Journal of Japan Society of Energy and Resources
Online ISSN : 2433-0531
ISSN-L : 2433-0531
Research Paper
Study on Methods for Reducing Prediction Errors in Demand Response Linked to Market Prices Using Household Storage Batteries
Nodoka Nakagaki Ryouji SezaiSatoshi IzumiyaTakashi FurukawaKenta Kinoshita
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2025 Volume 46 Issue 1 Pages 38-46

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Abstract
Electricity retailers procure electric power by combining multiple methods strategically. If they select Demand Response (DR) using Virtual Power Plant(VPP) systems as their procurement means, it is expected to reduce purchasing volume from wholesale electricity market and shift those for arbitrage. We studied estimation methods to reduce the impact of forecast errors in electricity consumption on DRs and the effective approaches for battery level management. In simulations of VPP system using these methods on 80 houses, we confirmed that the response error was within 10% on average. It was also confirmed that the error could be kept within ±10% in 90% of the DR cases when 0.1 kW per customer can be supplied. Moreover, we verified the equivalent accuracy in a demonstration experiment using three houses.
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© 2025 Japan Society of Energy and Resources
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