Optimised scheduling of a cogenerative subnetwork based on a micro gas turbine and thermal storage with the addition of an innovative solar assisted heat pump and Ni-Zn battery

The Innovative Energy Systems (IES) laboratory at the University of Genoa features a plant configuration comprising a micro gas turbine, latent heat thermal energy storage, an innovative heat pump system connected to solar façade panels, and a NiZn battery. This study presents the optimization of four distinct sub-plant configurations, focusing on their economic and environmental performance across different seasons (January, April, July, and October) under two market scenarios (no selling price or selling price equal to buying price). A genetic algorithm-based tool is developed for the optimized energy scheduling of these configurations, taking into account the operational characteristics of programmable, non-programmable energy sources and energy storage devices. The analysis highlighted that when the selling price is equal to zero, the system is optimised to improve sell-consumption. The addition of the battery or the heat pump to the system always leads to reduction of operational costs compared to the baseline case with only the micro gas turbine and thermal energy storage. Notably, the heat pump alone provides greater cost benefits than the battery, although the combined use of both systems yields the highest cost reductions ranging, depending on the month, up to − 16.9% in the “no sell” scenario and up to − 12.3% when selling and buying prices are equal. Regarding the CO2 emissions, both components lead to an emission reduction in the “no sell” scenario while only the HP guarantees an emission reduction during the “equal to buy” scenario, in both cases up to − 20.5% less. This analysis highlights the economic and environmental advantages of integrating NiZn battery storage and a solar-assisted heat pump into the energy system, demonstrating cost savings and emission reductions across various market conditions and seasonal demands.