主催: The Japanese Society for Artificial Intelligence
会議名: 2023年度人工知能学会全国大会(第37回)
回次: 37
開催地: 熊本城ホール+オンライン
開催日: 2023/06/06 - 2023/06/09
Electricity procurement of industrial consumers is becoming more and more complicated, involving a combination of various procurement methods, due to electricity liberalization and decarbonization trends. This study analyzed power procurement strategies for a factory to achieve carbon neutralization through a multi-agent model simulating the electricity market and introduced a factory agent using various procurement methods including PV, FC, storage batteries (SB) and DR. Firstly, we created a new procurement strategy utilizing all methods. Then, from the perspective of total cost to achieve carbon neutralization, we analyzed the effects of each procurement method, improved the DR scenario and verified it. Results showed PV had a remarkable cost reduction effect, while effect of FC increased significantly with unit cost decrease. Effect of SB and DR were not as great as PV but still considered to be effective as certain effects was confirmed. Finally, we created a DR scenario incorporating the operation of PV, as it is considered to be necessary based on the results. Through experiment, the new scenario was confirmed to be effective in cost-effectiveness for decarbonization.