TY - GEN
T1 - Blockchain-Enabled Energy Marketplace
AU - Boumaiza, Ameni
AU - Sanfilippo, Antonio
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The growth of decentralized energy production, especially through solar PV systems in homes and businesses, has introduced the concept of an 'energy prosumer.' This term combines the roles of energy producers and consumers, challenging traditional categorizations. The key factor in this transformation is blockchain technology. By utilizing its encrypted database structure built on consensus, blockchain provides a novel solution for direct energy trading. It serves a wide range of users, including everyday consumers and prosumers, as well as larger energy suppliers and utility companies, ensuring secure and cost-effective energy transactions. This research aims to introduce and apply an Agent-Based Model (ABM) that simulates electricity trade. The goal is to predict household power consumption patterns and validate blockchain procedures. A specially designed multi-agent system, specifically created for Transactive Energy (TE) in Distributed Energy Resources (DER), was developed and tested within the ECCH microgrid, relying on blockchain principles. Emerging concepts like blockchain-driven Local Energy Markets (LEM) suggest the use of auction mechanisms to balance future energy supply and demand. These models require accurate short-term predictions of individual household energy generation and usage. This study focuses on improving the accuracy of household energy forecasts using advanced techniques. It also examines the impact of prediction errors across three different supply scenarios. This research significantly diverges from previous studies that mainly tracked smart meter timelines.
AB - The growth of decentralized energy production, especially through solar PV systems in homes and businesses, has introduced the concept of an 'energy prosumer.' This term combines the roles of energy producers and consumers, challenging traditional categorizations. The key factor in this transformation is blockchain technology. By utilizing its encrypted database structure built on consensus, blockchain provides a novel solution for direct energy trading. It serves a wide range of users, including everyday consumers and prosumers, as well as larger energy suppliers and utility companies, ensuring secure and cost-effective energy transactions. This research aims to introduce and apply an Agent-Based Model (ABM) that simulates electricity trade. The goal is to predict household power consumption patterns and validate blockchain procedures. A specially designed multi-agent system, specifically created for Transactive Energy (TE) in Distributed Energy Resources (DER), was developed and tested within the ECCH microgrid, relying on blockchain principles. Emerging concepts like blockchain-driven Local Energy Markets (LEM) suggest the use of auction mechanisms to balance future energy supply and demand. These models require accurate short-term predictions of individual household energy generation and usage. This study focuses on improving the accuracy of household energy forecasts using advanced techniques. It also examines the impact of prediction errors across three different supply scenarios. This research significantly diverges from previous studies that mainly tracked smart meter timelines.
KW - AI
KW - Agent Based Modelling
KW - Simulation
KW - Solar Energy Trading
KW - Transactive Grid
UR - http://www.scopus.com/inward/record.url?scp=85179513029&partnerID=8YFLogxK
U2 - 10.1109/IECON51785.2023.10312584
DO - 10.1109/IECON51785.2023.10312584
M3 - Conference contribution
AN - SCOPUS:85179513029
T3 - IECON Proceedings (Industrial Electronics Conference)
BT - IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
PB - IEEE Computer Society
T2 - 49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
Y2 - 16 October 2023 through 19 October 2023
ER -