Search

This study assesses the effects of sending home energy reports utilizing the Home Energy Management System (HEMS) data to more than 1600 households in Japan. The treatment effect was verified using a panel data regression random effects model comparing the electricity consumption of a treatment group to which the report was sent with that of a control group that was not sent. The report was effective in winter and led to a 3.4% reduction in electricity consumption compared to the previous year in the average household. A further reduction of 5.4% for the households with higher electricity consumption for whom a significant reduction of 11.4% in the use of space heating was also observed. Although the treatment effect was not significant in summer for the average household, larger households reduced consumption by an overall average of 2%, with reductions of 6.8% and 7% in terms of space cooling and hot water use, respectively, from the previous month. In contrast, smaller households increased their space cooling consumption by more than 10% on average, which might be considered an undesirable boomerang effect. The accumulative treatment effect in a detached house group was also confirmed. Additionally, an accumulative two-year winter consumption reduction of 7.5% demonstrated the effectiveness of continual intervention. [ABSTRACT FROM AUTHOR]

Japan's energy consumption in 2018 was about 2.5 times that in 1975, with the increase in the household sector being the largest at 28%. Most of primary energy is still fossil fuel, and it is urgent to reduce energy consumption in the household sector. The purpose of this paper was to identify ways to reduce household energy consumption without compromising the quality of life in residence. However, the reduction methods vary by region, building specifications, household type, equipment specifications, season, and weather. The value of this paper is based on a systematic analysis of home energy management systems (HEMS) data from about 50,000 households under various conditions. We are analyzing ways to reduce energy consumption. Few studies have analyzed this much back-up data, which is likely to lead to a reduction in CO2 emissions across the household sector. To explore ways to reduce energy consumption in this sector, the company has introduced and provided services for home energy management systems (HEMS) since 2011 and is currently collecting HEMS data for up to 50,000 households. In order to grasp the actual state of energy consumption in each household, HEMS data are systematically analyzed, necessary conditions for energy reduction and self-sufficiency rate (SSR) improvement are analyzed, and energy consumption under certain conditions is estimated using storage batteries (SB) and heat pump water heaters (HPWH). In addition, energy consumption was investigated by actual measurement and simulation for several hundred households. Since power generation and consumption vary greatly depending on the region, building specifications, household type, equipment specifications, season, weather, etc., it is necessary to analyze these factors systematically. As a conclusion, in order to improve SSR, it is necessary to (1) reduce surplus power consumption and energy consumption of heat pump water heaters (HPWHs), (2) increase solar power generation, and (3) increase the size of SB. This study contributes to the spread of advanced housing and the reduction of CO2 emissions in the household sector. [ABSTRACT FROM AUTHOR]

To develop a decarbonized society, two contradictory requirements must be met: (1) reducing energy demand and (2) creating flexibility in energy demand in order to respond to fluctuations in renewable electricity generation. To help meet these requirements, conventional energy efficiency studies should be extended to incorporate "energy demand science." This paper presents a definition of "energy demand science" and then reviews the related history and research questions of energy demand science in the context of the residential sector. It then examines three key areas that must be integrated into the next-generation energy demand science: (1) energy demand measurement with detailed granularity and analysis using cutting-edge technology, (2) energy demand modeling that helps clarify the formation mechanism of energy demand, and (3) identification of the factors that influence people's decision making, which represents typical human-dimension research. Energy demand science consists of technical, human, natural environment, demographic, and land-use dimensions, and their integration is key for the establishment of a decarbonized society. • Energy demand must be reduced and have the flexibility to establish decarbonization. • Knowledge integration is needed for planning, design, and operation of energy systems. • As energy demand data becomes more granular, data analysis methods must do the same. • High spatiotemporal modeling and consideration of occupant behavior is necessary. • Identification of factors influencing behavior is important to a human-dimension study. [ABSTRACT FROM AUTHOR]