Last year, a group of researchers from Western Australia wrote a paper about the increasing amount of solar generated rooftops and the idea of using blockchain technology for energy trading. Peer-to-Peer energy trading is the focus of this peer reviewed research paper that ultimately proposes a blockchain scalability solution (Pornpit Wongthongtham, 2021).
They reported that Peer-to-Peer (P2P) trading of energy has emerged as a next generation system in energy management that enables prosumers, who are consumers who produce their own solar energy, to trade their surplus energy. This would create opportunities for power system markets and would transform the way consumers use their energy, allowing them to trade energy with their peers. P2P electricity markets may allow consumers to freely choose their source of electric energy by, for instance, investing in locally produced renewable energy (Pornpit Wongthongtham, 2021).
They say that the adoption of blockchain technology for P2P electricity enables a transition from a highly centralized market controlled by a few key players to a more democratic decentralized market dominated by microgrids. The primary focus of this paper is the “blockchain trilemma” of scalability, security, and decentralization in P2P energy trading, through a trial occurring in Western Australia (Pornpit Wongthongtham, 2021). They include models of blockchain-based energy trading and all intermediary steps that are involved. They propose a P2P blockchain solution based on a case study. Then they lay out what future work is envisioned to get consumers and “prosumers” on the same page in order to create this new market.
Works Cited
Pornpit Wongthongtham, D. M.-S. (2021). Blockchain-enabled Peer-to-Peer energy trading. Computers & Electrical Engineering, Volume 94, 107299 ISSN 0045-7906.
Article Authors
Pornpit Wongthongtham received the B.Sc. degree in Mathematics, the M.Sc. degree in Computer Science, and the Ph.D degree in Information Systems. She is the senior research fellow at University of Western Australia. Her research interests include Data Science, Artificial Intelligence, Information Systems, and the like.
Daniel Marrable is a lead data scientist at Curtin Institute for Computation at Curtin University. He has a PhD in remote sensing. He is very passionate about and experienced in both satellite remote sensing and data analysis. Dan has gained much experience processing very large data sets as well as coding complex light models on a variety of platforms such as cloud infrastructure, supercomputers and GPUs.
Bilal Abu-Salih is an Assistant Professor at the University of Jordan. He holds a Ph.D. in Information Systems. He worked with various cross-disciplinary funded research projects which are related to data analytics, machine learning, data mining of social media, Big data analytics, and the like. Bilal’s research interests include; Knowledge Graphs and Machine Learning/Data Mining.
Xin Liu is a principal researcher at Huawei and an adjunct research fellow at the Curtin University Sustainability Policy (CUSP), Curtin University. His research interests are data science and spatial science.
Greg Morrison is the professor in sustainable cities at Curtin University. Greg has successfully initiated and run large scale societal infrastructure related projects, with the most recent being a smart cities energy and water peer to peer trading project in Fremantle.
Comments
Post a Comment