Benefit allocation for distributed energy network participants applying game theory based solutions

Abstract

This study develops a mixed-integer linear programming (MILP) model integrating energy system optimization and benefit allocation scheme of the building distributed heating network. Based on the proposed model, the minimized annual total cost, energy generators configuration, optimal operation strategy and heating pipeline lay-out of the distributed energy network can be determined. Moreover, four benefit allocation schemes (Shapely, the Nucleolus, DP equivalent method, Nash-Harsanyi) based on cooperative game theory are employed to deal with the benefit (reduced annual cost) assignment among the building clusters, while considering the stability and fairness of each scheme. As a case study, a local area including three buildings located in Shanghai, China is selected for analysis. The simulation results indicate that the ground coalition in which all buildings cooperate with each other by sharing and interchanging the thermal energy yields the best economic performance for the distributed energy network as a whole. In addition, different allocation schemes may result in diversified outcomes in terms of the fairness and stability, which are measured by the Shapley-Shubik Power Index and the Propensity to Disrupt value, respectively. For the current case study, the Shapely value method is recognized to be the most acceptable allocation scheme from both viewpoints.