Harris hawk optimization-based MPPT control for PV systems under partial shading conditions

Mansoor, Majad; Mirza, Adeel Feroz; Ling, Qiang

doi:10.1016/j.jclepro.2020.122857

Cited by 157 publications

(60 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, the PV systems voltage fluctuation is a challenging task. To overcome these issues, Mansoor et al [ 22 ] proposed a novel Harris hawk optimization, and based on the MPPT controller, it tracks the voltage fluctuation effectively. Furthermore, the statistical examination is prepared by various cases based on the PV systems.…”

Section: Related Workmentioning

confidence: 99%

Novel Hybrid Optimization Maximum Power Point Tracking and Normalized Intelligent Control Techniques for Smart Grid Linked Solar Photovoltaic System

2021

View full text Add to dashboard Cite

Introduction of photovoltaic (PV) systems in grid causes some complex power quality problems such as harmonics, voltage fluctuation, and load imbalance that can affect the grid coordinated PV system performance. Therefore, herein, a novel normalized reasoning‐based fuzzy neural adaptive (NRFNA) control technique is proposed for the double‐stage grid coupled solar PV system. In addition, the utmost power in a double‐stage PV system is tracked at dissimilar environmental states by the proposed novel hybrid krill herd spider monkey (HKHSM)‐based maximum power point tracking (MPPT) algorithm. The current computation control method preserves the grid current in unity power factor as sinusoidal for the system at point common coupling (PCC). The simulation of this proposed work is done on MATLAB/Simulink. Subsequently, the performance of the developed replica results is validated under dissimilar conditions of power quality. Furthermore, the proposed HKHSM‐based MPPT along with a normalized reasoning herd spider monkey (NRHSM) control technique in a grid coordinated solar PV system has achieved 1.70% load current harmonics and 3.7% grid current harmonics. Consequently, the simulation outcomes are compared with the various conventional methods for proving the significance of the proposed system.

show abstract

Section: Related Workmentioning

confidence: 99%

Novel Hybrid Optimization Maximum Power Point Tracking and Normalized Intelligent Control Techniques for Smart Grid Linked Solar Photovoltaic System

2021

View full text Add to dashboard Cite

show abstract

“…Most of them depend on a power-voltage (P-V) scan of the PV and store the state at each observed shading condition. Other methods such as partial swarm optimization (PSO) [14,15], Harris hawk optimization [16], bat algorithm [17], or implementing soft computing optimization techniques [10,18] have been proposed before. The main limitations of these techniques are their computational complexity, initial condition dependency, cost, and slow tracking.…”

Section: Introductionmentioning

confidence: 99%

PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions

et al. 2021

View full text Add to dashboard Cite

Because of the unpredictable activity of solar energy sources, photovoltaic (PV) maximum power point tracking (MPPT) is essential to guarantee the continuous operation of electrical energy generation at optimal power levels. Several works have extensively examined the generation of the maximum power from the PV systems under normal and shading conditions. The fuzzy logic control (FLC) method is one of the effective MPPT techniques, but it needs to be adapted to work in partial shading conditions. The current paper presents the FLC-based on dynamic safety margin (DSM) as an MPPT technique for a PV system to overcome the limitations of FLC in shading conditions. The DSM is a performance index that measures the system state deviation from the normal situation. As a performance index, DSM is used to adapt the FLC controller output to rapidly reach the global maxima of the PV system. The ability of the proposed algorithm and its performance are evaluated using simulation and practical implementation results for single phase grid-connected PV system under normal and partial shading operating conditions.

show abstract

“…However, the algorithm fails to track the GP due to the less search space. The other meta-heuristic algorithms, such as Grey Wolf Optimization (GWO) [19], whale optimization algorithm (WOA) [20], harris-hawk optimization [21], slime mould algorithm [22], marine predator algorithm [23], salp-swarm optimization algorithm (SSA) [24], etc. were discussed in the literature.…”

Section: Introductionmentioning

confidence: 99%

A novel salp swarm assisted hybrid maximum power point tracking algorithm for the solar photovoltaic power generation systems

Premkumar¹,

Kumar²,

Sowmya

et al. 2020

Automatika

View full text Add to dashboard Cite

The photovoltaic (PV) systems must work at the maximum power point (MPP) to derive the highest possible power with the higher performance during a change in operating conditions. The primary objective is to implement a novel hybrid tracking algorithm to extract the maximum output power from the solar PV panel or array under partial shading conditions (PSCs). This hybrid MPP tracking algorithm is based on the salp swarm algorithm (SSA), which finds the initial global peak (GP) operating point and is followed by the perturb and observation (P&O) algorithm in the last stage to realize a faster convergence rate. Thus, the computational burden met by the conventional methods such as standalone P&O, hybrid grey-wolf-optimization (HGWO), and hybrid whale-optimization algorithm (HWOA) algorithm reported in the literature is overcome by the proposed hybrid SSA algorithm called HSSA. The P&O algorithm searches the MPP in the projected search space by the SSA algorithm. The proposed hybrid algorithm is simulated using MATLAB/Simulink simulation tool to validate the effectiveness of tracking the MPP. The hybrid SSA is compared with the standalone P&O, hybrid WOA, and hybrid GWO, and from the simulation results, it is proved that the hybrid tracking algorithm exhibits a high tracking performance.

show abstract

Harris hawk optimization-based MPPT control for PV systems under partial shading conditions

Cited by 157 publications

References 51 publications

Novel Hybrid Optimization Maximum Power Point Tracking and Normalized Intelligent Control Techniques for Smart Grid Linked Solar Photovoltaic System

Novel Hybrid Optimization Maximum Power Point Tracking and Normalized Intelligent Control Techniques for Smart Grid Linked Solar Photovoltaic System

PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions

A novel salp swarm assisted hybrid maximum power point tracking algorithm for the solar photovoltaic power generation systems

Contact Info

Product

Resources

About