计及混合潮流约束的热-电互联综合能源系统多目标优化调度
作者:
作者单位:

1.东北大学;2.东北大学秦皇岛分校

作者简介:

通讯作者:

中图分类号:

TM721

基金项目:

国家自然科学基金(U1908213),中央高校基本科研业务费(N182303037),河北省高等学校科学研究项目(QN2020504),东北大学秦皇岛分校校内基金 (XNB201803)


Multi-objective optimization scheduling for integrated electricity and heating system including hybrid power flow constraints
Author:
Affiliation:

1.Northeastern University;2.Northeastern University at Qinhuangdao

Fund Project:

National Natural Science Foundation of China (U1908213), Fundamental Research Funds for the Central Universities (N182303037), Colleges and Universities in Hebei Province Science Research Program (QN2020504), Foundation of Northeastern University at Qinhuangdao (XNB201803).

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    摘要:

    为满足多样化能源需求并提高能源网络的可靠性,研究多能源系统优化管理和混合潮流问题.针对多能源的网络约束及其耦合特性,构建了整合分布式发电、热电联产、电力网络和区域供热网络的热-电互联综合能源系统模型.基于梯形模糊隶属函数构建模糊化软约束,量化了电力网络节点电压和区域供热网络节点供给温度的技术不满意度.考虑系统的经济运行和网络节点的能源供给质量,提出了一种计及混合潮流约束的热-电互联综合能源系统多目标优化调度策略以最小化运行成本和网络节点状态变量的技术不满意度.采用epsilon约束算法精确求解该多目标优化问题的Pareto前沿.算例分析结果表明,构建的模型和提出的算法可以有效提高系统能源供给质量和优化决策的准确性.研究成果进一步体现了提出的多目标优化方案在兼顾经济性,能源供给质量以及复杂的运行约束,保证系统经济稳定运行等方面的效益.

    Abstract:

    The problems of multi-energy optimal management and hybrid power flow are investigated to improve the reliability of the energy network. Given multi-energy network constraints and their coupling characteristics, an integrated electricity and heating system is established to integrate multi-energy networks. The fuzzy soft constraint is constructed to quantify the technical dissatisfaction of the networks. A multi-objective optimization scheduling strategy is proposed to minimize the operation cost and technical dissatisfaction of the system with hybrid power flow constraints. An epsilon constraint algorithm is adopted to obtain the Pareto front of the proposed multi-objective optimization problem. Results from the case study indicate that the proposed model and algorithm can effectively improve the quality of energy supply and the accuracy of optimal decisions. It further reflects the benefits of the proposed scheme in the aspects of the economy, quality, and complex constraints, as well as ensuring the economical and stable operation of the system.

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历史
  • 收稿日期:2020-07-07
  • 最后修改日期:2021-09-30
  • 录用日期:2020-09-15
  • 在线发布日期: 2020-10-02
  • 出版日期: