Comprehensive overview of meta-heuristic algorithm applications on PV cell parameter identification

Maximum power point tracking (MPPT) control techniques play a vital role in efﬁciency improvement of photovoltaic (PV) systems. It is mainly used to extract maximum possible power of the PV modules under both variable climatic and partial shaded condition (PSC). From literature, various types of MPPT techniques have been developed to track the maximum power point efficiently, ranging from conventional methods to artificial intelligence and bio-inspired methods. Each technique has its own advantage and drawbacks. This paper focuses mainly on a review on advancements of global maximum power point tracking (GMPPT) techniques of photovoltaic (PV) system subjected to partial shading conditions (PSC) to help the users to make the right choice when designing their system. The most recent and selected MPPT methods are discussed and classified as optimization, hybrid, mathematical model based methods and other GMPPT methods. This study will serve as interesting guide for researchers working on PV system field.

A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions

Dynamic global maximum power point tracking of the PV systems under variant partial shading using hybrid GWO-FLC

Comprehensive overview of maximum power point tracking algorithms of PV systems under partial shading condition

A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system is presented in this paper. In recent years, there has been a growing attention toward mitigation of partial shading effect of the PV system through using modern optimization. The field of tracking MPP of the PV system attracts huge attention from the researchers, as it is the best way to increase PV plant efficiency. Under non-uniform solar irradiance, the power against voltage characteristics of PV array have more than one MPP. This condition leads to extra complications to track MPP and decreases the efficiency of the PV system. Traditional MPPT methods are typically used to increase the harvested energy of PV under normal conditions without any problems. The key drawback of such methods is failing extraction of global MPP under actual weather conditions that sometimes under shadowing condition. Several global MPPT methods based on modern optimization are presented for extracting global MPP in case of shadowing condition. The essential target of this work is not limited to present an integrated specific review on the state-of-the-art of these techniques; but also a comprehensive statistical evaluation of twenty optimizers that represent high percent of all the reported techniques is performed with changing shading scenarios. This work serves as a source of valuable information for researchers and engineers working with PV systems to keep abreast with the modern advance in the field of tracking MPP of PV system.

A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system

Partial shading condition is one of the adverse phenomena which effects the power output of photovoltaic (PV) systems due to inaccurate tracking of global maximum power point. Conventional Maximum Power Point Tracking (MPPT) techniques like Perturb and Observe, Incremental Conductance and Hill Climbing can track the maximum power point effectively under uniform shaded condition, but fails under partial shaded condition. An attractive solution under partial shaded condition is application of meta-heuristic algorithms to operate at global maximum power point. Hence in this paper, an Enhanced Grey Wolf Optimizer (EGWO) based maximum power point tracking algorithm is proposed to track the global maximum power point of PV system under partial shading condition. A Mathematical model of PV system is developed under partial shaded condition using single diode model and EGWO is applied to track global maximum power point. The proposed method is programmed in MATLAB environment and simulations are carried out on 4S and 2S2P PV configurations for dynamically changing shading patterns. The results of the proposed method are analyzed and compared with GWO and PSO algorithms. It is observed that proposed method is effective in tracking global maximum power point with more accuracy in less computation time compared to other methods. Article History : Received June 12nd 2017; Received in revised form August 13rd 2017; Accepted August 15 th 2017; Available online How to Cite This Article : Kumar, C.H.S and Rao, R.S. (2017 Enhanced Grey Wolf Optimizer Based MPPT Algorithm of PV System Under Partial Shaded Condition. Int. Journal of Renewable Energy Development, 6(3), 203-212. https://doi.org/10.14710/ijred.6.3.203-212

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Srinivasa Rao Rayapudi

Papers

Enhanced Grey Wolf Optimizer based MPPT Algorithm of PV system under Partial Shaded Condition