Day-Ahead Scheduling of Integrated Energy Systems Considering Carbon Emissions

Abstract

The forecast-based day-ahead scheduling can effectively reduce the integrated energy systems (IES) operating cost. In this paper, a day-ahead IES scheduling problem considering carbon emissions is studied. Firstly, an IES system model is established, and the optimization objectives of operating cost and carbon emissions, energy balance equations and constraints are established according to the model. A day-ahead scheduling operating cost considering the existence of prediction errors is established. Then, based on the proposed model, the dayahead scheduling problem of IES considering carbon emissions is formulated as a multi-objective optimization. The problem can be readily solved by the non-dominated sorting genetic algorithm-II (NSGA-II). Finally, some simulations are carried out, and the results show that the effectiveness of the proposed day-ahead scheduling strategy, reducing the operating cost by 45.82%.