Increasing integration of wind energy through the joint operation of electric vehicles and the grid using the intelligent spider monkey algorithm - Han Xiaoming; Qian Jingjing (Engineering Science and Technology, an International Journal)
This study introduces an advanced framework to enhance the integration of wind energy into power systems by utilizing electric vehicles (EVs) as dynamic energy storage units through vehicle-to-grid (V2G) technology. The proposed cooperative model integrates EV aggregators with wind power systems, operating under a single commitment approach with security constraints. Unlike existing studies, this framework incorporates detailed modeling of EV aggregation, accounting for diverse user travel patterns, time-varying energy storage capacities, and the complexities of charging and discharging behaviors. A significant innovation involves demonstrating that prohibitive constraints on simultaneous charging and discharging can, under specific conditions, be relaxed without compromising system stability, thereby simplifying the optimization process. The optimization problem is formulated as a single objective problem and solved using an improved spider monkey optimization algorithm. This algorithm delivers robust convergence, computational efficiency, and highly accurate solutions to complex energy dispatch problems. The framework is validated through extensive case studies on the IEEE system, incorporating realistic wind energy profiles and EV penetration scenarios. The research demonstrates a 28 % improvement in wind energy absorption, a 15 % reduction in thermal unit operating costs, and a substantial mitigation of storage violations under dynamic conditions. Furthermore, the study highlights the role of V2G in balancing renewable energy variability and reducing peak load pressures, showcasing its potential to optimize grid operations and improve reliability.