Development of Low-Code Platform for Electrical Power Trading using Blockchain and Artificial Intelligence

Abstract

Despite the government's encouragement of individuals to install on-grid solar panels in order to sell electricity as producers, the government still has authority over the purchasing and selling prices. For a new paradigm known as peer-to-peer (P2P) electrical energy trading, the objective of this study is to develop a low-code platform for P2P electricity auctions trading, where sellers and buyers can free to desire their prices. The blockchain technology (BT) is merged into the platform along with the artificial intelligence technology (AI) to lift up the system security and automatically determine the optimal bidding prices, respectively. The research utilized data from 20-house electricity trading auctions to train the AI model and assist in determining the most suitable electricity trading prices in the auctions. The results show that the developed platform can match the buyers and sellers who win auctions during the automated trading period obtain the best prices for electricity trading. The low-code platform significantly decreases the developing time while the BT with AI can provide the exchanged and recorded transaction data. They also enhance the security of the trading information and contributed to a higher level of security in the transactions. This research also provided insights for future development of artificial intelligence using low-code platforms, with the goal of applying it in the future.