Power Loss Minimization Using Optimal Placement and Sizing of Photovoltaic Distributed Generation Under Daily Load Consumption Profile with PSO and GA Algorithms.

The penetration of distributed generation (DG) in the distribution network has become a necessity and a significant solution to improve power grid quality, and solve power losses issue. To reach these targets, integrating these DGs in an optimal placement with an optimal sizing should be investigated and taken into consideration. This paper focuses on obtaining the optimal allocation and size of a photovoltaic (PV) distributed generation (PVDG) in order to reduce the total power losses and enhance voltage and frequency profiles of a modified IEEE 14 node distribution network (Hooshmand in J Appl Sci 8(16):2788–2800, 2008, https://doi.org/10.3923/jas.2008.2788.2800). An objective function is used in this paper aims to reduce grid power losses, and two optimization algorithms are applied to solve this function which are the particle swarm optimization (PSO) and the genetic algorithm (GA). Added to that, two scenarios are discussed in this paper in order to analyze the effects of variable PV penetration level, hourly load consumption profile variation and atmospheric condition change on the sizing optimization resolution. The obtained simulation results prove that the PSO algorithm has better performance compared to the GA in terms of speed convergence, power loss reduction and grid quality improvement (voltage and frequency profiles). Then, it shows that variable load consumption curve and weather condition change can affect not only the determination of the PVDG optimal position and capacity but also grid security. [ABSTRACT FROM AUTHOR]