From the background of the liberalization of electricity and city gas retail market, it is considered that in the future Japan will move to a distributed supply form from each building and household. In order to properly place and operate this decentralized supply facility in the city, knowledge of time-series demand fluctuation in urban scale is necessary, but since there is no data or estimation method corresponding to this, it is necessary to develop one. In this research, we first developed a program to estimate the energy demand fluctuation at five-minute intervals of non-residential buildings in urban scale into four energy applications (electricity, cooling, heating, and hot water supply). First, we acquire the building information (usage, extended floor, and coordinates) of the target city by GIS (Geographic Information System) data. Based on this data, we predict the demand fluctuation by building as a reference. By distributing the value, using probability density based on statistical and measurement data, we reproduced the variation of demand due to the difference of building characteristics which cannot be obtained via GIS data. We estimate the demand fluctuation for a city by integrating the building-specific demand fluctuation estimation values. In this paper, the calculation was carried out using a program for Fukuoka city, Tenjin and Hakata districts, and the estimation result was compared and verified. Based on the data obtained by the urban energy demand estimation program, we will consider optimal placement and operation methods of distributed supply equipment typified by PV panel, cogeneration, and storage battery. By flagging the presence or absence of equipment for each building and calculating it, we compared and examined the amount of energy reduction in each pattern.
|ジャーナル||IOP Conference Series: Earth and Environmental Science|
|出版ステータス||出版済み - 8月 9 2019|
|イベント||Sustainable Built Environment Conference 2019 Tokyo: Built Environment in an Era of Climate Change: How Can Cities and Buildings Adapt?, SBE 2019 Tokyo - Tokyo, 日本|
継続期間: 8月 6 2019 → 8月 7 2019
!!!All Science Journal Classification (ASJC) codes