Can integrating wastewater heat recovery with a passive geothermal borehole improve the cost-effectiveness? Optimal energy management through ANN and genetic algorithm

This article introduces a new advanced solution to act against global CO2 emission increment and reduce the building sector's primary energy needs and costs. The core idea is to harness domestic hot water's waste heat to improve the efficiency of heating, ventilation, and air conditioning systems. Also, the system is equipped with a naturally driven geothermal borehole to freely generate heating and cooling. The suggested system's performance is assessed and compared with the conventional model integrated with exhaust ventilation from all aspects using TRNSYS software. A genetic algorithm and artificial neural network model are combined to identify the optimal condition where energy cost is minimized, and the CO2 saving and energy reduction ratio are maximized. Moreover, the proposed system's performance is evaluated transiently by observing the impact of the outdoor condition on the main techno-environmental and economic aspects under optimal conditions. The findings indicate a conflicting shift in the main indicators, including emission and energy savings, levelized cost of energy, and saving ratio, when the key variables are altered, highlighting the optimization need. According to the results, the optimization cut the carbon emission by 600 kg and levelized energy cost by 14 $/MWh, resulting in a final value of 50.5 $/MWh. Additionally, the energy saving and saving ratio is improved by about 2.6 MWh and 1.2 % over a year, showing the optimization robustness to find the best condition satisfying all metrics. The results present that under optimal conditions, integrating wastewater preheating and borehole backup for air preheating results in the highest heating contributions during January (14 MWh) and December (13 MWh).