Developing an Appropriate Energy Trading Algorithm and Techno-Economic Analysis between Peer-to-Peer within a Partly Independent Microgrid

• Published in: Energies (Basel) Vol. 16; no. 3; p. 1549
• Main Authors: Muntasir, Fahim, Chapagain, Anusheel, Maharjan, Kishan, Baig, Mirza Jabbar Aziz, Jamil, Mohsin, Khan, Ashraf Ali
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-02-2023
• Subjects: Algorithms; Alternative energy sources; Consumers; Cost control; Demand side management; Distributed generation; Distributed generation (Electric power); Economic analysis; Economics; Electricity; Energy consumption; Energy demand; Energy management; Energy resources; Energy sources; Energy trading; Linear programming; matchmaking algorithm; microgrid; Optimization; peer-to-peer energy trading; Peers; pricing model; Profits; self-optimization; Supply & demand; supply-demand ratio; Canada
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en16031549

The intimidating surge in the procurement of Distributed Energy Resources (DER) has increased the number of prosumers, creating a new possibility of local energy trading across the community. This project aims to formulate the peer-to-peer energy (P2P) sharing model to encourage the DERs to share surplus energy among the consumers. An effective pricing method is developed based on the supply-demand ratio (SDR) with the importance of self-optimization, which allows the prosumers to maximize their energy sharing and profits. To implement this pricing method, a simplified dynamic matchmaking algorithm has been deployed to introduce the Outstanding Prosumer to interact with existing consumers to increase the efficiency and profitability of the trade network. Consumers also benefit from this model, as they can pick the most economical energy supplier instead of relying on the utility grid. The prosumer with high excess energy and the consumer with the highest energy demand will be prioritized to maintain the SDR ratio to one or greater than one. Here, all the above-stated features of the peer-to-peer energy trading have been demonstrated with some calculations to back up some tangible results. Finally, a case study is simulated among the residents of Dhaka, Bangladesh, to demonstrate how peers can profit from participating in trading at a given time. Comparing the results with and without P2P trading, there has been a 17.54% reduction in an electric bill on a typical day of July, and a 49.53% reduction in the interaction with the grid.