Improvement of PV unit hosting capacity and voltage profile in distorted radial distribution systems via optimal sizing and placement of passive filters

In the forthcoming decades, significant advancements will shape the construction and operations of distribution systems. Particularly, the increasing prominence of photovoltaic (PV) systems in the power industry will impact the security of these systems. This study employs Monte Carlo Simulation (MCS) in conjunction with genetic algorithm (GA) and differential evolution (DE) to address uncertainties. The probability density functions (pdf) for total voltage harmonic distortion (UTHD), individual voltage harmonic distortion (UIHDh), and RMS voltage (URMS) have been determined for utilization in chance constrained framework. In addition, the uncertainty effects of PV systems on grid losses for various solar radiation conditions are also investigated. Specifically, the paper aims to evaluate these impacts within the context of stochastic limits. The PV system sizing problem has been addressed inside the distribution system using a chance-constrained framework. A key contribution is the integration of GA, DE, and MCS into a cohesive approach, and the study evaluates the benefits of this approach through an analysis of outcomes derived from the stochastic method. The simulation results illustrate the advantages of the proposed stochastic GA methodology.

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Improvement of PV unit hosting capacity and voltage profile in distorted radial distribution systems via optimal sizing and placement of passive filters

Cited by 2 publications

References 30 publications

Applicability boundary calculation for directional current protection in distribution networks with accessed PV power sources

Applicability boundary calculation for directional current protection in distribution networks with accessed PV power sources

Investigations on solar PV integration and associated power quality challenges in distribution systems through the application of MCS and GA

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