Since there are heavy interdependencies among the electrical, heat, and gas systems to supply various load types worldwide, operation of multi-energy carrier (MEC) systems faces critical challenges. Moreover, any uncertainty rising in one carrier would directly influence the energy flow and the secure operation of the whole MEC system. This issue intensifies when an MEC system is integrated with industrial energy carrier demand response (ECDR) consumers and renewable energy sources (RESs). Large industrial ECDR consumers can increase the system uncertainty by randomly participating in the demand response programs and utilizing various carriers. Accordingly, this paper presents a powerful probabilistic tool named 2m + 1 point estimate strategy for energy flow analysis of an integrated MEC system considering ECDR, RES, and various load types uncertainties to control the risks associated with the uncertainties. In addition, a new decomposition technique is presented to accelerate the energy flow solving of the integrated MEC systems. This technique has been promoted by adding a novel noniterative method named holomorphic embedding and the less-computational graph methods for solving the energy flow of the MEC. The proposed probabilistic energy flow is tested on an integrated MEC system employing various incentives for industrial ECDR consumers.

中文翻译：

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基于可再生能源的综合电力__as__eat系统能量流的运营商需求响应不确定性研究


由于为全球各种负载类型供电的电力、热力和燃气系统之间存在严重的相互依赖性，因此多能源载体（MEC）系统的运行面临着严峻的挑战。而且，某一载体的任何不确定性都会直接影响整个MEC系统的能量流动和安全运行。当 MEC 系统与工业能源载体需求响应 (ECDR) 消费者和可再生能源 (RES) 集成时，这个问题会加剧。大型工业 ECDR 消费者可以通过随机参与需求响应计划并利用各种运营商来增加系统的不确定性。因此，本文提出了一种强大的概率工具，称为 2m + 1 点估计策略，用于考虑 ECDR、RES 和各种负载类型不确定性的集成 MEC 系统的能量流分析，以控制与不确定性相关的风险。此外，还提出了一种新的分解技术来加速集成MEC系统的能量流求解。通过添加一种名为全纯嵌入的新型非迭代方法和用于求解 MEC 能量流的计算量较少的图方法，该技术得到了推广。所提出的概率能量流在集成 MEC 系统上进行了测试，该系统采用了针对工业 ECDR 消费者的各种激励措施。