Optimal scheduling of an integrated energy system considering carbon trading mechanism and multi-energy supply uncertainties in a real-time price environment

Abstract

This research presents an optimized scheduling model for Integrated Energy Systems (IES) that harmonizes economic efficiency with low carbon emissions in a Real-Time Price (RTP) environment. Integrating a ladder-type carbon tax approach, this model adeptly addresses the unpredictability of renewable energy generation and IES load demands. It introduces a carbon trading mechanism for efficient emission control, complemented by an RTP model that manages interactions between the IES and the main power grid through piecewise linear functions. The model also proposes an adaptable operation strategy for thermoelectric and electric cooling ratios, enhancing the IES’s economic and operational flexibility. The objective function, crafted on a deviation preference optimization basis, reflects the diverse goals of decision-makers, and the model is skillfully translated into a mixed-integer linear programming format through a series of mathematical transformations. Simulation results demonstrate the model’s efficacy in achieving an optimal balance between cost-effectiveness and reliability, particularly by setting a strategic confidence level for spinning reserves. Additionally, incorporating a ladder-type carbon tax and Electric Vehicle (EV) charging within the IES underscores its significant environmental benefits, marking a stride towards a low-carbon future.