TY - GEN
T1 - Blockchain-based Electricity Market Agent-based Modelling&Simulation
AU - Boumaiza, Ameni
AU - Sanfilippo, Antonio
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - The use of distributed energy generation through business and residential photovoltaic (PV) applications creates new energy markets that blur the traditional line between energy providers and users. This new market dynamic results in the emergence of energy prosumers, whose role is to produce and consume energy. Blockchain technology automates direct energy exchanges within a distributed system architecture that relies on encryption hashing and general agreement verification. This technology provides prosumers, consumers, energy providers, and utilities with an affordable, safe, and unique energy-trading alternative. The Education City Community Housing (ECCH) in Qatar is the focus of this project, which aims to develop and implement an accurate Agent-Based Modeling (ABM) model and a Geographic Information System (GIS) to facilitate energy exchange in a real estate market. The ABM model simulates the spatiotemporal aspects of trading in a small market and collects and analyzes a large amount of data about daily energy usage. These simulations can help to better understand the structure of a trading market and to develop a decentralized system for trading energy. The findings of this study demonstrate that the peculiarities of transactions carried out in a community-based housing market can be easily researched using GIS data combined with an agent-based design by simply changing the settings. For large-scale simulation models with numerous stakeholders, high-performance computing will be used to improve the model's performance and to provide a scalable environment for analyzing an energy blockchain community for the technological, financial, and social sectors of Qatar.
AB - The use of distributed energy generation through business and residential photovoltaic (PV) applications creates new energy markets that blur the traditional line between energy providers and users. This new market dynamic results in the emergence of energy prosumers, whose role is to produce and consume energy. Blockchain technology automates direct energy exchanges within a distributed system architecture that relies on encryption hashing and general agreement verification. This technology provides prosumers, consumers, energy providers, and utilities with an affordable, safe, and unique energy-trading alternative. The Education City Community Housing (ECCH) in Qatar is the focus of this project, which aims to develop and implement an accurate Agent-Based Modeling (ABM) model and a Geographic Information System (GIS) to facilitate energy exchange in a real estate market. The ABM model simulates the spatiotemporal aspects of trading in a small market and collects and analyzes a large amount of data about daily energy usage. These simulations can help to better understand the structure of a trading market and to develop a decentralized system for trading energy. The findings of this study demonstrate that the peculiarities of transactions carried out in a community-based housing market can be easily researched using GIS data combined with an agent-based design by simply changing the settings. For large-scale simulation models with numerous stakeholders, high-performance computing will be used to improve the model's performance and to provide a scalable environment for analyzing an energy blockchain community for the technological, financial, and social sectors of Qatar.
KW - Agent-based modeling
KW - Blockchain
KW - Energy Trading
KW - Real-time mapping
KW - Social Simulation
KW - Spatial process
UR - http://www.scopus.com/inward/record.url?scp=85169457337&partnerID=8YFLogxK
U2 - 10.1109/IAICT59002.2023.10205894
DO - 10.1109/IAICT59002.2023.10205894
M3 - Conference contribution
AN - SCOPUS:85169457337
T3 - Proceedings of the 2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023
SP - 91
EP - 95
BT - Proceedings of the 2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology, IAICT 2023
Y2 - 13 July 2023 through 15 July 2023
ER -