TY - GEN
T1 - Blockchain-based Electricity Marketplace
AU - Boumaiza, Ameni
AU - Sanfilippo, Antonio
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The concept of "energy prosumer"is a relatively new phenomenon resulting from distributed energy production through photovoltaic (PV) technology, which has blurred the line between energy producers and consumers. Blockchain technology has facilitated secure and cost-effective energy transactions among consumers, prosumers, and utilities, automating the process. This study aims to develop an agent-based modeling (ABM) simulation framework for energy exchange, demonstrating the power profiles of households and the operation of blockchain operations. The simulation was conducted in the Education City Community Housing (ECCH) microgrid, using a multi-agent framework for a transactive energy (TE) distributed energy resource (DER) that requires blockchain technology. The current blockchain-based local energy market (LEM) aims to balance supply and demand using precise short-term energy generation forecasts and home consumption estimates. This study evaluated the accuracy of state-of-the-art energy forecasting methods in predicting household energy generation and consumption. It examined the impact of forecasting errors on market outcomes under different supply scenarios. Although LSTM models may provide low forecasting errors, the researchers found that the prediction process needs modification for a LEM built on a blockchain. This study stands out from previous research by forecasting the timeline of smart meters in general.
AB - The concept of "energy prosumer"is a relatively new phenomenon resulting from distributed energy production through photovoltaic (PV) technology, which has blurred the line between energy producers and consumers. Blockchain technology has facilitated secure and cost-effective energy transactions among consumers, prosumers, and utilities, automating the process. This study aims to develop an agent-based modeling (ABM) simulation framework for energy exchange, demonstrating the power profiles of households and the operation of blockchain operations. The simulation was conducted in the Education City Community Housing (ECCH) microgrid, using a multi-agent framework for a transactive energy (TE) distributed energy resource (DER) that requires blockchain technology. The current blockchain-based local energy market (LEM) aims to balance supply and demand using precise short-term energy generation forecasts and home consumption estimates. This study evaluated the accuracy of state-of-the-art energy forecasting methods in predicting household energy generation and consumption. It examined the impact of forecasting errors on market outcomes under different supply scenarios. Although LSTM models may provide low forecasting errors, the researchers found that the prediction process needs modification for a LEM built on a blockchain. This study stands out from previous research by forecasting the timeline of smart meters in general.
KW - Blockchain
KW - long-term memory (LSTM)
KW - market mechanism
KW - market simulation
KW - short-term energy forecasting
UR - http://www.scopus.com/inward/record.url?scp=85174064839&partnerID=8YFLogxK
U2 - 10.1109/ICECCME57830.2023.10252228
DO - 10.1109/ICECCME57830.2023.10252228
M3 - Conference contribution
AN - SCOPUS:85174064839
T3 - International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2023
BT - International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 International Conference on Electrical, Computer, Communications and Mechatronics Engineering, ICECCME 2023
Y2 - 19 July 2023 through 21 July 2023
ER -