Parameter estimation of solar cells and modules using an improved adaptive differential evolution algorithm
TL;DR: The proposed IADE algorithm provides better performance for estimation of the solar cell and module parameter values than other popular optimization methods such as particle swarm optimization, genetic algorithm, conventional DE, simulated annealing (SA), and a recently proposed analytical method.
About: This article is published in Applied Energy.The article was published on 2013-12-01. It has received 237 citations till now. The article focuses on the topics: Meta-optimization & Differential evolution.
Citations
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TL;DR: The Chaotic Whale Optimization Algorithm (CWOA) is proposed, using the chaotic maps to compute and automatically adapt the internal parameters of the optimization algorithm for the parameters estimation of solar cells.
465 citations
TL;DR: In this paper, the existing research works on PV cell model parameter estimation problem are classified into three categories and the research works of those categories are reviewed based on the conducted review, some recommendations for future research are provided.
Abstract: The contribution of solar photovoltaics (PV׳s) in generation of electric power is continually increasing. PV cells are commonly modelled as circuits. Finding appropriate circuit model parameters of PV cells is crucial for performance evaluation, control, efficiency computations and maximum power point tracking of solar PV systems. The problem of finding circuit model parameters of solar PV cells is referred to as “PV cell model parameter estimation problem,” and is highly attracted by researchers. In this paper, the existing research works on PV cell model parameter estimation problem are classified into three categories and the research works of those categories are reviewed. Based on the conducted review, some recommendations for future research are provided.
419 citations
TL;DR: The ABC (artificial bee colony) algorithm is proposed, an evolutionary method inspired by the intelligent foraging behavior of honey bees, which exhibits a better search capacity to face multi-modal objective functions in comparison with other evolutionary algorithms.
353 citations
TL;DR: An improved JAYA (IJAYA) optimization algorithm is proposed in the paper, which can obtain a highly competitive performance compared with other state-of-the-state algorithms, especially in terms of accuracy and reliability.
353 citations
TL;DR: In this paper, an application of pattern search optimization technique for extracting the parameters of different solar cell models is presented, where the solar cell parameters estimation is viewed and formulated as a multivariate nonlinear optimization problem.
322 citations
References
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TL;DR: In this article, a new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented, which requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
Abstract: A new heuristic approach for minimizing possibly nonlinear and non-differentiable continuous space functions is presented. By means of an extensive testbed it is demonstrated that the new method converges faster and with more certainty than many other acclaimed global optimization methods. The new method requires few control variables, is robust, easy to use, and lends itself very well to parallel computation.
24,053 citations
TL;DR: The many different techniques for maximum power point tracking of photovoltaic (PV) arrays are discussed in this paper, and at least 19 distinct methods have been introduced in the literature, with many variations on implementation.
Abstract: The many different techniques for maximum power point tracking of photovoltaic (PV) arrays are discussed. The techniques are taken from the literature dating back to the earliest methods. It is shown that at least 19 distinct methods have been introduced in the literature, with many variations on implementation. This paper should serve as a convenient reference for future work in PV power generation.
5,022 citations
"Parameter estimation of solar cells..." refers background in this paper
...Many strategies have been proposed to improve the efficiency of the solar energy systems, such as: using different composite materials [1], creating effective solar cell structures [2], designing more efficient maximum power point tracking (MPPT) and electrical converters for power harvesting [2–7], and new architectures for photovoltaic (PV) arrays [4,8]....
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TL;DR: In this article, the authors proposed a method of modeling and simulation of photovoltaic arrays by adjusting the curve at three points: open circuit, maximum power, and short circuit.
Abstract: This paper proposes a method of modeling and simulation of photovoltaic arrays. The main objective is to find the parameters of the nonlinear I-V equation by adjusting the curve at three points: open circuit, maximum power, and short circuit. Given these three points, which are provided by all commercial array data sheets, the method finds the best I-V equation for the single-diode photovoltaic (PV) model including the effect of the series and parallel resistances, and warranties that the maximum power of the model matches with the maximum power of the real array. With the parameters of the adjusted I-V equation, one can build a PV circuit model with any circuit simulator by using basic math blocks. The modeling method and the proposed circuit model are useful for power electronics designers who need a simple, fast, accurate, and easy-to-use modeling method for using in simulations of PV systems. In the first pages, the reader will find a tutorial on PV devices and will understand the parameters that compose the single-diode PV model. The modeling method is then introduced and presented in details. The model is validated with experimental data of commercial PV arrays.
3,811 citations
"Parameter estimation of solar cells..." refers background in this paper
...The single diode lumped parameter equivalent electrical circuit of solar cell is described as [26]:...
[...]
TL;DR: The results show that the algorithm with self-adaptive control parameter settings is better than, or at least comparable to, the standard DE algorithm and evolutionary algorithms from literature when considering the quality of the solutions obtained.
Abstract: We describe an efficient technique for adapting control parameter settings associated with differential evolution (DE). The DE algorithm has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters, which are kept fixed throughout the entire evolutionary process. However, it is not an easy task to properly set control parameters in DE. We present an algorithm-a new version of the DE algorithm-for obtaining self-adaptive control parameter settings that show good performance on numerical benchmark problems. The results show that our algorithm with self-adaptive control parameter settings is better than, or at least comparable to, the standard DE algorithm and evolutionary algorithms from literature when considering the quality of the solutions obtained
2,820 citations
"Parameter estimation of solar cells..." refers methods in this paper
...Popular adaptive DEs include SaDE [31], FADE [32], jDE [33], JADE [34], EPSDE [35], and CoDE [36], etc....
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...In [33], Brest et al....
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TL;DR: Simulation results show that JADE is better than, or at least comparable to, other classic or adaptive DE algorithms, the canonical particle swarm optimization, and other evolutionary algorithms from the literature in terms of convergence performance for a set of 20 benchmark problems.
Abstract: A new differential evolution (DE) algorithm, JADE, is proposed to improve optimization performance by implementing a new mutation strategy ldquoDE/current-to-p bestrdquo with optional external archive and updating control parameters in an adaptive manner. The DE/current-to-pbest is a generalization of the classic ldquoDE/current-to-best,rdquo while the optional archive operation utilizes historical data to provide information of progress direction. Both operations diversify the population and improve the convergence performance. The parameter adaptation automatically updates the control parameters to appropriate values and avoids a user's prior knowledge of the relationship between the parameter settings and the characteristics of optimization problems. It is thus helpful to improve the robustness of the algorithm. Simulation results show that JADE is better than, or at least comparable to, other classic or adaptive DE algorithms, the canonical particle swarm optimization, and other evolutionary algorithms from the literature in terms of convergence performance for a set of 20 benchmark problems. JADE with an external archive shows promising results for relatively high dimensional problems. In addition, it clearly shows that there is no fixed control parameter setting suitable for various problems or even at different optimization stages of a single problem.
2,778 citations
"Parameter estimation of solar cells..." refers methods in this paper
...Popular adaptive DEs include SaDE [31], FADE [32], jDE [33], JADE [34], EPSDE [35], and CoDE [36], etc....
[...]
...In [34], Zhang et al....
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