中国电力 ›› 2024, Vol. 57 ›› Issue (2): 171-182.DOI: 10.11930/j.issn.1004-9649.202212079

• 新能源 • 上一篇    下一篇

基于NNC法和DMC算法的CCHP型微电网两阶段调度

陈苏豪1(), 吴越2, 曾伟3, 杨晓辉1(), 王晓鹏1, 伍云飞1   

  1. 1. 南昌大学 信息工程学院,江西 南昌 330031
    2. 国网江西省电力有限公司,江西 南昌 330066
    3. 国网江西省电力有限公司电力科学研究院,江西 南昌 330096
  • 收稿日期:2022-12-15 出版日期:2024-02-28 发布日期:2024-02-28
  • 作者简介:陈苏豪(1995—),男,硕士研究生,从事分布式能源、综合能源系统规划研究,E-mail:2048676779@qq.com
    杨晓辉(1978—),男,通信作者,博士,教授,从事分布式能源、配电网优化控制研究,E-mail:yangxiaohui@ncu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(基于迁移学习的PHM预测模型的建模理论与方法,61963026)。

Two-Stage Dispatch of CCHP Microgrid Based on NNC and DMC

Suhao CHEN1(), Yue WU2, Wei ZENG3, Xiaohui YANG1(), Xiaopeng WANG1, Yunfei WU1   

  1. 1. School of Information Engineering, Nanchang University, Nanchang 330031, China
    2. State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330066, China
    3. Electric Power Research Institute of State Grid Jiangxi Electric Power Co., Ltd., Nanchang 330096, China
  • Received:2022-12-15 Online:2024-02-28 Published:2024-02-28
  • Supported by:
    This work is supported by National Natural Science Foundation of China (Modeling Theory and Method of PHM Predictive Model Based on Transfer Learning, No.61963026).

摘要:

冷热电联产(combined cooling, heating and power,CCHP)系统与微电网的结合有利于促进消纳可再生能源,为了提升CCHP型微电网的经济性、环保性和稳定性,提出了两阶段优化调度模型。离线优化阶段基于需求侧响应策略,建立了基于归一化法向约束法的多目标规划模型,并用熵权-TOPSIS法筛选最优结果。在线优化阶段建立了基于动态矩阵控制算法的有限时域优化模型,对离线优化结果进行跟踪优化和反馈校正,以降低不确定性因素的影响。最后,设计对比方案进行分析,验证了所提优化模型的有效性。

关键词: 冷热电联供型微电网, 两阶段优化调度, 多目标规划, 归一化法向约束法, 动态矩阵控制算法

Abstract:

The combination of combined cooling, heating and power (CCHP) and microgrid promotes the consumption of renewable energy. In order to improve the economy, environmental protection and stability of CCHP microgrid, a two-stage optimal dispatching model is proposed. The offline optimization stage is based on the demand response strategy, and the multi-objective model based on the normalized normal constraint method is established, and the optimal results are screened by the entropy-TOPSIS method. In the online optimization stage, a finite-time domain optimization model based on dynamic matrix control algorithm is established to track and optimize the offline optimization results with feedback correction to reduce the influence of uncertainty factors. Finally, a comparison scheme is designed to for analysis verify the effectiveness of the proposed optimization model.

Key words: CCHP microgrid, two-stage optimized scheduling, multi-objective optimization, normalized normal constraint method, dynamic matrix control algorithm