The comprehensive utilization of multi-energy resources has been recognized as an effective way to improve the energy utilization efficiency. This paper proposes a distributed double-side multi-energy coordination framework to minimize the total system cost by optimizing the energy supply of energy hubs (EHs) and the energy consumption of consumers, considering the tradeoff between the fuel cost of EHs and the satisfaction of consumers. In this framework, EHs and consumers are modeled through a standardized matrix modeling method by applying which arbitrary combinations of energy forms could be handled, i.e., EHs could include more forms of coupled energy rather than two or three specific forms and consumers have both time-shifting and energy-shifting loads. Hence, consumers implement the integrated demand response (IDR) such that the energy demand can be shifted among different time intervals and different energy forms, e.g., from the electricity to the gas, to achieve individual benefits. Moreover, suppose that EHs and consumers communicate via a time-varying network and only exchange information with their neighbors. Under such topology, we develop a fully distributed sub-gradient averaging consensus algorithm with the energy supply-demand balance guaranteed at each time interval. The convergence and optimality of the proposed algorithm are verified theoretically, and the numerical simulation is presented to illustrate the developed results.

中文翻译：

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基于次梯度平均共识的双面多能源系统分布式能源管理


多种能源的综合利用已被公认为提高能源利用效率的有效途径。本文提出了一种分布式双边多能源协调框架，通过优化能源中心（EH）的能源供应和消费者的能源消耗，考虑EH的燃料成本和消费者满意度之间的权衡，最小化系统总成本。消费者。在此框架中，EH和消费者通过标准化矩阵建模方法进行建模，通过应用该方法可以处理能量形式的任意组合，即EH可以包括更多形式的耦合能量而不是两种或三种特定形式，并且消费者具有时间-转移和能量转移负载。因此，消费者实施综合需求响应（IDR），使得能源需求可以在不同时间间隔和不同能源形式之间转移，例如从电力到天然气，以实现个人利益。此外，假设 EH 和消费者通过时变网络进行通信，并且仅与邻居交换信息。在这种拓扑下，我们开发了一种完全分布式的次梯度平均共识算法，保证每个时间间隔的能源供需平衡。从理论上验证了所提出算法的收敛性和最优性，并通过数值模拟来说明所开发的结果。