Optimization of a wind-photovoltaic-electrolysis integrated power-to-hydrogen-to-power plant for grid stability and hydrogen export

This study develops a novel bi-level optimization framework for the design and operation of an integrated Power-to-Hydrogen-to-Power facility, combining variable renewables (wind and solar Photovoltaic), proton exchange membrane electrolysis, large-scale underground hydrogen storage (depleted gas reservoirs), and hydrogen-fueled gas turbines. Focused on the Pearl River Mouth Basin in Guangdong, China, the system addresses grid stability while enabling green hydrogen export. A hybrid Particle Swarm Optimization–Modified Water Wave Optimization algorithm determines optimal component sizing to maximize net present value, coupled with a high-resolution dispatch model using IBM ILOG CPLEX. The optimized configuration includes 275 MW wind, 120.7 MW solar Photovoltaic, 156.6 MW gas turbines, 106.2 MW proton exchange membrane electrolyzer, and 1724 tons of hydrogen storage. The plant achieves over 85% renewable integration, 100% supply-demand matching, and flexible seasonal operation. It delivers a levelized cost of electricity of 0.1056 USD/kWh and a levelized cost of hydrogen of 4.664 USD/kg. Although the unsubsidized net present value is negative, the system significantly reduces land (41.8 km2) and water (150.46 × 103 m3/year) use, supporting the need for policy incentives. The proposed architecture offers a scalable blueprint for low-carbon, resilient energy systems aligned with future sustainability goals.