Crop‐light constrained circular‐energy optimization of a semitransparent photovoltaic greenhouse

Greenhouse cultivation faces the fundamental challenge of balancing energy supply, crop growth requirements, and environmental sustainability within a single production system. This study develops a deterministic linear optimization model that simultaneously coordinates photovoltaic generation, heat pumping, electrical and thermal storage, supplemental lighting, drainage reuse, reverse osmosis, freshwater consumption, sodium quality, greenhouse gas emissions, and nutrient discharge in a 1000 m 2 semitransparent photovoltaic tomato greenhouse located in Çanakkale, Türkiye. The model is formulated as a multi‐objective ε‐constraint problem with 10,620 continuous decision variables, solved over 366 days divided into day and night periods, and evaluated across twelve scenarios, including reference, cost‐optimal, environmentally constrained, and technology‐ablation cases. A balanced solution based on the case‐study weather data achieved simultaneous reductions of 20% in greenhouse gas emissions, 25% in freshwater use, and 96% in nitrogen and phosphorus discharges, with only a 0.74% increase in annual cost compared with the fossil fuel‐based reference system. This solution selected 418.40 kWp of photovoltaic capacity, 502.99 kW th of heat pump capacity, 2.13 MWh of thermal storage capacity, and 2.90 m 3 /d of reverse osmosis capacity, while setting the battery capacity to 0. The results demonstrated that crop‐light and water‐quality constraints materially affect renewable energy design; carbon‐only optimization fails to deliver comparable improvements in water and nutrient quality; removing thermal storage increases costs by 3.58%; and removing photovoltaic, heat pump, or reverse osmosis renders the joint environmental targets infeasible. The model developed in this study provides a reproducible pre‐feasibility framework for integrated greenhouse energy‐water‐environment management.