Volume 12: Proceedings Applied Energy Symposium: CUE2020, Part 1, Japan/Virtual, 2020

Game theory-based modeling and optimization for renewable multi-energy system design Zuming Liu, Shukun Wang, Xiaonan Wang


This paper presents a game theory-based modeling framework for government subsidy optimization and renewable multi-energy system (MES) design. The government offers subsidy for renewable technologies, while consumers return rational response to government subsidy on deploying renewable technologies in their respective MES. The game theory-based subsidy optimization and MES design is first formulated as a mixed-integer bilevel nonlinear programming problem and then transformed into a single level mixed-integer linear programing problem using Karush-Kuhn-Tucker conditions and linearization strategies. The results show that the government needs to provide a total subsidy of 3.86 million USD in order to achieve a renewable penetration of 60% in a small urban city composed of four towns. With government subsidy, the total net present costs for the four towns are 8.24, 6.7, 8.32, and 8.93 million USD, respectively.

Keywords Multi-energy system, Renewable energy, Incentive strategy, Game theory, Bilevel optimization

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