A hybrid intelligent GMPPT algorithm for partial shading PV system

Mao, Mingxuan; Zhou, Lin; Yang, Zengrui; Zhang, Qianjin; Zheng, Chen; Xie, Bin; Wan, Yihao

doi:10.1016/j.conengprac.2018.10.013

Cited by 48 publications

(19 citation statements)

References 24 publications

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“…Many mathematical models of the PV are introduced by the researchers. Among them, single diodes PV is the most frequently used for PV cell modeling because of the simplicity and computational efficiency 37 . The equivalent circuit of a single diode model is illustrated in Figure 2.…”

Section: Design Of Pv System Under Pscmentioning

confidence: 99%

CCGPA‐MPPT: Cauchy preferential crossover‐based global pollination algorithm for MPPT in photovoltaic system

Sundararaj

Anoop

Dixit

et al. 2020

Progress in Photovoltaics

173

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In general, the photovoltaic (PV) is considered as the best selection among renewable energy resources due to its nonpolluted operation and good flexibility condition. The PV system is affected because of the partial shading conditions (PSCs), which reduce the generated power. During steady-state operating conditions, there occurs a time delay in tracking the Global maximum power point (GMPP) and Local maximum power point (LMPP) under PSCs using the perturb and observe (P&O) method. In order to overcome such shortcomings, this paper proposed a hybrid algorithm with a P&O technique to improve the maximum power point tracking (MPPT) for the PV system under PSC. In addition to this, the P&O technique is utilized to achieve the LMPP in the first section, and the hybrid algorithm is utilized to achieve the GMPP in the second section. Here, the hybrid technique is the integration of Cauchy preferential crossover (CC) with the flower pollination algorithm (FPA). Furthermore, the exploitation ability of the FPA is enhanced by the CC, and the combined hybrid algorithm has the ability to produce the optimal duty cycle for the DC-DC boost converter for MPPT. Then the proposed method will be executed in MATLAB/Simulink model, and it is contrasted with the existing methods such as CC, current sensorless (CS), and FPA, respectively. The experimental results and analysis reveal that the proposed approach provides better performances when compared with several other metaheuristic algorithms. K E Y W O R D S crossover, DC to DC boost converter, global maximum power point, global pollination, local maximum power point, photovoltaic, PSC 1 | INTRODUCTION Due to the rapid growth and expansion in business as well as the consistently increasing refinement of existing ways of living, the world supply energy is exposed to a huge strain. This wonder creates uncertainties over energy security as well as environmental sustainability. 1,2 Besides, the problem of climatic changes and it is necessary to reduce carbon impressions has added to the solid force for organizations and countries to put resources into elective energy sources, especially renewable energy (RE). Solar energy is a standout among the most vital RE sources, rather than regular unrenewable assets, for example, fuel and coal. 3 Solar energy is spotless, limitless, and free. The primary utilization of photovoltaic (PV) frameworks is said to be a stand-alone (military, street and residential lighting, electric vehicles space applications, and water pumping). Despite these

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Section: Design Of Pv System Under Pscmentioning

confidence: 99%

CCGPA‐MPPT: Cauchy preferential crossover‐based global pollination algorithm for MPPT in photovoltaic system

Sundararaj

Anoop

Dixit

et al. 2020

Progress in Photovoltaics

173

View full text Add to dashboard Cite

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“…An improved PSO with brain emotional learning-based intelligence (IPSO-BELBI) is used for the same reason [91]. Another group of researchers opted to combine two or more metaheuristic search methods: WO-DE [92], PSO-SFLA [93], WOA-SA [94], FLC-FFA [95], and DE-PSO [15]. Others use PSO with FSA using an extended memory strategy [96], Gaussian process regression-JA with PSO [97], and ANN-FLC [77].…”

Section: Hybrid Between Sc and Conventional Mpptmentioning

confidence: 99%

Recent developments of MPPT techniques for PV systems under partial shading conditions: a critical review and performance evaluation

Kermadi

Salam

Eltamaly

et al. 2020

IET Renewable Power Generation

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This review covers global maximum power point tracking (GMPPT) methods for photovoltaic (PV) systems under partial shading conditions. Unlike the previous review works that primarily focused on soft computing and hybrid GMPPT, this study gives exclusive attention to the improvement achieved by the conventional MPPT (perturb and observe, hill climbing, and incremental conductance). The improved methods include the popular 0.8 × V oc model and, more recently, the skipping algorithms. In addition to providing qualitative descriptions of the available techniques, this work also attempts to provide a fair evaluation of GMPPT to determine their comparative performances. The competing algorithms, which are selected to represent every category (conventional and soft computing and hybrid MPPT), are benchmarked under carefully selected operating conditions and shading scenarios. The evaluation is focused on four main criteria: tracking accuracy, convergence time, length of voltage fluctuations, and transient efficiency during the search for the global maximum power point. The results obtained from this study can become a basis for researchers and designers to select the best MPPT technique for their respective applications.

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“…The literature also presents a combination of conventional MPPT and soft computing MPPT, such as PSO blended with ANFIS [58], hybrid ABC with HC [59], Fuzzy blended with PSO [60], ACO blended with P&O [61], FPA with P&O [56], PSO with P&O [62] and PSO combined with DE to produce DEPSO [54], [63]. The results of these combinations show promising outcomes and implementation opportunities.…”

Section: Introductionmentioning

confidence: 99%

An Effective Salp Swarm Based MPPT for Photovoltaic Systems Under Dynamic and Partial Shading Conditions

et al. 2021

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This study proposes a duty cycle-based direct search method that capitalizes on a bioinspired optimization algorithm known as the salp swarm algorithm (SSA). The goal is to improve the tracking capability of the maximum power point (MPP) controller for optimum power extraction from a photovoltaic system under dynamic environmental conditions. The performance of the proposed SSA is tested under a transition between uniform irradiances and a transition between partial shading (PS) conditions with a focus on convergence speed, fast and accurate tracking, reduce high initial exploration oscillation, and low steady-state oscillation at MPP. Simulation results demonstrate the superiority of the proposed SSA algorithm in terms of tracking performance. The performance of the SSA method is better than the conventional (hill-climbing) and among other popular metaheuristic methods. Further validation of the SSA performance is conducted via experimental studies involving a DC-DC buck-boost converter driven by TMS320F28335 DSP on the Texas Instruments Experimenter Kit platform. Hardware results show that the proposed SSA method aligns with the simulation in terms of fast-tracking, convergence speed, and satisfactory accuracy under PS and dynamic conditions. The proposed SSA method tracks maximum power with high efficiency through its superficial structures and concepts, as well as its easy implementation. Moreover, the SSA maintains a steady-state oscillation at a minimum level to improve the overall energy yield. It thus compensates for the shortcomings of other existing methods.

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A hybrid intelligent GMPPT algorithm for partial shading PV system

Cited by 48 publications

References 24 publications

CCGPA‐MPPT: Cauchy preferential crossover‐based global pollination algorithm for MPPT in photovoltaic system

CCGPA‐MPPT: Cauchy preferential crossover‐based global pollination algorithm for MPPT in photovoltaic system

Recent developments of MPPT techniques for PV systems under partial shading conditions: a critical review and performance evaluation

An Effective Salp Swarm Based MPPT for Photovoltaic Systems Under Dynamic and Partial Shading Conditions

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