A two-stage distributionally robust optimization model for P2G-CCHP microgrid considering uncertainty and carbon emission

The utilization of energy efficient combined cooling heat and power (CCHP) microgrid systems provide an opportunity for us to considering both the increase of economic benefits and environmental costs, simultaneously. The goal of this paper is to propose a P2G-CCHP microgrid system integration framework, connect power to gas (P2G) devices to CCHP microgrid, and provide a two-stage distributionally robust optimization (DRO) model to solve the problem of economic dispatch. DRO model uses the Wasserstein metric to extract the ambiguity set of the probability distribution information of the wind power and photovoltaic output uncertainty. And environmental cost is also considered in the optimal operation of the system. In addition, based on the strong duality theory, the DRO model is transformed into an easy-to-solve MILP problem. The simulation results show that: 1) The introduction of a P2G device can effectively improve the electrical-gas coupling of the P2G-CCHP microgrid system, and improve the stability and economy of the system operation. 2) Considering environmental cost, the pollutant emission of the P2G-CCHP microgrid system is significantly reduced, which ensures the low-carbon operation of system. 3) The DRO model can resist the interference of uncertain wind power and PV output with relatively low conservatism and computational complexity and has the characteristics of data-driven. • A P2G-CCHP microgrid system integration framework is proposed. • A two stage distributionally robust optimization (DRO) model is proposed. • Wasserstein metric is used to extract the ambiguity set of renewable energy output. • The environmental cost is also considered in the optimal operation of the system.