Performance dynamics of hybrid energy management strategies for greenhouse heating across Lebanon’s microclimates

Sustainable greenhouse production under Mediterranean climatic conditions requires reliable heating systems to maintain crop productivity during winter. This study presents a dynamic energy management framework for a greenhouse farm in Lebanon composed of 20 Quonset-type greenhouses installed on a 10,000 m 2 site, heated and maintained at 18 °C using an air-source heat pump. Five operating strategies are investigated under limited photovoltaic (PV) installation area constraints, including a single diesel generator (550 kW) with and without heat recovery, dual diesel generators (550 and 120 kW), and hybrid photovoltaic–battery–diesel systems using either south-facing PV panels (426 panels, 92 lithium-ion batteries) or east–west-oriented PV arrays (720 panels, 155 lithium-ion batteries). Unlike conventional annual-average approaches, the proposed methodology employs an hourly dynamic simulation combined with a Multi-Source Dispatch Heuristic Algorithm (MSDHA) to coordinate diesel generation, photovoltaic production, battery storage, and thermal demand. A multi-objective Pareto optimization based on the importance of cost of energy (COE), renewable fraction, and payback period is applied to rank the investigated strategies. In addition, sensitivity analyses are conducted across multiple climate zones, years, and fluctuating diesel fuel prices to evaluate the robustness of the proposed framework under varying environmental and economic conditions. The results demonstrate that fully eliminating diesel generation remains impractical for greenhouse heating under the investigated conditions. Under balanced criteria, the dual-generator configuration achieved the best overall performance with a COE of 0.3455 $/kWh due to improved part-load efficiency. When environmental performance was prioritized (>60%), the hybrid south-facing PV configuration became the optimal solution with a COE of 0.3621 $/kWh for a fuel price of 0.85$/L. Overall, the developed framework provides a scalable optimization tool for greenhouse microgrid design and advanced agricultural energy management.