基于Benders分解和纳什议价的分布式热电联合优化调度

doi:10.19595/j.cnki.1000-6753.tces.221155

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摘要

考虑供热管网储能特性的热电联合优化调度可以有效地提高电力系统的灵活性,促进可再生能源高比例消纳。电力系统和热力系统隶属于不同的运营主体,热电联合优化调度在最大化总体效用时,不应损害个体利益。该文提出一种基于Benders分解和纳什议价的电-热综合能源系统分布式优化调度方法。首先,热力系统与电力系统依次计算最优热流和最优功率分配,分别得到各自独立调度的运行总成本;然后,利用Benders分解计算电-热综合能源系统最优能流,相应得出电-热综合能源系统运行总成本;最后,通过纳什议价重新分配两者的合作剩余以鼓励热力系统参与热电联合优化调度。两个不同规模算例的仿真结果表明,所提方法能在保护信息隐私的前提下,实现激励相容并促进可再生能源消纳。

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关键词 ：管道储能, 热电联合调度, Benders分解, 纳什议价, 激励相容

Abstract：

Combined heat and power dispatch considering pipeline energy storage of district heating networks can improve the flexibility of electric power systems (EPSs) and promote a high proportion of renewable energy consumption. EPSs and district heating systems (DHSs) are operated by different entities. However, combined heat and power dispatch may deviate from the optimal scheduling strategy of DHSs. In other words, combined heat and power dispatch can harm individual interests when maximizing overall utility. Recently, some methods for combined heat and power optimal scheduling have been proposed, but most do not consider both privacy protection and incentive compatibility. To address these issues, the paper proposes a distributed optimal scheduling method for integrated electricity and heat systems (IEHSs) based on Benders decomposition and Nash bargaining.
First, DHSs and EPSs calculate optimal heat flow and power dispatch to obtain the respective total operating cost. Next, Benders decomposition is employed to calculate the optimal energy flow of IEHSs, and the total operating cost of IEHSs is derived accordingly. In addition, this paper strictly proves that combined heat and power optimal scheduling reduces the total operating cost of EPSs while increasing the total operating cost of DHSs. Finally, the cooperative surplus is redistributed through Nash bargaining to encourage DHSs to participate in cooperation, which decreases the total cost of EPSs and DHSs. The proposed method can achieve incentive compatibility and promote renewable energy accommodation while protecting information privacy.
The simulation results of the small-scale system show that combined heat and power dispatch considering pipeline energy storage reduces wind curtailment by 223.15 MW and increases the heat output of combined heat and power (CHP) units by 26.43 WM. The centralized scheduling of IEHSs requires disclosure of all information privacy, such as topology structure, operating status, and network parameters. In contrast, EPNs and DHSs only need to communicate with 115 feasibility or optimality cut plants in a distributed way based on Benders decomposition. The total cost of EPNs in the combined heat and power optimal scheduling is decreased by \$10 809 compared to the separate dispatch, but the total cost of DHSs is raised by \$787. As a result, DHSs have no incentive to cooperate with EPNs. To promote cooperation, EPNs and DHSs redistribute cooperative surplus through Nash bargaining. The overall cost of EPNs is lowered by \$5 011 compared to separate dispatch, and the total cost of DHNs is decreased by \$5 011 compared to separate dispatch. According to the simulation results for the large-scale system, EPNs and DHSs only need to interact with 2 765 feasibility or optimality cut plants instead of disclosing 10 440 constraints. The overall cost of EPNs and DHNs are both decreased by \$41 865 by sharing the cooperative surplus through Nash bargaining.
The following conclusions can be drawn from the simulation analysis: (1) Combined heat and power dispatch considering pipeline energy storage can improve the flexibility of EPSs and reduce wind curtailment. (2) Compared with centralized scheduling, the distributed optimal dispatch for IEHSs based on Benders decomposition can fully protect the information privacy between EPSs and DHSs. (3) The proposed IEHS decentralized dispatch method based on Nash bargaining can decrease the total cost of EPSs and DHSs, respectively.

Key words： Pipeline energy storage combined heat and power optimal scheduling Bender decomposition Nash bargaining incentive compatibility

收稿日期: 2022-06-18

PACS:

TM732

基金资助:

国家自然科学基金面上项目（52177087）和新型电力系统运行与控制全国重点实验室开放基金课题（SKLD22KM11）资助

通讯作者: 朱继忠男,1966年生,教授,博士生导师,研究方向为综合智慧能源系统优化运行与控制。E-mail: zhujz@scut.edu.cn

作者简介: 朱浩昊男,1997年生,硕士研究生,研究方向为热电联合调度。E-mail：epzhh@mail.scut.edu.cn

引用本文:

朱浩昊, 朱继忠, 李盛林, 陈梓瑜, 董瀚江. 基于Benders分解和纳什议价的分布式热电联合优化调度[J]. 电工技术学报, 2023, 38(21): 5808-5820. Zhu Haohao, Zhu Jizhong, Li Shenglin, Chen Ziyu, Dong Hanjiang. Distributed Combined Heat and Power Optimal Scheduling Based on Benders Decomposition and Nash Bargaining. Transactions of China Electrotechnical Society, 2023, 38(21): 5808-5820.

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