Coordinated optimization strategy of low-carbon complementary energy system considering electric vehicles response

Integrated Energy System (IES) serves as one of the core carriers for low-carbon transformation. However, it confronts three challenges: poor load management causing large demand fluctuations, inefficient multi-energy coordination limiting flexible resource utilization and uniform carbon pricing lacking mechanisms to differentially incentivize emission reductions across diverse stakeholders. To address these issues, this paper proposes a coordinated optimization strategy for multi-energy complementary IES that integrates electric vehicles (EVs) cluster response with a stepped reward-punishment carbon trading mechanism, aiming to achieve multi-objective collaborative optimization of "economy, low-carbon and stability". First, predictive average voting (PMV) metrics are used to obtain load demands that take into account user comfort feedback. This approach improves the flexibility of the integrated system. Then, an intelligent agent-based EVs cluster scheduling strategy is proposed. The purpose is to solve the problem of poor adjustability of power load and improve the stability of the system. Finally, a step-by-step reward and punishment carbon trading mechanism is established that takes into account the quota of EVs. This mechanism optimizes the carbon emission structure of each unit, reduces carbon emissions, and increases carbon trading income. The case study showed that the proposed strategy can effectively achieve peak clipping and valley filling, reduce IES carbon emissions and total operating costs, and prove its effectiveness in improving IES performance.