Assessing the financial viability of PV integration and grid expansion for wind farms

To meet ambitious renewable energy targets, innovative solutions are critical. Hybrid power plants (HPPs), combining wind turbines and solar photovoltaic (PV) systems at shared grid connections, offer significant potential. This approach optimizes resource use and addresses the challenge of limited transmission capacity, accelerating the energy transition. Oversizing HPPs relative to grid capacity allows more electricity to be exported without costly grid upgrades. Integrating PV with wind farms is a cost-effective strategy, though profitability and optimal sizing depend on site conditions, electricity prices, and financial factors. This study develops a Python-based optimization model using Pyomo, applicable to any location. The model incorporates wind and PV resource availability and electricity prices to determine the optimal PV capacity for integration into wind farms using existing grid connections. Curtailment in oversized HPPs remains below 5 % at a 200 % HPP-to-grid capacity ratio. The economic viability of grid expansion is evaluated, assessing whether the additional PV generation revenue justifies the associated costs. The model is applied to a case study in a country with high-resolution, 0.25-degree mesh grid locations, using ERA5 reanalysis data for hourly wind and PV generation estimates. Profitability is analyzed using historical day-ahead (spot market) prices, with sensitivity analyses under various financial scenarios. Results indicate that, even in regions with low solar potential, hybridizing wind farms with PV is profitable in some locations. Grid expansion is economically beneficial only in high-potential areas. This globally applicable model provides a framework for identifying viable sites for hybrid wind-PV projects and grid expansion, supporting the renewable energy transition.