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Analysis of Demand Response Scenarios by Large Consumers Using an Electricity Market Model [in Japanese]

Ryo WAKASUGI, Kiyoshi IZUMI, Masanori HIRANO

The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence, Mar. 12, 2022


Conference

The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence (SIG-FIN)

Abstract

In addition to the need for electricity consumers to take into account the complex behavior of the electricity market as a result of electricity deregulation, CO2 emissions from economic activities have also become an issue in response to recent calls for decarbonization, making the electricity procurement environment increasingly complex. In this study, we focus on electricity procurement by a factory as a large consumer in such a complicated electricity sector. We have conducted simulation experiments and evaluations using an electricity market multi-agent model for several scenarios, focusing on the benefits to the demand side of demand response (DR), which is attracting attention as a means of stabilizing supply and demand in the electricity system, in terms of cost and CO2 emission reduction effects. The results show the effectiveness of DR that takes into account the characteristics of the season and time of day, and the effectiveness of demand shifting that utilizes out-of-service hours.

Keywords

事前学習モデル; 追加事前学習; 自然言語処理; BERT; ELECTRA;


Paper

PDF, Official page


bibtex

@inproceedings{Wakasugi2022-sigfin28,
  title={{Analysis of Demand Response Scenarios by Large Consumers Using an Electricity Market Model [in Japanese]}},
  autor={Ryo WAKASUGI and Kiyoshi IZUMI and Masanori HIRANO},
  booktitle={The 28th meeting of Special Interest Group on Financial Informatics of Japanese Society for Artificial Intelligence},
  pages={19-24},
  url={https://sigfin.org/?028-04},
  year={2022}
}