A Novel Combined Particle Swarm Optimization and Genetic Algorithm MPPT Control Method for Multiple Photovoltaic Arrays at Partial Shading

Liu, Liqun; Liu, Chunxia

doi:10.1115/1.4007940

Cited by 31 publications

(12 citation statements)

References 19 publications

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“…Any multivariable function can be optimized to a maximum or minimum value using this metaheuristic technique. [84][85][86][87][88][89][90][91][92][93] An optimum solution is obtained using the operating particles that move on the search space with a velocity and exchange the information of the fitness using Equations (21) and (22) and graphically shown in Figure 25:…”

Section: Particle Swarm Optimization Techniquementioning

confidence: 99%

A state‐of‐the‐art review on conventional, soft computing, and hybrid techniques for shading mitigation in photovoltaic applications

Kumar

Nema

et al. 2020

Int Trans Electr Energ Syst

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Summary This article intends to present a compendious review to extract maximum power in solar photovoltaic (PV) systems under varying environmental conditions and partial shading conditions by enumerating various circuit‐based topologies and different state‐of‐the‐art maximum power point techniques (MPPT). Partial shading reduces the overall efficiency of the PV system; therefore techniques that are dealing with partial shading play an important part in the power conditioning unit of all PV system connected to the stand‐alone mode or grid mode. Various circuit‐based topologies and various algorithms have been broadly discussed till date. As every algorithm is associated with its own merits and demerit, hence an extensive literature survey is required while planning for PV generating station under normal and partial shading condition. In this article, a comprehensive review of shading mitigation using different topologies has been done. The article on shading mitigation is broadly divided into two major groups. The first group includes all major circuit‐based topologies and the second group includes MPPT based techniques, which has been further classified into modified conventional techniques, soft computing techniques, and hybrid techniques. This comprehensive review presents an assessment of all techniques according to parameters like converter used, tracking speed, complexity, efficiency, number of sensors under partial shading condition would certainly provide a single platform to carry forward their research in solar PV application.

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Section: Particle Swarm Optimization Techniquementioning

confidence: 99%

A state‐of‐the‐art review on conventional, soft computing, and hybrid techniques for shading mitigation in photovoltaic applications

Kumar

Nema

et al. 2020

Int Trans Electr Energ Syst

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“…Proof. Take the Lyapunov function candidate (17) where denotes the estimation error. Taking the time derivative of gives (18) in which can be obtained by using (11) and 14as…”

Section: Definingmentioning

confidence: 99%

“…Fixed irradiance at and cell temperature (298 oK ). The ASMC algorithm, formed by (16), (17), and (23) with is applied here to solve the MPPT problem. Fig.…”

Section: Casementioning

confidence: 99%

“…Robust tracking methods [9,16] have been also developed to ensure robust stability and performance, despite the perturbations. Combination of classical strategies with evolutionary algorithms [17,18] may facilitate obtaining some additional goals as fast convergence, removing some measurements, and tracking the global peak of multiple PV arrays. However, apart from the category of the method, designing an MPPT algorithm with both the simplicity and universality properties is still highly desired.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive robust maximum power point tracking control for perturbed photovoltaic systems with output voltage estimation

Koofigar

2016

ISA Transactions

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The problem of maximum power point tracking (MPPT) in photovoltaic (PV) systems, despite the model uncertainties and the variations in environmental circumstances, is addressed. Introducing a mathematical description, an adaptive sliding mode control (ASMC) algorithm is first developed. Unlike many previous investigations, the output voltage is not required to be sensed and the upper bound of system uncertainties and the variations of irradiance and temperature are not required to be known. Estimating the output voltage by an update law, an adaptive-based H∞ tracking algorithm is then developed for the case the perturbations are energy-bounded. The stability analysis is presented for the proposed tracking control schemes, based on the Lyapunov stability theorem. From a comparison viewpoint, some numerical and experimental studies are also presented and discussed.

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“…So, the fast technique to get optimum duty change will be helpful in increasing the stability of the PV system. A modified PSO technique 28,32 has been used to modify the inertia weight, x using a genetic algorithm (GA) principals to improve its robustness while searching for the GP. The modified inertia weight, x can be obtained from Equation (8) which uses the GA principles by increasing the value of inertia weight, x for the beginning (at global search stage) and reduces it for precise increment at the end of optimization when the particles get closer to optimal solution xðkÞ ¼ x s À ðx s À x e ÞðT m À kÞ=T m ;…”

Section: Pso Mppt Techniquementioning

confidence: 99%

Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems

Eltamaly

2015

Journal of Renewable and Sustainable Energy

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Power quality assessment of a solar photovoltaic two-stage grid connected system: Using fuzzy and proportional integral controlled dynamic voltage restorer approach J. Renewable Sustainable Energy 7, 013113 (2015); 10.1063/1.4906980Modeling and global maximum power point tracking for photovoltaic system under partial shading conditions using modified particle swarm optimization algorithm J. Renewable Sustainable Energy 6, 063117 (2014); 10.1063/1.4904436Adaptive fuzzy logic control based optimal Hopfield neural network of standalone photovoltaic system with battery storage J. Renewable Sustainable Energy 6, 033113 (2014); 10.1063/1.4878844Maximum power point tracking of partial shaded photovoltaic array using an evolutionary algorithm: A particle swarm optimization technique Partial shading on photovoltaic (PV) modules reduces the generated power of the PV system than the maximum power generated from each module separately. The shaded PV module acts as a load to unshaded ones which can lead to hot-spot. To alleviate the effect of partial shading, bypass diodes should be connected across each PV modules. Connecting several PV modules together produces multiple peaks (one global peak (GP) and multiple local peaks (LPs)) on partial shading conditions. Maximum power point tracker conventional techniques are designed to follow the GP but they stuck around LPs such as fuzzy logic controller (FLC). In this paper, modified particle swarm optimization (MPSO) using genetic algorism has been used to follow the GP under any operating conditions. MPSO has been studied and compared with the FLC technique to show the superiority of this technique under all operating conditions. Co-simulation between Matlab/Simulink and PSIM has been used to model the PV system under partial shading conditions. The simulation results show that the MPSO technique is more effective than FLC in following the GP. The generated power increases considerably with the MPSO than the FLC technique in shading conditions. V C 2015 AIP Publishing LLC.

show abstract

A Novel Combined Particle Swarm Optimization and Genetic Algorithm MPPT Control Method for Multiple Photovoltaic Arrays at Partial Shading

Cited by 31 publications

References 19 publications

A state‐of‐the‐art review on conventional, soft computing, and hybrid techniques for shading mitigation in photovoltaic applications

A state‐of‐the‐art review on conventional, soft computing, and hybrid techniques for shading mitigation in photovoltaic applications

Adaptive robust maximum power point tracking control for perturbed photovoltaic systems with output voltage estimation

Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems

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