Two-stage service restoration of integrated electric and heating system with the support of mobile heat sources

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy Pub Date : 2024-11-19 DOI:10.1016/j.apenergy.2024.124899

Han Shi , Yunyun Xie , Kai Hou , Sheng Cai , Hongjie Jia , Hao Wu , Jinsheng Sun

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引用次数: 0

Abstract

Mobile heat sources (MHSs), including truck-mounted mobile electric boilers (MEBs) and mobile thermal energy storages (MTESs), are critical flexibility resources. However, these MHSs are currently under-utilized for multi-energy service restoration (SR) against natural disasters. To improve the flexibility and efficiency of service restoration (SR) strategies, this paper proposes an MHS-assisted SR method for distribution-level integrated electric and heating system (IEHS). The constraints for MHSs scheduling, involving energy conversion and spatial-temporal energy transfer, are modelled based on the interactive behavior between MHSs and IEHS. Considering the slow response speed of MHSs, a two-stage model is formulated, consisting of pre-SR and real-time SR stages. In the pre-SR stage, the locations of MHSs and absorbing/releasing behaviors of MTES are determined. In the real-time SR stage, multi-energy resources are re-dispatched to compensate the pre-SR strategies after the uncertainties realized. To address diverse uncertainties in the pre-SR stage, the stochastic programming (SP) is utilized, and an improved progressive hedging algorithm (PHA) is applied to reduce the computational burden caused by multiple scenarios in SP. Numerical results validate the effectiveness of MHSs in improving the flexibility of SR strategy and enhancing IEHS resilience.

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在移动热源的支持下，对集成电力和供暖系统进行两阶段服务恢复

移动热源（MHS），包括车载移动电锅炉（MEB）和移动热能储存器（MTES），是重要的灵活性资源。然而，这些移动热源目前在应对自然灾害的多能源服务恢复（SR）方面利用不足。为了提高服务恢复（SR）策略的灵活性和效率，本文针对配电级综合电力和供热系统（IEHS）提出了一种 MHS 辅助 SR 方法。基于 MHS 与 IEHS 之间的交互行为，模拟了 MHS 调度的约束条件，其中涉及能量转换和时空能量传递。考虑到 MHS 的响应速度较慢，因此建立了一个两阶段模型，包括预 SR 阶段和实时 SR 阶段。在预 SR 阶段，将确定 MHS 的位置和 MTES 的吸收/释放行为。在实时 SR 阶段，在不确定性实现后，重新分配多能源资源以补偿预 SR 策略。为解决预 SR 阶段的各种不确定性，利用了随机编程（SP），并采用了改进的渐进对冲算法（PHA），以减少 SP 中多种情景造成的计算负担。数值结果验证了 MHS 在提高 SR 策略灵活性和增强 IEHS 恢复能力方面的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Energy 工程技术-工程：化工

CiteScore

21.20

自引率

10.70%

发文量

1830

审稿时长

41 days

期刊介绍： Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.