Optimizing combined heat and power systems for multi-residential buildings: A multi-objective framework for sustainable energy management

This study presents a novel multi-objective optimization framework for combined heat and power systems in multi-residential buildings carried out at the Chikballapura District in the State of Karnataka, India. The proposed approach uses a hybridized optimization model to determine the optimal size and operating schedule of the CHP system. Utilizing an innovative combination of Cuckoo Search and Non-dominated Sorting Genetic Algorithm II (CN2R), the approach determines the optimal size and operating schedule of the CHP system. The model considers both electrical and thermal energy demands of the building to minimize total energy costs while satisfying year-round energy requirements. Our findings demonstrate that the proposed CN2R model achieves a 15% reduction in energy costs compared to conventional methods, while also improving thermal efficiency by 12%. Additionally, the integration of thermal and electrical energy storage into the system resulted in a 20% increase in self-consumption of generated energy, significantly reducing reliance on grid electricity. The model also contributed to a 25% decrease in CO2 emissions, underscoring its potential for sustainable energy management in residential buildings. These results confirm the model’s capability to optimize CHP systems effectively, offering both economic and environmental benefits. •A novel multi-objective (CN2R) optimization framework is presented for building sustainability.•The CN2R framework optimizes energy demands in buildings to reduce costs year-round•It examines how building configuration impacts the design and economic viability of the system.