The energy crisis poses a significant challenge to modern society, exacerbated by the increasing deployment of renewable energy sources (RES) like wind turbines (WT), photovoltaics (PV), and combined cooling, heat, and power (CCHP) systems. Also, the optimal operation of integrated energy systems (IES) in the presence of energy storage systems (ESS) is imperative. This study proposes optimized energy dispatching for IES incorporating CCHP and RES, i.e., WT and PV, alongside ESS, including electrical energy storage (EES), thermal energy storage (TES), and plug-in hybrid electric vehicles (PHEVs). As natural gas is the primary fuel for CHP units, proper modeling of the natural gas network is necessary, considering its constraints for optimal gas flow. This paper uses the gas shift factor (GSF) matrix in a linear equation to obtain efficient gas flow in pipelines. This linear equation utilizing the GSF matrix facilitates efficient gas flow computation, reducing computational complexity. The study illustrates the economic benefits of modeling the natural gas network in cost reduction. Additionally, it investigates the impact of ESS on energy management within the IES, demonstrating how EES and TES enhance flexibility in meeting electric, heating, and cooling demands, particularly during peak hours, thus reducing operational costs. PHEVs further contribute to electric load supply when not used for daily trips. The objective function minimizes the total operating costs of the proposed IES, which is formulated as a mixed-integer linear programming (MILP) model implemented in the general algebraic modeling system (GAMS) and solved using the CPLEX solver. Simulation results substantiate the effectiveness of the proposed IES in achieving optimal system performance, highlighting its potential in addressing contemporary energy challenges. The simulation results indicate that by modeling the natural gas network and incorporating TES, the total operating cost decreases from $384,098 to $378,430.
