A new emperor penguin optimisation‐based approach for solar photovoltaic parameter estimation

Chauhan, Abhishek; Prakash, Surya

doi:10.1002/2050-7038.12917

Cited by 15 publications

(18 citation statements)

References 48 publications

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“…However, the analytical methods are simple, but the effectiveness of these methods is greatly dependent on approximations, assumptions, and pre‐information, for example, the slope of different points in the I‐V or P‐V curve 17,18 . In most of the analytical methods, either the value of ideality factor ( A ) and R s are pre‐fixed, or R s and R p were ignored 7,19‐23 . Indeed, these parameters affect the I‐V curve significantly at the maximum power point (MPP).…”

Section: Introductionmentioning

confidence: 99%

“…All these five‐ unknown parameters are equally important and influence the shape of I‐V and P‐V curves of solar PV. Hence none of any unknown parameters can be ignored for accurate assessment of solar PV characteristics 21‐25 …”

Section: Introductionmentioning

confidence: 99%

“…Recently, several hybrid methods have also been developed in the researches to overcome the issues existing due to large numbers of unknown model parameters 22‐24 . In these hybrid methods, either two or three unknown parameters are achieved through some optimization techniques, and the remaining parameters are either through numerical or analytical techniques.…”

Section: Introductionmentioning

confidence: 99%

“…In these hybrid methods, either two or three unknown parameters are achieved through some optimization techniques, and the remaining parameters are either through numerical or analytical techniques. For instance, in Reference 22, firstly, I pv and I s are estimated analytically, and then, by using these values of current, an objective function has been developed in terms of R s , R p , and A . Finally, the developed objective function is minimized through Emperor Penguin Optimization (EPO) to estimate the values of R s , R p , and A .…”

Section: Introductionmentioning

confidence: 99%

“…Finally, the developed objective function is minimized through Emperor Penguin Optimization (EPO) to estimate the values of R s , R p , and A . The method presented in Reference 22 is based on the assumption that under STC the value of I pv will be equal to I sc . In, strictly speaking, the value of I pv will not be equal to I sc under STC.…”

Section: Introductionmentioning

confidence: 99%

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A novel hybrid parameter estimation technique of solarPV

Rawat

Thakur

Singh

2021

Intl J of Energy Research

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Summary This paper develops a novel hybrid parameter estimation technique of the solar photovoltaic (PV) cell. First, a mathematical model of the solar PV cell, which is a function of three unknown parameters, namely, series resistance, shunt resistance, and thermal voltage, is developed. Then, trust‐region algorithms are used to evaluate these three unknown parameters. The accuracy and efficacy of the proposed technique are tested with five different PV modules of mono‐ and poly‐crystalline materials by estimating their various benchmarks, such as relative maximum power error (RMPE), root mean square error (RMSE) and mean absolute error (MAE) of the current. In addition, the results of the proposed technique are compared with the experimental as well as the results obtained from other established techniques. The %RMSE, as obtained with the proposed technique, is found in order of 10−4 while the other techniques provide the value in the range between 10−1 and 10−3. Similarly, %MAE and %RMSE, as obtained with the proposed technique, are found 0.064 and 0.17, respectively, which is smaller than the other existing techniques. Hence, the proposed hybrid technique provides characteristics that are almost similar to the real characteristics of solar PV. Highlights The characteristic equation is developed in terms of Rs, Rp, and Vth. The hybrid technique is used to evaluate five unknown parameters of solar PV. Various performance indicators have been estimated for different types of solar PV. Characteristics obtained with the proposed technique are similar to real characteristics. The proposed technique reduces the complexity of parameter estimations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A novel hybrid parameter estimation technique of solarPV

Rawat

Thakur

Singh

2021

Intl J of Energy Research

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Parameter extraction of solarPVcell models using novel metaheuristic chaotic tunicate swarm algorithm

Gupta

Nijhawan

Ganguli

2021

Int Trans Electr Energ Syst

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The photovoltaic(PV) system's efficiency can be improved with the aid of effective solar PV cell modeling. However, flawed solar cell parameters affect PV cell modeling incorrectly. The manufacturers are usually not providing all the necessary data for the exact modeling of PV cells. It is therefore necessary to efficiently predict the parameters of the PV cell. The literature discusses various optimization algorithms, but the suboptimal outcomes are obtained by most of the algorithms due to their convergence toward local minima. This paper introduces a new stochastic optimization algorithm for the estimation of solar PV cell parameters. Therefore, for the evaluation of the solar cell, a new novel chaotic algorithm is introduced in this paper called the chaotic tunicate swarm algorithm (CTSA). The proposed algorithm has a new function called an outstanding mathematical model of adaptive weights to stimulate negative and positive inputs from the spreading wave in order to find the best way to connect food with an excellent exploitation tendency and exploratory ability. For the double-diode model, the computation time of the chaotic variants (CTSA1-1.1885, CTSA2-1.2502, CTSA3-1.2962, CTSA4-1.1204, and CTSA5-1.2214) is better than the rest of the compared algorithms (particle swarm optimization [PSO]-17.4532, tunicate swarm algorithm (TSA)-2.5278, Harris hawks optimization [HHO]-10.8942, ant lion optimizer [ALO]-15.0214, and atom search optimization [ASO]-9.5214). For the triple-diode model, the computation time of the chaotic variants (CTSA1-1.2658, CTSA2-1.3520, CTSA3-1.3056, CTSA4-1.2290, and CTSA5-1.3859) is better than the rest of the compared algorithms (PSO-18.5421, TSA-3.2568, HHO-9.8754, ALO-13.5841, and ASO-List of Symbols and Abbreviations: α 1 , ideality factor for first diode.; α 2 , ideality factor for second diode; α 3 , ideality factor for third diode; B !

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A novel black widow optimization approach to improve the precision in parameter estimation problem of solar photovoltaic electrical model

Chauhan

Prakash

2022

Env Prog and Sustain Energy

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Mathematical modeling of solar photovoltaic (PV) cell/module or array is to assess its unknown modeling parameters with the experimental current-voltage (I-V) characteristic or from the manufacturer's datasheet, where exploitation of implicit and precise solution is a stern concern among researchers for the designing of an optimized solar PV system. Hence, in this article, a robust pheromone value black widow optimization (pv-BWO) algorithm is proposed to estimate precise modeling parameters of equivalent solar PV single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM). The proposed algorithm is well investigated in coordination with three case studies that hold polycrystalline and monocrystalline PV modules. The suggested technique is validated through the analysis of I-V and power-voltage (P-V) performance characteristics that are meticulously analyzed under various environmental constraints. The first two case studies are widely investigated in the literature also, whereas, to affirm the suitability of pv-BWO under real implementation the third case study is carried out in an experimental environment. Furthermore, the pv-BWO method for the aforesaid case studies are validated and compared with the experimental data along with various well-established parameter estimation techniques in literature, where the proposed method promises a more reliable, stable, and precise solution for the parameter estimation problem.

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A new emperor penguin optimisation‐based approach for solar photovoltaic parameter estimation

Cited by 15 publications

References 48 publications

A novel hybrid parameter estimation technique of solarPV

A novel hybrid parameter estimation technique of solarPV

Parameter extraction of solarPVcell models using novel metaheuristic chaotic tunicate swarm algorithm

A novel black widow optimization approach to improve the precision in parameter estimation problem of solar photovoltaic electrical model

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