计及新能源机会约束与虚拟储能的电-热系统分布式多目标优化调度

doi:10.19595/j.cnki.1000-6753.tces.230926

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摘要

为提升综合能源系统消纳新能源能力,探究不同优化目标之间的联系,本文将含虚拟储能的电-热系统调度问题分解为备用制定问题与计及机会约束的新能源消纳最优运行问题,构建了兼顾经济性、低碳性与综合能效提升的电-热综合能源系统多目标优化模型。通过引入多场景与场景指示变量近似机会约束,提出一种双线性Benders分布式计算框架以提升求解效率,将原问题分解为主问题和若干子问题迭代求解,采用法线边界交叉法得到Pareto前沿面。算例分析表明,所提算法相较于集中式算法的求解速度有明显提升,考虑新能源消纳机会约束的模型可在调度中通过调整置信度平衡运行的经济性与鲁棒性,同时虚拟储能可以根据新能源处出力情况调节热网充放功率,进一步提升新能源消纳能力,降低运行成本。最后,通过求解得到的Pareto前沿面分析了经济、低碳、能效不同优化目标之间的影响。

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关键词 ：综合能源系统, 机会约束, 虚拟储能, 双线性Benders分解法, 多目标优化

Abstract：

In order to improve the integrated energy system's ability to absorb new energy and explore the relationship between different optimization objectives. In this paper, the scheduling problem of the integrated electric-heat system with virtual energy storage is decomposed into the standby formulation problem and the new energy consumption optimal operation problem considering the opportunity constraints, and a multi-objective optimization model of the integrated electric-heat system is constructed, which simultaneously takes into account the economy, low carbon and comprehensive energy efficiency improvement. A bilinear Benders distributed computing framework is proposed to improve the solving efficiency by introducing the approximate chance constraints of multiple scenarios and scenario indicator variables. The original problem is decomposed into the main problem and several sub-problems for iterative solving. The normal boundary crossing method is used to obtain Pareto frontier. Example analysis shows that compared with the centralized algorithm, the solution speed of the proposed algorithm is significantly improved. The model considering the constraints of new energy consumption opportunities can balance the economy and robustness of operation by adjusting the confidence degree during scheduling. Meanwhile, virtual energy storage can adjust the charging and discharging power of the heat supply network according to the output of the new energy department, further improving the absorbing capacity of new energy and reducing the operating cost. Finally, the influence of different optimization goals of economy, low carbon and energy efficiency is analyzed by solving the Pareto frontier.
First, the integrated electric-heat system standby optimal scheduling model based on opportunity constraints is proposed. The model includes the start-stop and climb constraints of generator sets, CHP units and EB units, as well as the charge and discharge constraints of electric energy storage and capacity constraints. At the same time, the virtual energy storage characteristics of heat supply network and its mass flow regulation mode are considered, and new energy opportunity constraints are constructed to cope with system uncertainties, so as to obtain a day-ahead backup plan that can balance conservatism and economy.
Secondly, the problem is divided into the standby formulation problem and the optimal operation problem, in which the chance constraint is transformed into bilinear form by scenarioization. In order to solve the problem that the charge and discharge constraints of electric energy storage cannot generate Benders cuts, the integer cycle comparison strategy in the bilinear Benders method is adopted to achieve the global optimal. At the same time, a parallel framework supporting distributed computing is proposed to improve the solving efficiency.
Finally, from the perspective of the integrated electric-heat system optimal operation, this paper establishes a multi-objective optimization model that takes into account the economy, low carbon and comprehensive energy efficiency improvement of the integrated electric-heat system, and uses the normal boundary crossing method to solve it, and analyzes the restrictive relationship between the three objectives. Finally, a numerical example is given to verify the effectiveness of the proposed method.

Key words： integrated energy system chance constraint virtual storage bilinear Benders decomposition multi-objective optimization

收稿日期: 2023-06-23

PACS:

TM73

基金资助:

国家自然科学基金联合基金重点支持资助项目（U22B2098）

通讯作者: 郭创新男,1969年生,教授,博士生导师,研究方向为能源互联网运行与规划、风险调度。E-mail：guochuangxin@zju.edu.cn

作者简介: 林雨眠男,2000年生,硕士研究生,研究方向为综合能源系统优化调度、规划技术E-mail：yumianlin@zju.edu.cn

引用本文:

林雨眠, 熊厚博, 张笑演, 林雨洁, 郭创新. 计及新能源机会约束与虚拟储能的电-热系统分布式多目标优化调度[J]. 电工技术学报, 0, (): 230926-. Lin Yumian, Xiong Houbo, Zhang Xiaoyan, Lin Yujie, Guo Chuangxin. Distributed Multi-Objective Optimal Scheduling of Integrated Electric-Heat System Considering Chance Constraint of New Energy and Virtual Storage. Transactions of China Electrotechnical Society, 0, (): 230926-.

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