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Residential energy and carbon management system for a city and a nation

Panel: 4. Monitoring and evaluation for a wise, just and inclusive transition

This is a peer-reviewed paper.

Authors:
Yoshiyuki Shimoda, Osaka University - Division of sustainable energy and environmental engineering, Graduate School of Engineering, Japan
Misaki Fujiwara, Osaka University, Japan
Toshiki Nakanishi, Osaka University, Japan
Yohei Yamaguchi, Osaka University, Japan
Hideaki Uchida, Osaka University, Japan

Abstract

A digital twin model for energy and carbon management of the building sector, both nationally and at the city level, is developed. The model consists of the following three tools: 1) a bottom-up, end-use energy simulation model that replicates the energy demand determination mechanism, 2) individual statistical data that explain the relationships between household/building characteristics and appliance ownership/energy-saving behavior, which enables the model to consider the heterogeneity of households and buildings, and 3) smart meter data that can be used to analyse the energy efficiency progress of households and buildings. The concept of an energy/carbon management system is introduced and the progress of the Japanese Plan for Global Warming Countermeasures (PGWC) is assessed. A distinctive feature of the Japanese PGWC is that it clearly identifies the target diffusion amounts for each countermeasure technology. To simulate Japan's residential sector, a representative sample of 0.03 % of Japanese households is randomly selected, and various characteristics, including the number and attributes of household occupants, the thermal performance of the residential building, occupant ownership and use of home appliances, and the type of water heater and space heating equipment, are used to accurately reflect population heterogeneity. With these data, together with weather data for the target years, the annual energy demand of the Japanese residential and non-residential sectors is simulated for 2013-2019. In the residential sector, the impact of differences in weather conditions is found to be substantial, reaching a maximum of 50 %. For the non-residential sector, the effect of weather differences is relatively small. The effect of the government's energy efficiency measures as estimated by the simulation is smaller than the government estimates for both the residential and non-residential sectors, and is well below the government’s 2019 target.

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