| Title |
Transaction Operation Algorithm for Peer to Peer Energy Transaction between Microgrids |
| Authors |
나의균(Ui-Kyun Na) ; 김준성(Jun-Sung Kim) ; 정재성(Jae-Sung Jung) |
| DOI |
https://doi.org/10.5370/KIEE.2021.70.9.1282 |
| Keywords |
Artificial Neural Network; Distributed Resources; Electric Power Transaction; Microgrid; Peer-to-Peer |
| Abstract |
Research on microgrids for efficient use of distributed resources and renewable energy is being actively conducted. In domestic, FIT(Feed-in-Traiff) was applied to increase the penetration rate of renewable energy and distributed resources, and research is being conducted to enable efficient operation through predict of power generation, demand forecast and anomaly detection algorithm by combining with AI to improve the stability of MG operation. A electric power transaction model between MGs, like P2P(peer to peer) trading, has been proposed, but it is still incomplete. In this paper, we propose electric power transaction model between MGs. A correlation and dependence between weather elements and loads is performed and a load prediction model is proposed. In addition, we propose a transaction calculation algorithm that determines the transaction unit price for P2P energy transactions between MGs and a power transaction model which is an optimal matching algorithm for transactions between MGs where both sellers and buyers generate profits. |