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首页 > 过刊浏览>2022年第37卷第3期 >19-32. DOI:10.19781/j.issn.1673-9140.2022.03.003
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计及不确定性和混合储能设备的综合能源系统多目标优化调度模型
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TM732

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国网宁夏电力有限公司科技项目(5229JY190014)


Multi-objective optimal scheduling model for multi-energy system considering uncertainty and hybrid energy storage devices
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    摘要:

    为提高综合能源系统内可再生能源消纳水平,量化不确定性机组出力对系统调度的影响,首先构建包含氢能—天然气混合储能的综合能源系统,分析混合储能在系统中的运行特性;其次,构建综合能源系统多目标优化调度模型,利用多目标CVaR方法对风电机组不确定性风险进行描述;然后,采用模糊C均值—综合质量评估方法(FCM-CCQ)与改进的粒子群算法将系统不确定性问题转化为确定性问题;最后,分别求解不考虑不确定性的单目标优化结果和考虑不确定性的综合目标优化结果。结果表明:混合储能设备能够有效地提高可再生能源消纳水平,实现能量的多级转化;可再生能源不确定性将增加综合能源系统综合成本,系统风险承受能力越强,调度结果越优。

    Abstract:

    Aiming at improving the renewable energy consumption level in the multi-energy system and quantify the influence of uncertain unit output on system scheduling, a multi-energy system containing hydrogen and gas energy storage is constructed and the operation characteristics of hybrid energy storage in the system are analyzed in this paper. Then, a multi-objective optimal scheduling model for multi-energy systems is proposed, and the uncertainty risk of wind turbines is described by the multi-objective conditional value at risk method. In addition, the fuzzy C-mean-comprehensive quality assessment and improved particle swarm optimization are utilized to transform the system uncertainty problem into a deterministic problem. Finally, the single-objective optimization results without uncertainty and the comprehensive objective optimization results with uncertainty are solved respectively. It is shown that (1) hybrid energy storage devices can effectively improve the consumption level of renewable energy and realize the multi-stage energy conversion. (2) the uncertainty of renewable energy increases the comprehensive cost of a multi-energy system. (3) the improved risk tolerance of system can improve scheduling results.

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马艳霞,周静涵,董晓晶,等.计及不确定性和混合储能设备的综合能源系统多目标优化调度模型[J].电力科学与技术学报,2022,37(3):19-32.
MA Yanxia, ZHOU Jinghan, DONG Xiaojing, et al. Multi-objective optimal scheduling model for multi-energy system considering uncertainty and hybrid energy storage devices[J]. Journal of Electric Power Science and Technology,2022,37(3):19-32.

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