Abstract
The efficiency of electrical distribution systems is being more affected by the increase in voltage drops and power losses. These issues of voltage drop and power loss can be significantly minimized by the incorporation of a Distribution Static Compensator (DSTATCOM) in the distribution network. However, inappropriate positioning and sizing of DSTATCOM can undermine its efficiency. Despite the contributions of many researchers to the optimal placement of DSTATCOM and other compensators in distribution networks, the problems of voltage drop, power losses, and power quality persist, necessitating the need for additional research in this area. In this paper, an innovative technique based on hybridized Immune and Genetic Algorithm (IA-GA) for optimal DSTATCOM placement and sizing for three distinct load levels is proposed. Simulation and analysis of the proposed algorithm were carried out using IEEE-33 bus radial distribution network (RDN) in MATLAB. The simulation results demonstrate a substantial decrease in power loss and a significant improvement in the voltage profile. Evaluation of the proposed method against existing techniques reveals that the proposed technique outperforms IA and PSO in terms of decreasing power loss and enhancement of voltage profiles. A cost-benefit analysis was performed, and it was discovered that the proposed technique yields improved annual cost savings.
Highlights
The growing power demand, high costs associated with building new grids, and environmental concerns have created unavoidable challenges such as power line overload and excessive power transmission, voltage instability, high losses, low power quality, voltage profile problems, and reliability issues
5.1 DSTATCOM Allocation and Voltage Profile Table 3 shows the results for optimal bus number, DSTATCOM optimal size as well as the yearly cost of the optimally allocated DSTATCOM
The optimal location of the DSTATCOM was found to be at bus seven (7) of the IEEE-33 bus radial distribution network (RDN) for all three load levels
Summary
The growing power demand, high costs associated with building new grids, and environmental concerns have created unavoidable challenges such as power line overload and excessive power transmission, voltage instability, high losses, low power quality, voltage profile problems, and reliability issues. In [14], Taher and Afsari adopted IA (immune algorithm) to obtain DSTATCOM’s best position and size in distribution systems in order to minimize energy cost loss, power congestion, and boost the voltage profile. For both the test systems used, IA has lower objective function values than GA at all load levels. The algorithm optimally allocates the sized DSTATCOM to the distribution network for power loss mitigation and voltage profile improvement. The optimal DSTATCOM position and size in an IEEE-33 bus RDN is obtained using the hybridization of immune and genetic algorithms (IA-GA) for three load scenarios (light, medium and peak load conditions). Where Kci is the time proportion of the ith load level and Ti is the time of the individual load level
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