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Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 24th Aug 2026, 01:48:13am WEST

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Daily Overview

Session

Egg-Timer: Energy Transition and Technology Adoption
Location: D-110
Session Chair: Graham Macklin, Toulouse School of Economics

Presentation 4

Does an Artificial Intelligence Energy Management System Reduce Electricity Consumption in Japan’s Retail Sector?

GUANYU LU¹, Hajime Katayama¹, Toshihide Arimura¹, Shohei Morimura¹, Tomoichi Ishiwatari², Tetsu Iwasaki²

1: Waseda University, Japan; 2: iGRID SOLUTIONS Inc.

This study examines the impact of “Enudge,” an artificial intelligence (AI) energy management system (EMS), on electricity consumption in the retail sector. As retail installations increasingly contribute to nonindustrial CO₂ emissions, conventional EMSs frequently fail to manage the complex and variable energy demands in these settings. By leveraging a difference-in-differences framework on store-level data from over 1,700 retail stores in Japan between November 2018 and December 2023, this study finds that installation of AI EMS-Enudge reduces electricity consumption by an average of 1.9%. However, this reduction effect declines over time, with electricity savings diminishing within five to ten months. This decay effect is consistent with the decrease in user interaction with the recommendations provided by AI, suggesting that user engagement may play a crucial role in reducing electricity consumption. Heterogeneity analyses reveal that the system’s performance varies across retail establishments and seasonal contexts. Moreover, a cost-benefit analysis aimed at exploring break-even tariffs and implied abatement costs highlights that the installation of an AI EMS can contribute to cost savings, especially under high tariffs and higher-carbon grids.