TY - GEN
T1 - Uncertainty mitigation in feeder level power loss reduction with distributed generation
AU - Manoharan, Arun Kaarthick
AU - Hettiarachchige-Don, Anton
AU - Aravinthan, Visvakumar
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7/22
Y1 - 2019/7/22
N2 - The grid is moving towards a system of decentralized distributed generation using a large number of small scale renewable generation resources. These resources are stochastic in nature and therefore have to be continuously monitored and controlled for better system operation. This calls for an Information and Communication Technology (ICT) infrastructure that is able to provide continuous generation and load data. However, losses in communication is always possible. The work in this paper tries to come up with a DG control scheme that makes it possible for the system to make meaningful decisions even during communication losses. Proposed here is a feeder level loss minimization control scheme that uses a possibilistic approach to come up with DG set points in the absence of continuous system data.
AB - The grid is moving towards a system of decentralized distributed generation using a large number of small scale renewable generation resources. These resources are stochastic in nature and therefore have to be continuously monitored and controlled for better system operation. This calls for an Information and Communication Technology (ICT) infrastructure that is able to provide continuous generation and load data. However, losses in communication is always possible. The work in this paper tries to come up with a DG control scheme that makes it possible for the system to make meaningful decisions even during communication losses. Proposed here is a feeder level loss minimization control scheme that uses a possibilistic approach to come up with DG set points in the absence of continuous system data.
KW - Distribution Generation
KW - fuzzy optimization
KW - power loss reduction
KW - Smart Grid
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85069930334&partnerID=8YFLogxK
U2 - 10.1109/GreenTech.2019.8767121
DO - 10.1109/GreenTech.2019.8767121
M3 - Conference contribution
AN - SCOPUS:85069930334
SN - 9781728114583
T3 - IEEE Green Technologies Conference
BT - 2019 IEEE Green Technologies Conference, GreenTech 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Green Technologies Conference, GreenTech 2019
Y2 - 3 April 2019 through 6 April 2019
ER -