Abstract
The penetration of renewable distributed generations (RDGs) into traditional distribution systems (TDSs) remedies many of its deficiencies and shortcomings. Also, it provides mutual technical, economic and environmental benefits for both electricity companies and their customers as well. With a 25% load increase for the standard IEEE 30-bus system, buses 19, 26 and 30 have the lowest voltage magnitudes among all buses. Therefore, these weak buses are selected initially to allocate RDGs. Three cases, namely, one RDG allocated, two RDGs allocated and three RDGs allocated, of RDGs insertion are covered. A novel crow search algorithm auto-drive particle swarm optimization (CSA-PSO) technique is proposed for the first time in this study to specify the optimal allocation, sizing, and number of RDGs based on the total cost and power losses minimization objectives. A new reduction percent formula is used to estimate the reduction in total cost and the total power losses. These will help us to discern between the best cases based on total cost minimization and those based on total power losses minimization to pick up the best among all best cases. In brief, RDGs allocated on buses 19 and 30 is the best among all cases based on total cost reduction and total power losses reduction. Therefore, buses 19 and 30 are recommended to allocate a wind farm and a solar photovoltaic, respectively based on technical and economic issues. Finally, the simulation findings revealed the superiority of the CSA-PSO algorithm in solving the optimal power flow problem with RDGs compared to the state-of-the-art metaheuristic techniques.
Highlights
This study proposed a novel crow search algorithm auto-drive particle swarm optimization (CSA-particle swarm optimization (PSO)) algorithm to solve the optimal power flow (OPF) problem with renewable distributed generations (RDGs) allocation at weak buses based on total cost generation minimization and total power losses minimization
RDGs allocated on weak buses 19 and 30 reduced both the total cost to lowest value (617.09 $/h) and total power losses to 2.14425 MW compared with the previous case (Case#1) and other two RDGs insertion in Case#2
A new reduction percent formula is used to evaluate the total cost reduction and the total power losses reduction. These calculations will help us to differentiate between the best cases based on total cost minimization and the best cases based on total power losses minimization so that the best RDGs case among all best cases can be identified
Summary
C. CONTRIBUTION AND PAPER ORGANIZATION On the basis of the previous literature review, this paper is counted as the first study that proposes a novel crow search algorithm auto-drive PSO (CSA-PSO) to determine the optimal allocation, sizing, and number of RDGs based on both total cost minimization and power losses minimization. A new reduction percent formula is used to evaluate the total cost reduction and the total power losses reduction These will help in discerning between all the best cases based on the total cost minimization and those based on total power losses minimization in order to pick up the eventual optimal allocation, sizing, and numbers of RDGs. The rest of this paper is organized as follow: Section 2 introduces the OPF mathematical problem formulation with RDGs. Section 3 presents the improved IEEE 30-bus power distribution system. The results are presented and discussed followed by the conclusions
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