V. S. K. V. Harish
Department of Electrical Engineering, School of Technology, Pandit Deendayal Petroleum University Gandhinagar, Gujarat, 382007, India.
Department of Hydro and Renewable Energy, Indian Institute of Technology Roorkee, Uttarakhand, 247667, India.
Building energy management systems with high-level of sophistication have to control and manage a large set of actuators and other equipment and evaluate performance of each and every-subsystem on periodic basis. In the present study, a control algorithm has been developed as an engineered solution for intelligent energy control and comfort management in buildings. A hybrid genetic algorithm - particle swarm optimization based multi-objective optimization routine is developed to compute the optimal set-point level of heating, ventilation, and air conditioning and lighting systems with a view to balancing energy consumption and occupants' comfort. Occupants' comfort is evaluated for indoor air quality as CO2 concentration, thermal and visual comfort. Case studies with a different set of optimal parameters have been worked out to calculate the amount of energy consumed as well as comfort level achieved. Overall occupants' comfort was improved by 17% and daily, weekly and monthly building energy consumption was reduced by 2.5%, 7.7%, and 17.9%, respectively. The developed intelligent control strategy can be integrated with building automation systems to achieve finely tuned real-time optimized comfort management
Keywords- Building energy model, Multi-objective optimization, Genetic algorithm, Particle swarm optimization, Pareto-front, Occupancy, comfort.
Harish, V. S. K. V., & Kumar, A. (2020). Simulation Based Energy Control and Comfort Management in Buildings Using Multi-Objective Optimization Routine. International Journal of Mathematical, Engineering and Management Sciences, 5(6), 1324-1332. https://doi.org/10.33889/IJMEMS.2020.5.6.098.