The stochastic economic model for integrated energy system with carbon mechanism

Abstract

As energy conversion technology progresses and evolves, interconnected energy networks with diverse attributes have emerged. The traditional model of energy networks has changed from isolated operation to the combined optimization and scheduling of integrated energy system. To efficiently decrease carbon dioxide emissions, it is necessary to vigorously develop green energy and fully consider carbon emission factors. To tackle the aforementioned issue, this paper proposes a stochastic optimal economic model within the carbon mechanism for integrated energy system. The model incorporates carbon trading, the volatility of renewable energy, and the deviation of real-time electricity prices into the objective function. By applying convex and robust optimization approaches, the primary problem is divided into the master problem and subproblem characterized by mixed-integer linearity, subsequently addressed iteratively. Convex optimization is mainly used to transform the deviation term of electricity price, and robust optimization is employed to find out the economically optimal scheme based on the worst scenario. Simulation results indicate that as the uncertainty in electricity market prices decreases, the electricity market cost can be reduced by up to 22.28 %, while the total cost of the integrated energy system can be reduced by up to 8.56 %. Finally, in the context of the carbon mechanism, the proposed stochastic optimization model was validated through simulations.