Blockchains for Transactive Energy Systems: Opportunities, Challenges, and Approaches
September 2020·,,,
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Scott Eisele
Carlos Barreto
Abhishek Dubey
Xenofon Koutsoukos
Taha Eghtesad
Aron Laszka
Anastasia Mavridou
Abstract
The emergence of blockchains and smart contracts have renewed interest in electrical cyber-physical systems, especially in the area of transactive energy systems. However, despite recent advances, there remain significant challenges that impede the practical adoption of blockchains in transactive energy systems, which include implementing complex market mechanisms in smart contracts, ensuring safety of the power system, and protecting residential consumers’ privacy. To address these challenges, we present TRANSAX, a blockchain-based transactive energy system that provides an efficient, safe, and privacy-preserving market built on smart contracts. Implementation and deployment of TRANSAX in a verifiably correct and efficient way is based on VeriSolid, a framework for the correct-by-construction development of smart contracts, and RIAPS, a middleware for resilient distributed power systems.
Type
Venue
IEEE Computer, 53(9), 66–76
Authors
Ph.D. 2026
Taha Eghtesad joined the Applied Artificial Intelligence Lab as a Ph.D. student in Fall 2018 and received his Ph.D.
in 2026 under the supervision of Dr. Aron Laszka. He received a B.S. degree in Computer Engineering, with a minor in
Software Engineering, from Shahid Beheshti University, Tehran, Iran. His research lies at the intersection of
machine learning, game theory, cyber-physical systems, and systems security. In particular, his Ph.D. research
focused on using artificial intelligence and machine learning to make cyber-physical systems more secure.
Associate Professor
Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.
His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.
His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.