Abstract
This research work proposed a hybrid model to maximize energy consumption and maximize user comfort in residential buildings. The proposed model consists of two widely used optimization algorithms named the firefly algorithm (FA) and genetic algorithm (GA). The hybridization of two optimization approaches results in a better optimization process, leading to better performance of the process in terms of minimum power consumption and maximum occupant’s comfort. The inputs of the optimization model are illumination, temperature, and air quality from the user, in addition with the external environment. The outputs of the proposed model are the optimized values of illumination, temperature, and air quality, which are, in turn, used in computing the values of user comfort. After the computation of the comfort index, these values enter the fuzzy controllers, which are used to adjust the cooling/heating system, illumination system, and ventilation system according to the occupant’s requirement. A user-friendly environment for power consumption minimization and user comfort maximization using data from different sensors, user, processes, power control systems, and various actuators is proposed in this work. The results obtained from the hybrid model have been compared with many state-of-the-art optimization algorithms. The final results revealed that the proposed approach performed better as compared to the standard optimization techniques.
Highlights
One of the most prominent applications of technological integration with AI techniques is the conception of smart or energy-efficient buildings
From hour 14 to hour 24, the results show that the firefly algorithm (FA)-genetic algorithm (GA) produced the most reduced error difference for the actual and optimized temperatures
A hybrid algorithm of one evolutionary intelligence (EI) technique—namely, the GA, and one swarm intelligence (SI) approach called the FA was developed for the multi-objective optimization problem of energy consumption minimization and management of the indoor environmental quality (IEQ) of smart buildings
Summary
One of the most prominent applications of technological integration with AI techniques is the conception of smart or energy-efficient buildings. The authors are of the opinion that there are many other parameters that can be useful for defining the ITQ, but covering all of them for maintaining a standardized thermal requirement is one of the sophisticated tasks during building energy management. The internationally accepted standard for developing an IEQ is the ANSI/ASHRAE guidelines 10P, which recommend a few parameters when working with design, development, and operations of energy-efficient buildings [13]. In this standard, the ITQ, IAQ, aural, and IVQ are separately addressed.
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