A new high performance variable step size perturb-and-observe MPPT algorithm for photovoltaic system

Saidi, Khadidja; Maamoun, Mountassar; Bounekhla, M.

doi:10.11591/ijpeds.v10.i3.pp1662-1674

Cited by 25 publications

(18 citation statements)

References 19 publications

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“…The solution to this aforementioned problem is done by introducing bypass diode which is connected in parallel to each module. The presence of bypass diode in each module creates multiple peaks of P-V and I-V curves as shown in Figure 1 [6]. PV module BPSX150 with specifications as shown in Table 1 is used to generate the pattern of partial shading conditions in this paper.…”

Section: Partial Shading Conditionsmentioning

confidence: 99%

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A maximum power point tracking based on levy flight optimization

Charin

Ishak

Zainuri

2020

IJPEDS

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This paper proposes a Levy flight global maximum power point tracking for solar photovoltaic (PV) system under partial shading conditions. The proposed method comes with merits such as simplicity, fast response and free of oscillation. This algorithm uses random search over the exploration space and compares the previous and current states to obtain the best solution. For evaluation and comparative analysis, performance of the proposed method is also measured against Perturb and Observe (P&O) and Particle Swarm Optimization (PSO). All three algorithms are simulated in MATLAB/Simulink environment. Simulation results are satisfactory over the conducted tests under uniform and non-uniform irradiance. The proposed algorithm is able to track global maximum power point (GMPP) under partial shading conditions with fast tracking time and zero ripple at steady-state.

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Section: Partial Shading Conditionsmentioning

confidence: 99%

“…This emerging technology has gained a lot of interests from researchers in the area of grid integration, control and optimization [5]. However, this technology is still limited to its efficiency [6]. Efficiency of PV system is still low, less than 22.4% [3,7].…”

Section: Introductionmentioning

confidence: 99%

A maximum power point tracking based on levy flight optimization

Charin

Ishak

Zainuri

2020

IJPEDS

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“…Thus, the need for low carbon-based sources of electricity (green energy) such as wind, solar, biomass, etc., is essential in the coming future [5,6]. Among these sources, solar photovoltaic (PV) energy is seen as the best potential candidate due to its availability and cleanliness [7][8][9][10]. Thus, due to this interest, focusing on solar PV energy is prioritized.…”

Section: Introductionmentioning

confidence: 99%

Modified Levy Flight Optimization for a Maximum Power Point Tracking Algorithm under Partial Shading

et al. 2021

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This paper presents a novel modified Levy flight optimization for a photovoltaic PV solar energy system. Conventionally, the Perturb and Observe (P&O) algorithm has been widely deployed in most applications due to its simplicity and ease of implementation. However, P&O suffers from steady-state oscillation and stability, besides its failure in tracking the optimum power under partial shading conditions and fast irradiance changes. Therefore, a modified Levy flight optimization is proposed by incorporating a global search of beta parameters, which can significantly improve the tracking capability in local and global searches compared to the conventional methods. The proposed modified Levy flight optimization is verified with simulations and experiments under uniform, non-uniform, and dynamic conditions. All results prove the advantages of the proposed modified Levy flight optimization in extracting the optimal power with a fast response and high efficiency from the PV arrays.

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“…Different MPPT methods have been presented in literature such as perturb and observe (P&O) [7][8][9][10], Hill Climbing (HC) [11,12], incremental conductance (INC) [13,14], comparative between P&O and incremental conductance [15,16], fuzzy logic [17] comparative between P&O and fuzzy logic [18,19], and neural network [20,21]. The most known and commercially used methods is the (P&O).…”

Section: Introductionmentioning

confidence: 99%

Comparison between neural network and P&O method in optimizing MPPT control for photovoltaic cell

Abdullah

Aziz

Hamad

2020

IJECE

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The demand for renewable energy has increased because it is considered a clean energy and does not result in any pollution or emission of toxic gases that negatively affect the environment and human health also requiring little maintenance, and emitting no noise, so it is necessary to develop this type of energy and increase its production capacity. In this research a design of maximum power point tracking (MPPT) control method using Neural Network (NN) for photovoltaic system is presented. First we design a standalone PV system linked to dc boost chopper with MPPT by perturbation and observation P&O technique, and then a design of MPPT by using ANN for the same system is presented. Comparative between two control methods are studied. The results explained in constant and adjustable weather settings such as irradiation and temperature. The results exposed that the proposed MPPT by ANN control can improve the PV array efficiency by reduce the oscillation around the MPP that accure in P&O method and so decreases the power losses. As well as decrease the the overshot that accure in transient response, and hence improving the performance of the solar cell.

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A new high performance variable step size perturb-and-observe MPPT algorithm for photovoltaic system

Cited by 25 publications

References 19 publications

A maximum power point tracking based on levy flight optimization

A maximum power point tracking based on levy flight optimization

Modified Levy Flight Optimization for a Maximum Power Point Tracking Algorithm under Partial Shading

Comparison between neural network and P&O method in optimizing MPPT control for photovoltaic cell

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