| Abstract |
This paper proposes total optimization of smart city (smart community, SC) using initial searching points generation based on k-means algorithm. In this paper, energy flow models of various sectors in SC are utilized. Namely, energy supply models such as electric power utility, natural gas utility, drinking water treatment plant, and waste water treatment plant, and energy consumption models such as industry, building, residence, and railroad are utilized. Using the SC model, energy costs, actual electric power at peak load hours, and the amount of CO2 emission of the whole SC is minimized This paper proposes an initial searching points generation method based on K-means algorithm in order to set the initial searching points in several attractive areas in which quality of solutions are relatively high, without prior information. The proposed method is applied to a model of Toyama city, which is a moderately-sized city in Japan. Optimal operation by the proposed method is compared with that by pseudo-random number generator (PRNG) based initial searching points. |