An Optimization Approach Based on Improved Artificial Bee Colony Algorithm for Location and Capacity of Grid-Connected Photovoltaic Systems

Abstract

Access of photovoltaic system (PVS) to distribution network impacts voltage and power losses and also other related parameters. In order to make full use of the advantages of PVS and determine its optimal location and capacity, an optimal allocation's method for grid-connected PVS is proposed in this paper. This method takes the active power losses minimization as the optimization goal, divides the distribution feeder system into several paths to determine the path priority to install PVS according to active power load moment (APLM). The allowable maximum and minimum active power of grid-connected PVS for each bus are calculated via voltage sensitivity. The improved artificial bee colony (IABC) algorithm that selects initial solution by using path priority and active power restrictions of grid-connected PVS is applied to achieve the optimal allocation of PVSs. This method was examined with IEEE 33-bus feeder system, and the optimal locations and capacities for different numbers of grid-connected PVSs are determined. The results obtained by the proposed IABC algorithm were compared with the results obtained by the artificial bee colony (ABC) algorithm and particle swarm optimization and those attained via other methods. The results show that the proposed method is feasible and 1 / 3 2019 N 5 s11 effective. References 11, figures 7. tables 4.

Optimization of Load Distribution Between Distributed Generation Units of a Similar Technology Using Dynamic Programming

“…The reverse run converges quickly, since there is no consumption optimization here, but only the conditionally optimal equation P j (P e 1 ) = n, where n = 1, 2, …, obtained in the forward run is used. The optimal value of the last variable P n is determined from the dependency P n = P n P e n (6) Knowing P n , it is possible to calculate the optimal value P e n −1 = P e n − P n . Then, referring to (6), the penultimate variable P n−1 can be determined.…”

“…In paper [5], an efficient analytical (EA) technique was applied to allocate different DG units with the aim to reduce power losses in distribution power networks. An improved artificial bee colony (IABC) algorithm that selects initial solution by using path priority and real power restrictions was proposed in [6], aiming to find an optimal placement of DGs of photovoltaic (PV) nature. In article [7], advancements of an ant lion optimization algorithm (ALOA) for optimal location and sizing of DGs were introduced, and a comparison with several other methods was done.…”