Optimal planning of grid-connected energy storage and renewable energy sources integration using an improved whale...

The integration of renewable energy sources (RESs) into energy systems poses considerable operational challenges, due to their intermittent and stochastic nature. Grid-connected energy storage systems (ESSs) present a compelling alternative for reliably accommodating various RESs. This paper presents an optimal scheduling for allocating wind-storage system capacity in high mountain regions with abundant wind resources and irrigation pumping demand. To capture uncertainty in wind and solar generation, a scenario-free stochastic formulation is adopted, enabling tractable and scalable uncertainty modelling. To reduce the overall lifecycle comprehensive cost (COC), a synergistic optimization model is developed by integrating features of wind energy, pumping unit parameters, and storage configurations. The model considers startup/shutdown losses, optimal flow distribution, and operating expenses of the pumping station while optimizing energy storage capacity. A single-battery system is compared with a hybrid battery-hydrogen storage strategy. Results show the hybrid solution reduces COC by 5.4%, alleviates battery operational stress, and maintains pumping station efficiency. The framework incorporates a reliability model for wind power generation, ensuring robust lifecycle cost optimization. This approach demonstrates the financial and technological benefits of hybrid storage in renewable energy-driven irrigation systems. Simulations in the case study validate the flexibility and effectiveness of the proposed approach across various practical settings.