Optimal Scheduling of an Integrated Energy System Considering Carbon Trading Mechanism and Multi-Energy Supply Uncertainties in a Real-Time Price Environment

To further constrain the carbon emission of the integrated energy system (IES) and reduce the comprehensive cost, an optimal scheduling model to balance economy and low carbon in a real-time price (RTP) environment was proposed. In this model, a low carbon operation strategy considering a reward and punishment ladder-type carbon tax, uncertain renewable power generation and uncertain load for the IES was proposed. First, a ladder-type carbon trading mechanism was introduced to participate in the carbon market to control carbon emissions, a RTP model with piecewise linear functions between this constructed IES and the main grid was considered, and then, the operation strategy of adjustable thermoelectric and electric cooling ratio was proposed to achieve flexibility and economy of IES operation. Next, the objective function was constructed using the deviation preference optimization strategy to reflect the different optimization preferences of the decision-makers, and the original model was converted into a mixed-integer linear programming by a series of mathematical processing and transformations. Finally, the simulation shows that the IES operation effectively balances economy and reliability by setting an appropriate confidence level for the spinning reserve, a ladder-type carbon tax and EV charging in IES has a considerable environmental and low-carbon advantages