TY - GEN
T1 - Optimal allocation of multi-type distributed generators for minimization of power losses in distribution systems
AU - Ahmadi, Bahman
PY - 2019
Y1 - 2019
N2 - Distributed generation (DG), including photovoltaics (PVs), wind turbines (WTs) are becoming vital for Active Distribution Networks (ADN). Therefore, optimal sizing and allocation of these units can improve voltage profiles and reduce active power losses. This study concentrates on optimal allocation and sizing of two kinds of DG units (PVs and WTs) with 1 MW maximum size limits, due to the regulations in Turkey. The Whale optimization algorithm (WOA) and Grey wolf optimization algorithm (GWO) are used as optimization tools to minimize active power losses of 33 and 69 Bus Test Systems. The performance analysis of the methods are performed through simulations and the numerical results are compared in terms of optimal OF values and convergence characteristics.
AB - Distributed generation (DG), including photovoltaics (PVs), wind turbines (WTs) are becoming vital for Active Distribution Networks (ADN). Therefore, optimal sizing and allocation of these units can improve voltage profiles and reduce active power losses. This study concentrates on optimal allocation and sizing of two kinds of DG units (PVs and WTs) with 1 MW maximum size limits, due to the regulations in Turkey. The Whale optimization algorithm (WOA) and Grey wolf optimization algorithm (GWO) are used as optimization tools to minimize active power losses of 33 and 69 Bus Test Systems. The performance analysis of the methods are performed through simulations and the numerical results are compared in terms of optimal OF values and convergence characteristics.
UR - http://www.scopus.com/inward/record.url?scp=85084295485&partnerID=8YFLogxK
U2 - 10.1109/isap48318.2019.9065974
DO - 10.1109/isap48318.2019.9065974
M3 - Conference contribution
SN - 9781728131924
T3 - 2019 20th International Conference on Intelligent System Application to Power Systems, ISAP 2019
BT - 2019 20th International Conference on Intelligent System Application to Power Systems, ISAP 2019
ER -