Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation

Soon, Tey Kok; Mekhilef, Saad; Seyedmahmoudian, Mehdi; Horan, Ben; Oo, Amanullah Than; Stojcevski, Alex

doi:10.1109/tii.2018.2793210

Cited by 249 publications

(108 citation statements)

References 22 publications

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“…if the fitness of the trial vector f(U) is less than or equal to the target vector f(X), the trial vector will replace the target vector into the next generation, otherwise, the target vector will remain unchanged [25][26][27].…”

Section: Selectionmentioning

confidence: 99%

Maximum Power Point Tracking Technology of Photovoltaic Array under Partial Shading Based On Adaptive Improved Differential Evolution Algorithm

Zhang

Sui

2020

Energies

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In the case of partial shading conditions, there will be more than one maximum power point (MPP) in photovoltaic (PV) array. The traditional maximum power point tracking (MPPT) methods are easy to get in the local maximum power point (LMPP) and fail. Based on the standard differential evolution (DE) algorithm, the mutation strategy, scaling factor F, and cross factor CR of the algorithm are optimized. Also, the population position variance δ 2 is used to prevent falling into LMPP. Finally, the conditions for algorithm termination and restart are set. It is verified by simulation that the method has fast convergence speed, high accuracy, and can adapt well to changes in the external environment. The improved DE algorithm has a great advantage in MPPT.Energies 2020, 13, 1254 2 of 15 model and has strong robustness. However, it is difficult to establish a fuzzy rule because it needs to accumulate a lot of operation experience of power point tracking. In references [11,12], neural networks are used to track the MPP. This method also requires the distribution of power extremum points under many different shadows, so it is not practical. In references [13,14], Fibonacci is used to track the GMPP; this method also depends on the learning to the peak distribution, and it is easy to fall into LMPP. Reference [15] proposed a dichotomy, the first step is to find the vicinity of GMPP, and the second step is to use traditional MPPT method to track MPPs, but the dichotomy will fail in the case of complex shading. Reference [16] proposed a MPPT method using shading detection and the trend of slopes from each section of the curve. After the short-term and long-term testing, this method shows the advantages of high precision and short tracking time. In reference [17] a modified P&O MPPT algorithm is proposed for accurate detection of PSC, which stabilizes the system output voltage without compromising the power efficiency. Reference [18] proposed an algorithm that is based on bio-inspired Whale Optimization. This algorithm eliminates the computational burden faced by the hybrid MPPT algorithms as discussed in various references and reduces the power oscillation during the change in operating conditions. Reference [19] proposed a modified P&O MPPT that can be used under PSC effectively, by integrating the Artificial Bee Colony algorithm in the first stage and P&O algorithm in the second stage. However, the algorithm needs many parameters to be adjusted, which is not conducive to control.Based on the advantages and disadvantages of the above methods, the DE algorithm is used to optimize the output of PV array. DE only needs two adjustable parameters. Firstly, according to the method proposed in reference [20], the initial positions of particles are selected near the voltages corresponding to the possible MPPs to avoid falling into the LMPP. The mutation direction, mutation operator, and crossover operator of particles are optimized based on the traditional DE algorithm.

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Section: Selectionmentioning

confidence: 99%

Maximum Power Point Tracking Technology of Photovoltaic Array under Partial Shading Based On Adaptive Improved Differential Evolution Algorithm

Zhang

Sui

2020

Energies

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“…Only the buck or boost converter is unsuitable for PV systems because it provides limited output voltage. The buck and buck-boost converters have discontinuous current input flow, and SEPIC has a discontinuous output current with many components [104,105]. A single buck converter can be applied in dc MG for distributed and stand-alone PV systems due to its simple construction and high efficiency [103].…”

Section: Pv Converter Selectionmentioning

confidence: 99%

Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems

et al. 2018

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This paper elaborates a comprehensive overview of a photovoltaic (PV) system model, and compares the attributes of various conventional and improved incremental conductance algorithms, perturbation and observation techniques, and other maximum power point tracking (MPPT) algorithms in normal and partial shading conditions. Performance evaluation techniques are discussed on the basis of the dynamic parameters of the PV system. Following a discussion of the MPPT algorithms in each category, a table is drawn to summarize their key specifications. In the performance evaluation section, the appropriate PV module technologies, atmospheric effects on PV panels, design complexity, and number of sensors and internal parameters of the PV system are outlined. In the last phase, a comparative table presents performance-evaluating parameters of MPPT design criterion. This paper is organized in such a way that future researchers and engineers can select an appropriate MPPT scheme without complication.

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“…The tracking accuracy of this technique is always above 98%. In addition, an improved differential evolution-based MPTT algorithm using SEPIC DC/DC converter is proposed in [37] and [38]. Results of this technique shows that the MPPT algorithm has the capability to track the GMPP within 2s with an accuracy of 99%, and respond to load variation within 0.1s.…”

Section: Introductionmentioning

confidence: 99%

Assessing MPPT Techniques on Hot-Spotted and Partially Shaded Photovoltaic Modules: Comprehensive Review Based on Experimental Data

Dhimish

2019

IEEE Trans. Electron Devices

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Hot-spotting is a reliability problem influencing photovoltaic (PV) modules, where a mismatched solar cell/cells heat up significantly and reduce the output power of the affected PV module. Therefore, in this paper, a succinct comparison of seven different state-of-the-art MPPT techniques are demonstrated, doing useful comparisons with respect to amount of power extracted, hence calculate their tracking accuracy. The MPPT techniques have been embedded into a commercial off-the-shelf MPPT unit, accordingly running different experiments on multiple hot-spotted PV modules. Furthermore, the comparison includes real-time long-term data measurements over several days and months of validation. Evidently, it was found that both fast changing MPPT (FC-MPPT) and the modified beta (M-Beta) techniques are best to use with PV modules affected by hot-spotted solar cells as well as during partial shading conditions, on average, their tracking accuracy ranging from 92% to 94%. Ultimately, the minimum tracking accuracy is below 93% obtained for direct PWM voltage controller (D-PWM-VC) MPPT technique.

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Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation

Cited by 249 publications

References 22 publications

Maximum Power Point Tracking Technology of Photovoltaic Array under Partial Shading Based On Adaptive Improved Differential Evolution Algorithm

Maximum Power Point Tracking Technology of Photovoltaic Array under Partial Shading Based On Adaptive Improved Differential Evolution Algorithm

Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems

Assessing MPPT Techniques on Hot-Spotted and Partially Shaded Photovoltaic Modules: Comprehensive Review Based on Experimental Data

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