Improving the multi-energy synergy flexibility of RIES: slackness-driven morphable multi-dimensional differentiated charging-discharging strategy for electric vehicle cluster

Driven by the global clean energy transition and the “Dual-Carbon” strategy, the explosive growth of electric vehicles (EVs) has introduced substantial “mobile energy storage” resources into regional integrated energy systems (RIES). However, the temporal and spatial randomness associated with EV charging and discharging poses new challenges for peak-valley imbalances and multi-energy coordination. To address these issues, this study proposes a Slackness-Driven Morphable Multi-Dimensional Differentiated Charging/Discharging Strategy for EVs (SCDS), a Cross-Spatiotemporal Flexible Allocation Strategy for Hydrogen Energy Considering Seasonal Characteristics (CHES) and develops a Multi-objective Status-Based Optimization Algorithm (MOSBOA), which aims to balance economic benefits, environmental sustainability, and stakeholder profits. First, the proposed SCDS quantifies user-perceived flexibility in time and energy as a slackness index, dynamically adjusts EV charging/discharging prices, effectively mitigates peak-valley disparities, and enhances charging station utilization. Second, CHES introduces two evaluation indices, “storing worthiness” and “discharging worthiness”, to assess the cross-seasonal value of hydrogen energy and alleviate structural imbalances like “spring storage, winter shortages”. Third, the MOSBOA algorithm incorporates consensus-based diversity mechanisms, multi-source knowledge fusion, and hierarchical collaboration strategies to improve both the convergence speed and distribution quality of high-dimensional nonlinear Pareto front solutions. Lastly, a two-layer scheduling framework is developed based on industrial, commercial, and residential RIES scenarios. The upper layer employs MOSBOA to optimize pricing signals, while the lower layer uses Gurobi to solve energy dispatch and energy trading problems, forming a “pricing-response-rescheduling” closed-loop system. Simulation results demonstrate that the integration of SCDS and CHES reduces the total economic cost of the RIES by 21.1%, increases the revenue for energy producers and energy managers by 23.5% and 22.4%, respectively, and achieves a 7.2% reduction in annual carbon emissions.