Hybrid Approach Based on GA and PSO for Parameter Estimation of a Full Power Quality Disturbance Parameterized Model

Rodriguez-Guerrero, Marco Antonio; Jaen-Cuéllar, Arturo Yosimar; Carranza-Lopez-Padilla, Rene D.; Osornio-Ríos, Roque Alfredo; Herrera-Ruíz, Gilberto; Romero-Troncoso, René de Jesús

doi:10.1109/tii.2017.2743762

Cited by 52 publications

(19 citation statements)

References 33 publications

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“…In fact, the PSO as a metaheuristic approach is used to optimise a function that is difficult to express analytically. In PSO, the global position is searched by a number of agents (particles) with a continually updated velocity [29]. As shown in Fig.…”

Section: Proposed Methodology For Creating Models Of Snow‐covered Pmentioning

confidence: 99%

Particle swarm optimisation‐based model and analysis of photovoltaic module characteristics in snowy conditions

Khenar¹,

Hosseini²,

Taheri³

et al. 2019

IET Renewable Power Generation

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In this paper, a novel methodology of PV modeling is proposed to represent the instantaneous electrical characteristics of PV modules covered with snow. The attenuation of the transmitted solar radiation penetrating a layer of snow is rigorously estimated based on the Giddings and LaChapelle theory. This theory introduced the level of radiation that reaches the surface of PV module through snowpack, significantly affected by the snow properties and thickness. The proposed modeling approach is based on the single-diode-five-parameter equivalent circuit model. The parameters of the model are updated through instantaneous measurements of voltage and current that are optimized by the particle swarm optimization algorithm. The proposed approach for modeling snow-covered PV modules was successfully validated in outdoor tests using three different types of PV module technologies typically used in North America's PV farms under different cold weather conditions. In addition, the validity of the proposed model was investigated using real data obtained from the SCADA system of a 12-MW grid-connected PV farm. The proposed model can help improving PV performance under snow conditions and can be considered a powerful tool for the design and selection of PV modules subjected to snow accretion.

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Section: Proposed Methodology For Creating Models Of Snow‐covered Pmentioning

confidence: 99%

Particle swarm optimisation‐based model and analysis of photovoltaic module characteristics in snowy conditions

Khenar¹,

Hosseini²,

Taheri³

et al. 2019

IET Renewable Power Generation

View full text Add to dashboard Cite

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“…This method is used as an optimization technique for search problems and provides a good solution for power system application. It is also used as a population-based optimization approach and proved as a powerful tool for classifying the PQDs in the dynamic environment of the power system [140]. The multiple combinations of this technique help to select the best features for classification of power quality disturbances.…”

Section: A: Genetic Algorithm-based Optimization Techniquesmentioning

confidence: 99%

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

et al. 2020

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The global concern with power quality is increasing due to the penetration of renewable energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power quality (PQ) disturbances are found to be more predominant with RE penetration due to the variable outputs and interfacing converters. There is a need to recognize and mitigate PQ disturbances to supply clean power to the consumer. This paper presents a critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration. The broad perspective of this review paper is to provide various concepts utilized for extraction of the features to detect and classify the PQ disturbances even in the noisy environment. More than 220 research publications have been critically reviewed, classified and listed for quick reference of the engineers, scientists and academicians working in the power quality area.

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“…For instance, GA keep a population of potential solutions, whereas other techniques work with a single variable. Another benefit is their concept simplicity and their easiness of implementation [29]. GA are a set of elements based on Darwin's theory of survival of the fittest.…”

Section: Evolutionary-based Algorithmmentioning

confidence: 99%

Genetic Algorithm Methodology for the Estimation of Generated Power and Harmonic Content in Photovoltaic Generation

et al. 2020

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Renewable generation sources like photovoltaic plants are weather dependent and it is hard to predict their behavior. This work proposes a methodology for obtaining a parameterized model that estimates the generated power in a photovoltaic generation system. The proposed methodology uses a genetic algorithm to obtain the mathematical model that best fits the behavior of the generated power through the day. Additionally, using the same methodology, a mathematical model is developed for harmonic distortion estimation that allows one to predict the produced power and its quality. Experimentation is performed using real signals from a photovoltaic system. Eight days from different seasons of the year are selected considering different irradiance conditions to assess the performance of the methodology under different environmental and electrical conditions. The proposed methodology is compared with an artificial neural network, with the results showing an improved performance when using the genetic algorithm methodology.

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Hybrid Approach Based on GA and PSO for Parameter Estimation of a Full Power Quality Disturbance Parameterized Model

Cited by 52 publications

References 33 publications

Particle swarm optimisation‐based model and analysis of photovoltaic module characteristics in snowy conditions

Particle swarm optimisation‐based model and analysis of photovoltaic module characteristics in snowy conditions

Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration

Genetic Algorithm Methodology for the Estimation of Generated Power and Harmonic Content in Photovoltaic Generation

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