Total Optimization of Smart City by Brain Storm Optimization

This paper proposes a total optimization method of a smart city (SC) by brain storm optimization (BSO). The method utilizes a SC model. The model includes natural gas utilities, electric power utilities, drinking and waste water treatment plants, industries, buildings, residences, and railroads. It minimizes energy cost, shifts actual electric power loads, and minimizes CO2 emission using the model. Particle Swarm Optimization (PSO), Differential Evolution (DE), and Differential evolutionary particle swarm optimization (DEEPSO) have been applied to the optimization problem. However, there is room for improving solution quality. The proposed BSO based method is applied to a model which considers a moderately-sized city in Japan, such as Toyama city. The proposed method is compared with the conventional PSO, DE, and DEEPSO based methods with promising results.