| 引用本文: | 王蓬蓬,宋运忠.计及最恶劣场景概率和供需灵活性的综合能源系统分布鲁棒低碳优化调度[J].电力系统保护与控制,2024,52(13):78-89.[点击复制] |
| WANG Pengpeng,SONG Yunzhong.Distributed robust low-carbon optimal scheduling of an integrated energy system considering worst-case scenario probability and flexibility of supply and demand[J].Power System Protection and Control,2024,52(13):78-89[点击复制] |
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| 摘要: |
| 随着可再生能源渗透率的提升，其不确定性给综合能源系统(integrated energy system, IES)的经济性和鲁棒性带来了极大挑战。为了促进可再生能源消纳以及降低碳排放量，提出了一种基于数据驱动的分布鲁棒优化(distributionally robust optimization, DRO)调度策略。首先，构建了由有机朗肯循环(organic Rankine cycle, ORC)、氢燃料电池和电动汽车等构成的供需灵活响应模型，并引入阶梯碳交易机制来约束系统碳排放量。其次，为了能获取最恶劣情况下的场景概率分布，采用综合范数对风电输出场景的概率分布置信集合进行约束。然后，以在最恶劣场景概率分布下综合能源系统运行总成本最低为目标建立两阶段鲁棒优化模型，并通过列和约束生成(column and constraint generation, CCG)算法对模型进行迭代求解。最后，算例仿真结果表明了所提模型和求解方法的有效性，并分析了阶梯碳交易机制和供需灵活响应模型对提高系统灵活性和低碳经济性的影响。 |
| 关键词: 综合能源系统 供需灵活性 阶梯碳交易 数据驱动 分布鲁棒优化 |
| DOI：10.19783/j.cnki.pspc.231146 |
| 投稿时间：2023-09-04修订日期：2024-01-15 |
| 基金项目:国家自然科学基金项目资助(61340041，61374079)；河南省自然科学基金项目资助(182300410112) |
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| Distributed robust low-carbon optimal scheduling of an integrated energy system considering worst-case scenario probability and flexibility of supply and demand |
| WANG Pengpeng,SONG Yunzhong |
| (School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454003, China) |
| Abstract: |
| As the penetration of renewable energy increases, its uncertainty poses great challenges to the economics and robustness of integrated energy systems. To promote renewable energy consumption and reduce carbon emissions, a data-driven distributionally robust optimization (DRO) scheduling strategy is proposed. First, a flexible supply and demand response model consisting of an organic Rankine cycle (ORC), hydrogen fuel cell and electric vehicle is constructed, and a stepped carbon trading mechanism is introduced to constrain the carbon emissions of the system. Secondly, in order to obtain the probability distribution of the scene in the worst case, a comprehensive norm is used to constrain the probability distribution confidence set of the wind power output scene. Then, a two-stage robust optimization model is established with the goal of minimizing the total cost of integrated energy system (IES) operation in the worst scenario probability distribution, and the model is iteratively analyzed by a column and constraint generation (CCG) algorithm. Finally, the simulation results show the effectiveness of the proposed model and solution method. It also analyzes the influence of the ladder carbon trading mechanism and the supply and demand flexible response model in improving the system flexibility and low-carbon economy. |
| Key words: integrated energy system supply-demand flexibility ladder carbon trading data-driven distributionally robust optimization |
