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[CRIEPI Research Report]

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[Detailed Information]

Êó¹ð½ñÈÖ¹æ [Report Number]
Y14003
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[Title]
Utilization of Smart Meter Data's Analytical Information -Trend of Technology and an Exploratory Demand Analysis-
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[Abstract]
Although power utilities are about to install smart meters in residential sectors, data analysis methods for smart meters are not sufficiently developed. In this respect, this report surveys data analysis technologies for smart meters and identifies the trend. Also, an exploratory analysis is conducted to estimate temperature-sensitive demands and other properties for individual households. The survey shows that the data objectives include 'support for efficient use of energy' to increase the efficiencies of energy-saving and demand-response programs, and 'support for tariff selection' to allow comparison of electricity bills. Data analysis technologies meeting those objectives include 'simplified disaggregation' to estimate what kinds of activities cause demand, based on the master switch load curve, and 'life pattern estimation', based on occupancy rate. To verify these data analysis technologies, in the exploratory analysis, regression analysis incorporating life patterns estimation was used to extract the following from the master switch load curves of four households: i) temperature-sensitive demand, ii) variable demand, and iii) static demand. The results show that the method can estimate rough trends in hourly air conditioner usage and activity levels by days of the week in each house. The information obtained from such analysis can be used for targeted advices or demand response programs intended to reduce demand of heavy-consuming customers who are at home in the afternoon.
Êó¹ð½ñǯÅÙ [Report's Fiscal Year]
2014
ȯ¹Ôǯ·î [Issued Year / Month]
2014/11
Êó¹ð¼Ô [Author]

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¥­¡¼¥ï¡¼¥É [Keywords]
ÏÂʸ ±Ñʸ
ÅÅÎϼûÍ× Electricity demand
¥¹¥Þ¡¼¥È¥á¡¼¥¿ Smart meter
²ÈÄíÉôÌç Residential sector
¾Ê¥¨¥Í¥ë¥®¡¼ Energy efficiency
ÀáÅÅ Electricity saving
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