An Improved Dynamic Robust Optimization Algorithm and Its Application in Optimal Scheduling of Integrated Energy System Considering Carbon Emission Reduction

Abstract

Under the background of low-carbon and efficient development of energy system, renewable energy will be vigorously developed and gradually become the main force of energy system. However, renewable energy has great uncertainty and randomness due to its own formation characteristics. In order to solve this problem and reduce the carbon emission of regional integrated energy system (RIES), this paper first introduces the optimal structure of RIES considering shared energy storage system (SESS) and power-to-gas (P2G). Secondly, a ladder type reward-punishment carbon trading mechanism model is proposed, which considers the reward and punishment interval of carbon emissions. At the meantime, an improved robust optimization over time (ROOT) method based on index contribution degree is proposed for dynamic problem considering uncertainty, based on the effect of each solution operator in the robust solution calculation process. Finally, a scheduling model with the lowest daily operation cost is established, and the effectiveness of the proposed low-carbon operation method is verified by comparison. Experimental results show that under the same dynamic test environment, the calculation accuracy of the improved ROOT method based on the contribution degree is increased by 3.56% on average, the calculation time is shortened by 2.93% on average. Meanwhile, the carbon emission can be reduced by 8.13% by adopting the carbon emission reduction measures, which ensures the system under low-carbon conditions.

Keywords

• Dynamic robust optimization
• integrated energy system
• electrical energy storage
• renewable energy source
• uncertainty