Optimizing Under-voltage Load-shedding using genetic algorithm in microgrid
Astriani, Y., Shafiullah, GM.ORCID: 0000-0002-2211-184X and Shahnia, F.
ORCID: 0000-0002-8434-0525
(2019)
Optimizing Under-voltage Load-shedding using genetic algorithm in microgrid.
In: 2nd International Conference on High Voltage Engineering and Power Systems (ICHVEPS) 2019, 1 - 4 October 2019, Denpasar, Bali
*Subscription may be required
Abstract
Imbalance power in an off-grid microgrid highly affecting its voltage variation. As microgrid is usually operated in low voltage, thus, the farthest node in the microgrid will encounter the biggest voltage drop. This paper presents a load shedding scheme for restoring the under-voltage condition at the affected load bus by imitating the droop control method. Using the Newton-Raphson power flow analysis and a simple linear regression formula, the P-V droop constant for each individual load’s bus can be calculated. The amount of active and reactive power adjustment is then retrieved referring the droop gain and the desired voltage magnitude to be corrected, the amount of active and reactive power adjustment can be retrieved. Furthermore, this paper proposes an optimization algorithm to minimize the number of disconnected loads as well as fulfilling the constraint of active and reactive power to be reduced.
Item Type: | Conference Paper |
---|---|
Murdoch Affiliation(s): | School of Engineering and Information Technology |
URI: | http://researchrepository.murdoch.edu.au/id/eprint/55285 |
![]() |
Item Control Page |