to available information evolved
mechanism are made to the decision policy to adapt to this information structure. Consequently, dynamic programming
algorithm was applied to solve the sub problems. Finally, the overall result of the investigated problem considering uncertainty
was obtained by identified trends and essential features on the solution of the sub problems. The study on case proves
the validity of this optimization methodology. |
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