| 引用本文: | 郑晓东,陈皓勇,段声志,黄剑平.基于场景概率驱动的输电网和储能分布鲁棒规划[J].电力自动化设备,2022,42(6): |
| ZHENG Xiaodong,CHEN Haoyong,DUAN Shengzhi,HUANG Jianping.Distributionally robust planning of transmission network and energy storage based on scenario probability-driven[J].Electric Power Automation Equipment,2022,42(6): |
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| 摘要: |
| 在碳达峰和碳中和的目标要求下，可再生能源+储能被认为是一种能够有效促进新能源消纳的手段。传统的3层鲁棒规划方法在进行输电网和储能联合优化时忽略了风电出力场景的概率信息，所得投资决策往往过于保守。为此，利用风电出力场景的历史数据构建了基于[L1]-范数和[L∞]-范数的混合概率分布不确定集，在考虑最恶劣概率分布的情况下进行输电网和储能的最优投资决策，能够改善传统鲁棒规划方法过于保守的问题。此外，采用一种可并行计算的列和约束生成算法求解所建模型，在求解max-min内层问题时不需要进行复杂的对偶转换，且无需求解双线性项，只需要并行求解若干个小规模的线性规划问题，有效提高了求解效率。Garver 6节点系统算例的仿真结果验证了所建模型和算法的有效性。 |
| 关键词: 输电网 储能 概率分布 列和约束生成算法 场景概率驱动 分布鲁棒规划 |
| DOI：10.16081/j.epae.202205019 |
| 分类号:TM715 |
| 基金项目:国家自然科学基金重点资助项目(51937005)；广东省自然科学基金面上项目(2019A1515010689) |
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| Distributionally robust planning of transmission network and energy storage based on scenario probability-driven |
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ZHENG Xiaodong, CHEN Haoyong, DUAN Shengzhi, HUANG Jianping
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School of Electric Power Engineering, South China University of Technology, Guangzhou 510641, China
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| Abstract: |
| Under the requirement of carbon peak and carbon neutrality targets, the coordination of renewable energy and energy storage is considered to be an effective means to promote the consumption of new energy. The traditional three-layer robust planning method ignores the probability information of wind power output scenarios when carrying out the joint optimization of transmission network and energy storage, and the obtained investment decisions are often too conservative. Therefore, the uncertainty sets of mixed probability distribution based on [L1]-norm and [L∞]-norm are constructed by using the historical data of wind power output scenarios, and the optimal investment decision of transmission network and energy storage is made under the worst probability distribution condition, which can improve the problem that the traditional robust planning method is too conservative. In addition, a parallel computable column-and-constraint generation algorithm is used to solve the model, which does not need to perform complex dual transformation and solve double-linear term in solving max-min inner layer problem, but only needs to solve several small-scale linear planning problems in parallel, effectively improving the solving efficiency. The simulative results of Garver 6-bus system verify the effectiveness of the proposed model and algorithm. |
| Key words: transmission network energy storage probability distribution column-and-constraint generation algorithm scenario probability-driven distributionally robust planning |
