储能科学与技术 ›› 2024, Vol. 13 ›› Issue (6): 1888-1899.doi: 10.19799/j.cnki.2095-4239.2023.0958

• 储能系统与工程 • 上一篇    下一篇

基于多场景多重不确定性的含混氢天然气的综合能源系统运行优化

熊阳阳(), 于艾清(), 王育飞, 薛花   

  1. 上海电力大学电气工程学院,上海 200090
  • 收稿日期:2023-12-28 修回日期:2024-01-29 出版日期:2024-06-28 发布日期:2024-06-26
  • 通讯作者: 于艾清 E-mail:young2008cq@126.com;yuaiqing@shiep.edu.cn
  • 作者简介:熊阳阳(1999—),男,硕士研究生,研究方向为综合能源系统优化调度,E-mail:young2008cq@126.com
  • 基金资助:
    上海市自然科学基金(23ZR1425000);上海市科技创新行动计划项目(22010501400)

Optimization of integrated energy system operation containing hydrogen-compressed natural gas based on multiple scenarios and uncertainties

Yangyang XIONG(), Aiqing YU(), Yufei WANG, Hua XUE   

  1. College of Electrical Engineering, Shanghai University of Electric Power, Shanghai 200090, China
  • Received:2023-12-28 Revised:2024-01-29 Online:2024-06-28 Published:2024-06-26
  • Contact: Aiqing YU E-mail:young2008cq@126.com;yuaiqing@shiep.edu.cn

摘要:

合理利用氢能能够提高综合能源系统优化运行的灵活性,有效缓解源荷不确定性对系统运行的影响。将氢气混入天然气中作为燃料注入热电联产机组可以有效提高系统的经济性以及氢能利用率。为此,提出了基于多场景多重不确定性的含混氢天然气的综合能源系统运行优化模型。首先,建立以混氢天然气为燃料的综合能源系统拓扑。其次,综合考虑源荷不确定性以及场景概率不确定性,建立以系统运行成本最低为目标的三阶段鲁棒优化模型,根据列与约束生成算法拆分为主、子问题,运用数学方法将其变为单层优化进行求解。分析对比不同鲁棒模型的运行结果,表明提出的含混氢天然气的综合能源系统三阶段鲁棒优化模型可以提高系统经济性,有效缓解系统优化时因忽略场景实际发生概率与预测值的偏差而导致结果趋于极端的问题。

关键词: 含混氢天然气综合能源系统, 鲁棒优化模型, 多阶段优化, 多场景

Abstract:

Rational utilization of hydrogen energy can enhance the flexibility of optimizing integrated energy systems and effectively mitigate the impacts of source and load uncertainty on system operations. Employing hydrogen-compressed natural gas (HCNG) as fuel and incorporating it into cogeneration combined heat and power systems can significantly enhance economic efficiency and hydrogen energy utilization. This paper proposes an optimization framework for the operation of integrated energy systems incorporating HCNG, considering multiple scenarios and uncertainties. The approach begins by establishing an integrated energy system topology that utilizes HCNG as fuel. It then addresses the uncertainties of sources, loads, and scenario probabilities through a three-stage robust optimization model aimed at minimizing system operating costs. The main and subproblems are decomposed using the Column and Constraint Generation (C & CG) algorithm. The Karush-Kuhn-Tucker (KKT) conditions and the Big M method are applied to transform these into a single-layer optimization problem. Comparative analysis of system operation results and robust models demonstrates that HCNG can optimize system operations and reduce costs effectively. The proposed model adeptly handles the discrepancies between actual and predicted scenario probabilities, thus preventing extreme outcomes during system optimization.

Key words: integrated energy system containing hydrogen compressed natural gas, robust optimization model, multi stage optimization, multi scenario

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