Distributed Energy Management of Double-Side Multienergy Systems via Sub-Gradient Averaging Consensus

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.