TY - CHAP
T1 - Data Farming in a Smart Low Voltage Distribution System
AU - Fakude, Noah Sindile
AU - Ogudo, Kingsley A.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - The energy utility industry's evolution instigated a technological shift where the global community is moving into digital technology and where modification and changes of systems are automated and computerized. While some philosophers are convinced that we are at the exodus of the 4IR into the 5th Industrial revolution, a big question is whether the 4IR was a success or not. It is unclear to determine the successes and failures since the energy industry is divided according to the first to the third world countries and their technologies. Due to technological limitations, many studies have proven that even the 3IR has not kicked in their power grid infrastructures. Developing countries like South Africa, India, Brasil, Argentina, and more have the 4IR concept in place but are not fully functional in most areas where their power grid extends. Since the power infrastructure already exists, the main limitation is ICT infrastructure. Most parts of the power grid do not have any real-time communication infrastructure and protocols, making it difficult for utilities to procure smart devices and grid monitors if there’s no means to transmit and receive real-time information. These predicaments point to the 4IR enabler, that is, big data. There is no big data significance to harvest fundamental data. This book chapter addresses methods and ways to farm data, meaning putting entire systems in place to collect data. When data is available, it can be harvested to perform real-time tasks. Real data yields accurate information is vital for planning, simulation purposes, maintenance, and power outages computerized troubleshooting.
AB - The energy utility industry's evolution instigated a technological shift where the global community is moving into digital technology and where modification and changes of systems are automated and computerized. While some philosophers are convinced that we are at the exodus of the 4IR into the 5th Industrial revolution, a big question is whether the 4IR was a success or not. It is unclear to determine the successes and failures since the energy industry is divided according to the first to the third world countries and their technologies. Due to technological limitations, many studies have proven that even the 3IR has not kicked in their power grid infrastructures. Developing countries like South Africa, India, Brasil, Argentina, and more have the 4IR concept in place but are not fully functional in most areas where their power grid extends. Since the power infrastructure already exists, the main limitation is ICT infrastructure. Most parts of the power grid do not have any real-time communication infrastructure and protocols, making it difficult for utilities to procure smart devices and grid monitors if there’s no means to transmit and receive real-time information. These predicaments point to the 4IR enabler, that is, big data. There is no big data significance to harvest fundamental data. This book chapter addresses methods and ways to farm data, meaning putting entire systems in place to collect data. When data is available, it can be harvested to perform real-time tasks. Real data yields accurate information is vital for planning, simulation purposes, maintenance, and power outages computerized troubleshooting.
KW - 4IR
KW - Big data
KW - Data analysis
KW - IoT
KW - Power grid
KW - Smart devices
KW - Smart grid
KW - Smart sensors
UR - http://www.scopus.com/inward/record.url?scp=85172781021&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-29586-7_17
DO - 10.1007/978-3-031-29586-7_17
M3 - Chapter
AN - SCOPUS:85172781021
T3 - Studies in Systems, Decision and Control
SP - 445
EP - 469
BT - Studies in Systems, Decision and Control
PB - Springer Science and Business Media Deutschland GmbH
ER -