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Setsuden” - Data Survey on the Potential for Japan’S Electricity Savings by Behavioural Change

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Setsuden” - Data Survey on the Potential for Japan’S Electricity Savings by Behavioural Change IEEJ©2021 CERT Thematic Discussions: The role of ʻbehavioural aspectsʼ for reaching net zero emissions by 2050 Impact of “Setsuden” - data survey on the potential for Japan’s electricity savings by behavioural change 16 February, 2021 The Institute of Energy Economics, Japan Naoko DOI, and Asamu OGAWA What is “Setsuden” ? Weather-adjusted Peak Electricity Savings Rate July- • “Setsuden” is electricity savings September (compared with July-September in 2010) resulting from 11.0 11.7 technical/operational efficiency % % 11.2 improvement – including 10.7 % 8.8% % 8.5% behavioral change. 8.5% 6.0% • To cope with the rolling blackout 2011 2012 2013 2014 2011 2012 2013 2014 after the Great Eastern Japan TEPCO KEPCO Earthquake in 2011, Ministry Source: Nishio (2016). “Energy Efficiency, Electricity Savings Behavior - its Trends, requested industry, commercial Promoting Methods, and Challenges for Verification” and residential consumers to facilitate electricity peak savings. Actions for Residential Electricity Savings 56% 55% 48% 51% • 59% 41% 44% 41% 46% The behavioral change for 37% 42% 44% 48% 30% 31% 25% 38% 33% 30% 21% 23% electricity peak savings and 31% 17% 7% 16% electricity consumption savings – TEPCO Ar ea KEPCO Area 2% 4% 3%4% 2011 2012 2013 2011 2012 2013 2011 2012 2013 2011 2012 2013 2011 2012 2013 Replace Refrigerator Adjust Refigerator prompted by the emergency Shorter AC Adjust AC Temp. Shorter Lighting Hours Operational Hours with EE Temp. 21 situation – continues to be IEEJ©20 implemented. Source: Nishio (2016). “Energy Efficiency, Electricity Savings Behavior - its Trends, Promoting Methods, and Challenges for Verification” 1 The Outline of METI Commissioned Study: “Electricity Demand and Potential for Peak Demand Savings” (1) Survey/ measure: 10,000 households and and 10,000 building owners/occupants for 3 different seasons (summer, middle, winter) in 10 regions in Japan (2) Estimate load curve: for 3 different seasons (summer, middle, winter) by technology in 10 regions in Japan Source: https://www.meti.go.jp/meti_lib/report/H30FY/000385.pdf Note: A 899-page report on detailed analysis for 10 regions in Japan (3) List up menus of peak demand savings: for 3 seasons by 10 Regions in Japan technology for 10 regions Hokkaido Hokuriku (4) Estimate potential for Chubu Tohoku electricity savings: for 3 seasons in 10 Chugoku Kanto regions Okinawa Kinki Shikoku (5) Consider method for information Kyushu diffusion: for 3 seasons in 10 regions Source: FEPC • For emergency preparedness and load leveling, the IEEJ implemented METI (Ministry of Economy, Trade and Industry, Japan) commissioned study in FY 2019 on the impact of “Setsuden”. The study was conducted along with 21 the Energy Conservation Center, Japan, Jyukankyo Research Institute, and Dentsu Corp. • This presentation covers the results on residential sector – although the METI’s study included the analyses of the IEEJ©20 commercial sector. 2 Surveyed IEEJ©2021 Measured data with Comparison Estimate Load Curve by Region by Curve Load Estimate • hours hours operational ownership, Appliance region) (by consumption/household electricity Hourly region, by household) (by consumption/household electricity Hourly region, by household, by residential building) (by consumption/household electricity Hourly Regional hourly load curve load hourly Regional region) (by consumption electricity Hourly summer, middle, winter in 10 regions. for implemented is estimation This utilities. electric from data curve load hourly regional the with compare to data measured 3) data, statistical 2) data, surveyed 1) using estimated is curve load electricity Residential Estimation Method Estimation consumption by power Rated building residential of appliance, by type appliance by al hours operation Usage, Surveyed region by Temperature household Number of house/apartment detached of Ratio people/household) (numberof type household of Ratio Estimated Load Curve by Appliance (Summer) Appliance by Curve Load Estimated W/household W/household W/household W/household W/household 1,000 1,200 1,000 1,200 1,000 1,200 1,000 1,200 1,000 1,200 200 400 600 800 200 400 600 800 200 400 600 800 200 400 600 800 200 400 600 800 Source:The Institute of Energy Economics, Japan (2020) 0 0 0 0 0 W/ W/ W/ W/ W/ 0:00 0:00 0:00 0:00 0:00 1:00 世帯 1:00 世帯 1:00 世帯 1:00 世帯 1:00 世帯 2:00 2:00 2:00 2:00 2:00 3:00 3:00 3:00 3:00 3:00 4:00 4:00 4:00 4:00 4:00 5:00 5:00 5:00 5:00 5:00 Chugoku Hokuriku 九州 中国 北陸 関東 6:00 6:00 6:00 6:00 6:00 北海道 7:00 Kyushu 7:00 7:00 7:00 7:00 8:00 8:00 8:00 8:00 8:00 Hokkaido : : : : Kanto 9:00 合計（夏期） 9:00 合計（夏期） 9:00 合計（夏期） 9:00 合計（夏期） 9:00 : 10:00 10:00 10:00 10:00 10:00 合計（夏期） 11:00 11:00 11:00 11:00 11:00 12:00 12:00 12:00 12:00 12:00 13:00 13:00 13:00 13:00 13:00 14:00 14:00 14:00 14:00 14:00 15:00 15:00 15:00 15:00 15:00 16:00 16:00 16:00 16:00 16:00 17:00 17:00 17:00 17:00 17:00 18:00 18:00 18:00 18:00 18:00 19:00 19:00 19:00 19:00 19:00 20:00 20:00 20:00 20:00 20:00 21:00 21:00 21:00 21:00 21:00 22:00 22:00 22:00 22:00 22:00 23:00 23:00 23:00 23:00 23:00 W/household W/household 1,000 1,200 1,000 1,200 1,000 1,200 1,000 1,200 1,000 1,200 W/household W/household W/household 200 400 600 800 200 400 600 800 200 400 600 800 200 400 600 800 200 400 600 800 0 0 0 0 0 W/ W/ W/ W/ W/ 0:00 0:00 0:00 0:00 0:00 1:00 世帯 1:00 世帯 1:00 世帯 1:00 世帯 1:00 世帯 2:00 2:00 2:00 2:00 2:00 3:00 3:00 3:00 3:00 3:00 4:00 4:00 4:00 4:00 4:00 5:00 5:00 5:00 5:00 5:00 6:00 沖縄 6:00 四国 6:00 近畿 6:00 中部 6:00 東北 Okinawa 7:00 7:00 Shikoku 7:00 7:00 7:00 Tohoku 8:00 8:00 8:00 8:00 Chubu 8:00 Kinki : : : : : 9:00 合計（夏期） 9:00 合計（夏期） 9:00 合計（夏期） 9:00 合計（夏期） 9:00 合計（夏期） 10:00 10:00 10:00 10:00 10:00 11:00 11:00 11:00 11:00 11:00 12:00 12:00 12:00 12:00 12:00 13:00 13:00 13:00 13:00 13:00 14:00 14:00 14:00 14:00 14:00 15:00 15:00 15:00 15:00 15:00 16:00 16:00 16:00 16:00 16:00 17:00 17:00 17:00 17:00 17:00 18:00 18:00 18:00 18:00 18:00 19:00 19:00 19:00 19:00 19:00 20:00 20:00 20:00 20:00 20:00 21:00 21:00 21:00 21:00 21:00 22:00 22:00 22:00 22:00 22:00 23:00 23:00 23:00 23:00 23:00 Machine Washing Cooking Seat Electric Toilet TV/DVD AC Refrigerator Water Heating PC Stand Others Lighting /Router - by 3 Regional Differences, and Seasonal Differences Contributions to Peak Demand Kanto, Summer (14:00) Hokkaido, Summer (16:00) Dryer, 0.6% Stand-by power, 6.2% Washing machine, 0.4% Air Hours of Peak Demand by Season, and Others, 13.0% Conditioner, Electric toilet 15.0% seat, 0.5% Others, by Region Vacuum Dryer, 1.0% 19.6% cleaner, 0.5% Air Washing Stand-by TV, 3.1% Conditioner, machine, PC, 0.6% 44.7% 0.6% power, 7.6% Summer Middle Winter Electric toilet Refrigerator, Electric water 24.7% boiler, 1.0% Lighting, 6.3% seat, 0.8% Hokkaido 16:00 18:00 9:00 Vacuum Electric water cleaner, 1.7% heater, 2.8% Refrigerator, TV, Tohoku 14:00 14:00 17:00 17.8% PC, 0.8% 4.3% Lighting, 10.8% Electric Kanto 14:00 14:00 17:00 Rice Cooker, Electric Rice Cooker, 2.5% water boiler,water heater, 7.0% 1.7% 4.3% Chubu 14:00 14:00 9:00 Kanto, Winter (17:00) Hokkaido, Winter (9:00) Hokuriku 14:00 14:00 9:00 Stand-by, 6.1% Kinki 14:00 16:00 17:00 Kotatsu, Air FF Stove, 0.6% Conditioner, 1.0% 1.8% Chugoku 14:00 14:00 9:00 Others, 13.3% Central Air Road heating, 0.2% Conditioner, heating, Electric floor 23.0% 12.0% Shikoku 15:00 14:00 18:00 heating, 1.5% Refrigerator, Electric carpet, 18.4% Kyushu 14:00 19:00 18:00 2.1% Electric stove, Kotatsu, 2.6% 4.4% Refrigerator, Dryer, 5.2% Road heating, 16.0% Washing Okinawa 16:00 19:00 19:00 0.4% machine, Dryer, 0.6% 1.8%Electric toilet Washing seat, 0.9% machine, 0.3% TV, 3.5% TV, 3.2% PC, Vacuum PC, Lighting, Lighting, Rice Cooker, Source: The Institute of Energy Economics, Japan (2020) Electric toilet 0.5% cleaner, 0.5% 8.2% 7.9% 6.1% seat, 0.6% 2.0% Electric Vacuum Electric water water boiler, Electric cleaner, 2.5% Electric water Rice Cooker, boiler, 1.8% heater, 2.8% 8.7% 1.5% water heater, 3.3% 21 Source: The Institute of Energy Economics, Japan (2020) IEEJ©20 • Effective electricity savings options at peak load should consider operational characteristics by region.
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