Shared Energy Storage Planning for Integrated Energy Systems Based on Distributionally Robust Optimization

ZHAO Zhenyu, LIN Shan, MA Qianxin

Electric Power Construction ›› 2025, Vol. 46 ›› Issue (11) : 58-70.

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Electric Power Construction ›› 2025, Vol. 46 ›› Issue (11) : 58-70. DOI: 10.12204/j.issn.1000-7229.2025.11.006
Planning & Construction

Shared Energy Storage Planning for Integrated Energy Systems Based on Distributionally Robust Optimization

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Abstract

[Objective] To enhance energy utilization efficiency and develop demand-side resources, a shared energy storage (SES) planning framework is constructed for integrated energy system (IES) clusters by taking advantage of the cost- and energy-sharing features of shared energy storage.[Methods] First, considering multiple demands, a joint operation mode of IES clusters with shared energy storage is proposed and a planning model is established. Second, to address the uncertainty of the source load within the IES, a two-stage data-driven distributionally robust optimization model is proposed. The primary goal of the first stage is to minimize the upfront investment required for shared energy storage systems, whereas the second stage, under the scenario of user demand response, aims to minimize the costs of demand response, environment, and operations. The uncertainty is characterized by a comprehensive norm constraint, and the column-and-constraint generation (C&CG) algorithm was employed to solve the model.[Results] A typical load-, energy-, and balanced-type IES was used for the case study. The experimental results show that compared to the scenario that does consider the electricity demand response, the investment capacity and rated power of the SES were reduced by 54.00%, carbon emissions by 11.13%, and the investment and operation costs by 54.00% and 41.16%, respectively.[Conclusions] The demand response mechanism not only significantly improves the flexibility of the system and effectively reduces the investment cost of SES but also further reduces the operation cost by optimizing the grid interaction strategy, which can reduce system carbon emissions, achieving a win-win situation of economic and environmental benefits. The proposed method considers the energy storage demands of each IES within the system and significantly reduces the system investment cost, establishing a distributionally robust economical model with excellent planning and operation.

Key words

shared energy storage (SES) / demand response / integrated energy system (IES) / two-stage distributionally robust optimization

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ZHAO Zhenyu , LIN Shan , MA Qianxin. Shared Energy Storage Planning for Integrated Energy Systems Based on Distributionally Robust Optimization[J]. Electric Power Construction. 2025, 46(11): 58-70 https://doi.org/10.12204/j.issn.1000-7229.2025.11.006

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Abstract
目的 为促进储能和用户侧资源高效利用,提高清洁能源消纳水平,提出了一种考虑云储能的多区互联综合能源系统规划模型。 方法 在建立区域综合能源系统能源枢纽的基础上,提出了考虑电/热/气云储能的能源枢纽模型。针对云储能与综合能源系统分属不同投资主体的问题,考虑云储能投资回报年限约束,提出了双主体两阶段规划模型:第一阶段对网架、设备容量以及云储能使用价格进行规划;第二阶段对综合能源系统的运行策略进行优化。针对多能流网架规划复杂度高的问题,提出了基于最小生成树的预筛选算法。 结果 对某三园区综合能源系统规划的算例分析结果表明,所提模型有助于提高能效、降低碳排、提高互连综合能源系统的经济效益。 结论 研究成果揭示了云储能与多区域综合能源系统协同规划的潜力,并为多类型储能在能源领域的深度应用和商业推广提供参考。
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Objectives In order to promote the efficient utilization of energy storage and user-side resources and improve the level of clean energy consumption, a multi-area interconnected integrated energy system planning model considering cloud energy storage was proposed. Methods On the basis of establishing the energy router model of the regional integrated energy system, a virtual energy router model considering electricity/heat/gas cloud energy storage was proposed. Aiming at the problem that cloud energy storage and integrated energy system belong to different investment entities, considering the limitation of the investment return period of cloud energy storage, a dual-subject two-stage planning model was proposed. In the first stage, the grid, equipment capacity and cloud energy storage price were planned. In the second stage, the operation strategy of the integrated energy system was optimized. Aiming at the high complexity of multi-energy flow grid planning, a pre-screening algorithm based on minimum spanning tree was proposed. Results The example analysis results of a three-park integrated energy system planning show that the proposed model is helpful to improve energy efficiency, reduce carbon emissions, and improve the economic benefits of interconnected integrated energy systems. Conclusions The research reveals the potential of collaborative planning between cloud energy storage and multi-area integrated energy systems, and provides reference for the in-depth application and commercial promotion of multi-type energy storage in the energy field.

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Abstract
为有效应对可再生能源出力波动,实现综合能源系统低碳、经济、鲁棒三者平衡,提出考虑碳交易的电-热综合能源系统两阶段鲁棒优化低碳经济调度模型。首先,构建了配置碳捕获设备的综合能源系统模型。其次,采用可调不确定集合描述风电和光伏的出力波动,并以最恶劣情景下成本最小为优化目标,建立了两阶段鲁棒优化调度模型,然后利用列与约束生成算法迭代求解。最后,在调度模型中计及碳交易成本,来限制系统的电能交易以减少间接碳排放,并避免了调度方案的过度保守。结果表明,两阶段鲁棒优化有效提高了系统抵御风险的能力,减少了经济损失;碳交易机制的引入避免了系统过度鲁棒,能够维持低碳运行,实现了系统低碳、经济、鲁棒三者平衡。
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This study aims to handle fluctuations in renewable energy effectively and achieve low-carbon, economic, and robust balance optimization in an integrated energy system. A two-stage robust optimization low-carbon economic dispatch model for a park-level integrated energy system that considers carbon trade was proposed. First, an integrated energy system model with carbon capture and storage was constructed. Next, the adjustable uncertainty set was used to describe the fluctuations of wind and photovoltaic output, and a two-stage robust optimization dispatch model was developed with the optimal objective of solving the minimum cost under the worst-case scenario. Subsequently, the column-and-constraint generation algorithm was employed to iteratively solve. Finally, the carbon trading cost was considered in the dispatch model, which limited electricity purchases in the system to reduce indirect carbon emissions and avoid overconservative dispatching schemes. The results show that the two-stage robust optimization method can effectively improve the ability of the system to resist risks and reduce economic loss, and the introduction of a carbon trading mechanism can prevent excessive robustness and maintain low-carbon operation. The proposed method can effectively achieve robust, economical, and low-carbon-balance optimal scheduling for the system.
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Abstract
能源互联网的快速发展使得传统的能源系统向多种能源高度耦合的综合能源系统转型, 综合能源系统有助于促进可再生能源消纳、提高能源利用效率、缓解环境污染. 能量枢纽作为综合能源系统规划和运行的重要建模工具与分析框架,自提出以来一直受到广泛的研究和关注. 针对以风能和光热为代表的可再生能源渗透综合能源系统, 本文构建由风力发电机组、热电联产设备、电转气设备和光热电站组成的能量枢纽结构, 提出源荷不确定性环境下基于分布鲁棒优化的能量枢纽两阶段负荷优化调度模型. 该模型考虑风电、光热、电负荷和热负荷的不确定性, 建立基于Wasserstein距离的不确定性分布模糊集. 模型分为日前和实时两个调度阶段, 第一阶段基于日前预测数据进行日前调度,第二阶段为抑制预测误差的影响对灵活设备进行实时调度, 以期获得最恶劣不确定性分布下的最小实时调度成本. 模型采用仿射策略实现设备出力调整, 通过强对偶理论转换为混合整数线性规划问题并求解. 仿真结果表明, 多能耦合设备可以提升系统灵活性并促进可再生能源消纳, 同时所提分布鲁棒优化算法能在系统经济性和鲁棒性中取得平衡.
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Abstract
在新型电力系统建设下,电-热-氢多能源互联互通的综合能源系统将成为重要发展方向之一,但其全寿命周期运营经济性和能源供应可靠性受系统初始设备容量和日运行方案影响.因此,提出一种考虑源-荷不确定性的多目标两阶段鲁棒优化研究方法.建立了包含燃料电池、电解槽等装置的电-热-氢并网运行模型,采用分层拉丁超立方体抽样和Euclidean距离的场景削减方法增添源-荷不确定性因素,并采用两阶段鲁棒优化算法进行求解.算例对比分析了4类系统规定运行条件下设备投资等年值成本和典型日运行成本,验证所提方法可有效缓解源-荷不确定性对综合能源系统配置和运行规划的影响,研究成果有望为未来综合能源系统建设和运营提供新的思路.
LI Jianlin, ZHANG Zedong, LIANG Ce, et al. Multi-objective robustness of integrated energy system considering source-load uncertainty[J]. Journal of Shanghai Jiao Tong University, 2025, 59(2): 175-185.
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ZHENG Shicheng, XU Hao, LANG Jiahong, et al. Multi-scenario distributed robust optimal scheduling of multi-area integrated energy systems considering photovoltaic uncertainty[J]. Acta Energiae Solaris Sinica, 2024, 45(3): 460-469.
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Natural Science Foundation of Beijing(8232013)
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