| Abstract |
In a smart city, energy usage for sustaining indoor environmental quality (IEQ) and occupant comfort levels frequently clash. This research aims to design a novel approach to solve the conflict between the use of power and the comfort of the citizens. A multi-purpose problem for minimum consumption of energy as well as maximum occupant's ease within the energy-efficient construction for smart city as a future has been formulated. Across suggested design method, three variable namely temperature (°C), illumination level (lux), as well as Carbon dioxide (CO2-ppm) have been undertaken for occupant's comfort. The Crisscross Search Particle Swarm Optimization (CSPSO), a revolutionary solution for the design method, has been applied to search for the optimal value of environmental factors (temperature, light level, CO2) in relation to user-set preferences. In the heuristic method, the augmented particle swarm optimization strategy updates an initial solution before updating the best local solutions through length and breadth crossover operators. The CSPSO approach search explores the search space in all dimensions and reduces the stagnation trouble by through length and breadth crossover operators. The temperature, lighting, CO2 sensors data, and user-defined parameters are all inputs to the CSPSO algorithm, and the optimized parameters are the outputs of the optimization method. Such optimized parameters will become an input to the fuzzy controllers that adjust various actuators' status according to the users' comfort. Utilizing the CSPSO technique, 22.74% energy of 625.372 kWhr energy was saved during a day, and the comfort level has increased from 0.51692 to 0.75685. Therefore, the proposed novel design approach is acceptable in managing building energy consumption by achieving maximum comfort. © 2022 American Institute of Chemical Engineers. |
