A review on MPPT techniques of PV system under partial shading condition

Mohapatra, Alivarani; Nayak, Byamakesh; Das, Pritam; Mohanty, Kanungo Barada

doi:10.1016/j.rser.2017.05.083

Cited by 370 publications

(191 citation statements)

References 84 publications

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Section: Introductionmentioning

confidence: 99%

“…Figure 3 shows the P-V characteristics of a photovoltaic string during a partial shading condition. The highest peak is the global peak which represents the maximum power of the photovoltaic string, while the others are the local peaks [24,25]. Apparently, a photovoltaic system is highly susceptible to partial shading [26][27][28][29][30][31][32][33][34][35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

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Impact of Partial Shading on the P-V Characteristics and the Maximum Power of a Photovoltaic String

et al. 2018

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Abstract:A photovoltaic system is highly susceptible to partial shading. Based on the functionality of a photovoltaic system that relies on solar irradiance to generate electrical power, it is tacitly assumed that the maximum power of a partially shaded photovoltaic system always decreases as the shading heaviness increases. However, the literature has reported that this might not be the case. The maximum power of a partially shaded photovoltaic system under a fixed configuration and partial shading pattern can be highly insusceptible to shading heaviness when a certain critical point is met. This paper presents an investigation of the impact of partial shading and the critical point that reduce the susceptibility of shading heaviness. Photovoltaic string formed by series-connected photovoltaic modules is used in this research. The investigation of the P-V characteristic curve under different numbers of shaded modules and shading heaviness suggests that the photovoltaic string becomes insusceptible to shading heaviness when the shaded modules irradiance reaches a certain critical point. The critical point can vary based on the number of the shaded modules. The formulated equation in this research contributes to determining the critical point for different photovoltaic string sizes and numbers of shaded modules in the photovoltaic string.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impact of Partial Shading on the P-V Characteristics and the Maximum Power of a Photovoltaic String

et al. 2018

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“…Various artificial intelligence MPPT techniques have been further developed recently to enhance the tracking performance under varying environmental conditions, and attempts were also made to develop some hybrid techniques to achieve faster tracking. Overview of all the conventional, soft computing, and hybrid MPPT techniques is thoroughly discussed in Ram et al and Mohapatra et al Almost all these reviewed MPPT techniques use both voltage and current sensors. Recently proposed work in Killi and Samanta and Dasgupta et al cites the demerits of using current sensing approach and proposes an efficient MPPT technique using only a voltage sensor which is adopted in this work.…”

Section: System Configurationmentioning

confidence: 99%

Kalman filter variant intelligent control for power quality improvement in photovoltaic active power filter system

Prince

Panda

2019

Int Trans Electr Energ Syst

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Summary The increased usage of nonlinear loads in the distribution system network with deep integration of renewable energy sources imposes the need for advanced control to improve power quality. With the objective to attain desired sinusoidal voltage waveshape at the common utility point, unity power factor operation, and reduction in harmonics, a swarm intelligent enhanced dual extended Kalman filter (DEKF) control technique for improving the performance of shunt active power filter (SAPF) is proposed in this paper. A photovoltaic (PV) array is integrated at the DC‐bus which supplies the required load power thus reducing the grid power demand. A single sensor‐based control is used to track the maximum power from the two‐stage PV array. The enhancement of the SAPF performance requires proper tuning of parameters; constriction factor‐based particle swarm optimization (PSO) is adopted in this regard. The DEKF estimates both state and parameter from the nonlinear system for generating a reference signal. The performance of the proposed control algorithm is compared with the Extended Kalman filter (EKF)‐based PV‐SAPF system using MATLAB/Simulink. To verify the efficacy of the controller, an experimental PV‐SAPF prototype is developed in the laboratory and tested under balanced and unbalanced supply, dynamic load as well as varying irradiance conditions.

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“…Others are based on BI including particle swarm optimization (PSO), simulated annealing (SA), tabu search (TS), cuckoo search optimization (CSO), teaching learning-based optimization (TLBO), firefly algorithm (FA), flower pollination algorithm (FPA), ant colony optimization (ACO), ant bee colony (ABC), and gray wolf optimization (GWO). [17][18][19][20][21][22][23][24] These modern MPPT techniques can track the GMP under a certain partial shading [24][25][26][27] but are unable to track the dynamic GMP under time-variant PS without certain improvements or modifications.…”

Section: Introductionmentioning

confidence: 99%

Dynamic global power extraction from partially shaded photovoltaic using deep recurrent neural network and improved PSO techniques

Farh

Eltamaly

Ibrahim

et al. 2019

Int Trans Electr Energ Syst

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Summary Under partial shading (PS) condition, the P‐V curve becomes more complex where many peaks (one global maximum peak [GMP] and many other local maximum peaks [LMPs]) are generated. This GMP changes with time under a time‐variant PS; this is called dynamic GMP. Conventional particle swarm optimization (PSO) can track the GMP under the same PS effectively. Nevertheless, it cannot track the dynamic GMP because all particles will be concentrated at the first GMP caught. In addition, using PSO as a maximum power point tracker (MPPT) technique suffers from obvious power oscillations in the steady state. In this paper, the PSO technique is improved to make it able to follow the dynamic GMP under time‐invariant PS. In addition, a novel deep recurrent neural network (DRNN) is introduced to track the dynamic GMP under time‐variant PS. A detailed comparison between DRNN and improved PSO is introduced, analyzed, and discussed. DRNN performs well compared with the improved PSO in terms of dynamic GMP tracking with almost zero steady‐state oscillation, tracking speed, accuracy, and efficiency.

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A review on MPPT techniques of PV system under partial shading condition

Cited by 370 publications

References 84 publications

Impact of Partial Shading on the P-V Characteristics and the Maximum Power of a Photovoltaic String

Impact of Partial Shading on the P-V Characteristics and the Maximum Power of a Photovoltaic String

Kalman filter variant intelligent control for power quality improvement in photovoltaic active power filter system

Dynamic global power extraction from partially shaded photovoltaic using deep recurrent neural network and improved PSO techniques

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