TY - JOUR
T1 - Estimation of time series urban energy demand and Examination of optimal energy supply system
AU - Takahashi, K.
AU - Ueno, T.
AU - Sumiyoshi, D.
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number JP17K14773 and 18J12025
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/8/9
Y1 - 2019/8/9
N2 - 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.
AB - 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.
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U2 - 10.1088/1755-1315/294/1/012024
DO - 10.1088/1755-1315/294/1/012024
M3 - Conference article
AN - SCOPUS:85071844874
SN - 1755-1307
VL - 294
JO - IOP Conference Series: Earth and Environmental Science
JF - IOP Conference Series: Earth and Environmental Science
IS - 1
M1 - 012024
T2 - Sustainable Built Environment Conference 2019 Tokyo: Built Environment in an Era of Climate Change: How Can Cities and Buildings Adapt?, SBE 2019 Tokyo
Y2 - 6 August 2019 through 7 August 2019
ER -