Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method

Seyedmahmoudian, Mehdi; Rahmani, Rasoul; Mekhilef, Saad; Oo, Amanullah Maung Than; Stojcevski, Alex; Soon, Tey Kok; Ghandhari, Alireza Safdari

doi:10.1109/tste.2015.2413359

Cited by 282 publications

(141 citation statements)

References 41 publications

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“…However, the top ten cited papers In general aspects, it can be appreciated in Table 5 that the tendency of recent influential works lays on the hybridization of EC algorithms. Combinations of DE and PSO into DEPSO [90], ACO and ABC into ACO-ABC [91], or a multistep approach using cuckoo search (CS) algorithm, fuzzy system (FS), weather research and forecasting (WRF), and ensemble forecast (CS-FS-WRF-E) [92] are some examples of the synergies that can be produced between EC algorithms for solving more challenging problems.…”

Section: Evolutionary Computation (Ec) In the Energy Domainmentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.

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Section: Evolutionary Computation (Ec) In the Energy Domainmentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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“…Within the meta-heuristic algorithms, particle swarm optimization (PSO) is the most used algorithm in literature, thanks to its simple implementation and powerful behaviour at PSC. Other methods in this group are, simulated annealing [8], Grey-Wolf optimization [9], DEPSO [10], firefly colony [11] and artificial bee colony. All these algorithms are investigated for advantages and drawbacks in the following sub-sections.…”

Section: Meta-heuristicsmentioning

confidence: 99%

“…The DEPSO [10] technique is a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the MPP under PSC. The benefits of the DEPSO are reliability, systemindependence and accuracy in tracking the GMPP.…”

Section: Meta-heuristicsmentioning

confidence: 99%

A Review of MPPT Algorithms for Partial Shading Conditions

Erdem

2017

Acta Phys. Pol. A

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Maximum power point tracker in a photovoltaic system allows to maximize the energy drawn from the connected photovoltaic modules. In the partial shade conditions there can be more than one maximum point in photovoltaic output power curve. The solution for this situation is a maximum power point tracker algorithm, which finds the global maximum. In literature, there is a large number of studies on maximum power point trackers. Therefore designers are drowning in a sea of knowledge. This study eliminates similar studies and classified them into groups, and at the end of the study a comparison table is given to guide the designers in the performance information of the selected studies. This study aims to guide the designers to make a sensible selection of a maximum power point tracker algorithm for partial shade conditions.

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“…Figure 9. Circuitry diagram of the selected PV array [36]. Given the double-bypass diode in each module, three possible scenarios that have been considered in this study are as follows: (i) the entire module one receives an irradiance level of 1000 W/m 2 (G1 = G2 = 1000) and the entire module two receives an irradiance level of 350 W/m 2 (G3 = G4 = 350); (ii) the entire module one receives an irradiance level of 1000 W/m 2 (G1 = G2 = 1000) and module two receives irradiance levels of 700 W/m 2 and 500 W/m 2 (G3 = 700, G4 = 500); (iii) module one receives irradiance levels of (G1 = 1200, G2 = 700) and module two receives irradiance levels of 700 W/m 2 and 500 W/m 2 (G3 = 500, G4 = 300).…”

Section: Testing Conditionsmentioning

confidence: 99%

“…For instance, in [33], the authors used a deterministic PSO method with removed random coefficients to reduce the metaheuristic aspect of these evolutionary algorithms. In other studies [34][35][36], PSO has been combined with other methods in the form of hybrid techniques to boost the accuracy and reduce the effects of random coefficients in the PSO technique. These combinations however resulted in longer processing time or higher complexity.…”

Section: Introductionmentioning

confidence: 99%

Efficient Photovoltaic System Maximum Power Point Tracking Using a New Technique

et al. 2016

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Abstract:Partial shading is an unavoidable condition which significantly reduces the efficiency and stability of a photovoltaic (PV) system. When partial shading occurs the system has multiple-peak output power characteristics. In order to track the global maximum power point (GMPP) within an appropriate period a reliable technique is required. Conventional techniques such as hill climbing and perturbation and observation (P&O) are inadequate in tracking the GMPP subject to this condition resulting in a dramatic reduction in the efficiency of the PV system. Recent artificial intelligence methods have been proposed, however they have a higher computational cost, slower processing time and increased oscillations which results in further instability at the output of the PV system. This paper proposes a fast and efficient technique based on Radial Movement Optimization (RMO) for detecting the GMPP under partial shading conditions. The paper begins with a brief description of the behavior of PV systems under partial shading conditions followed by the introduction of the new RMO-based technique for GMPP tracking. Finally, results are presented to demonstration the performance of the proposed technique under different partial shading conditions. The results are compared with those of the PSO method, one of the most widely used methods in the literature. Four factors, namely convergence speed, efficiency (power loss reduction), stability (oscillation reduction) and computational cost, are considered in the comparison with the PSO technique.

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Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method

Cited by 282 publications

References 41 publications

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

A Review of MPPT Algorithms for Partial Shading Conditions

Efficient Photovoltaic System Maximum Power Point Tracking Using a New Technique

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