An integrated two-level demand-side management game applied to smart energy hubs with storage

Energy hubs, an important component of future energy networks employing distributed demand-side management, can play a key role in enhancing the efficiency and reliability of power grids. In power grids, energy hub operators need to optimally schedule the consumption, conversion, and storage of available resources based on their own utility functions. In sufficiently large networks, scheduling an individual hub can affect the utility of the other energy hubs. In this paper, the interaction between energy hubs is modeled as a congestion game. Each energy hub operator (player) participates in a dynamic energy pricing market and tries to maximize his/her own payoff when satisfying energy demand. We propose a distributed algorithm based on a congestion game, which guarantees the existence of a Nash equilibrium. Furthermore, two different types of signaling are developed (price-based, load-based) and simulation results compared. Simulation results show that with the implementation of either setup the peak-to-average ratio between electricity networks and natural gas networks diminishes. An analysis of the results shows that either setup can dominate the other one with regard to generation costs, convergence rate, price level, and stability. Hence, energy providers and consumers can choose a favorable setup based on their respective needs. (C) 2020 Elsevier Ltd. All rights reserved.