A Salp-Swarm Optimization based MPPT technique for harvesting maximum energy from PV systems under partial shading conditions

Mirza, Adeel Feroz; Mansoor, Majad; Ling, Qiang; Yin, Baocai; Javed, Muhammad Yaqoob

doi:10.1016/j.enconman.2020.112625

Cited by 157 publications

(73 citation statements)

References 33 publications

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“…In addition, in other studies, bee colony optimisation (BCO) algorithm [25], bat optimisation (BO) algorithm [26], salp swarm optimisation (SSO) algorithm [27], (all belong to the BI algorithms), were employed in the solar MPPT units mostly for their capability of tracking and identifying the GMPP under PSC. However, their efficiency, implementation complexity, and applicability in the large-scale solar SRES need to be further investigated.…”

Section: B Novel Mppt Methodsmentioning

confidence: 99%

A Scheme-Based Review of MPPT Techniques With Respect to Input Variables Including Solar Irradiance and PV Arrays’ Temperature

2020

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Maximum power point tracking (MPPT) techniques have been vastly researched and developed in order to obtain the maximum terminal power of photovoltaic (PV) arrays in the solar renewable energy system. The aim of this paper is to present a new principal scheme-based review of the categorised MPPT methods (conventional, novel, and hybrid) with respect to the deployment of their input variables (solar irradiance, PV arrays' temperature, and PV arrays' terminal voltage and current), where MPPT methods are categorised to six different schemes. For each scheme, previous MPPT studies are extracted from literature and analysed. Then the critical benefits and limitations of the six presented MPPT schemes are compared and discussed. It is concluded that those MPPT schemes deploying the measured external variables would be able to track the global maximum power point with high reliability; however, their implementation cost and applicability remains as a challenge due to increasing the sensor deployment cost and complexity. The conclusion of this paper will help new researchers to deliberately select an appropriate MPPT scheme based on their projects' objectives and limitations, prior to selecting an optimisation algorithm for MPPT.

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Section: B Novel Mppt Methodsmentioning

confidence: 99%

A Scheme-Based Review of MPPT Techniques With Respect to Input Variables Including Solar Irradiance and PV Arrays’ Temperature

2020

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“…Various MPPT algorithms for effective tracking of true maximum power point (MPP) are proposed in the literature and tested under various shading scenarios [5]. Some of these algorithms follow techniques such as fusion fly [6], Harish hawk optimization [7], grasshopper optimization [8], salp-swarm optimization [9], dynamic particle method [10], hybrid evolutionary methods [11], improved grey wolf optimization [12], bat algorithm [13], chaotic flower pollination [14], marine predators algorithm [15] etc. But, the adoption of these algorithms in the PV system can add to system cost and complexity due to the requirement of large numbers of switches, sensors, powerful microcontrollers and complex algorithms.…”

Section: Introductionmentioning

confidence: 99%

Impact of Uneven Shading by Neighboring Buildings and Clouds on the Conventional and Hybrid Configurations of Roof-Top PV Arrays

Satpathy

Babu

Shanmugam³

et al. 2021

IEEE Access

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Partial shading is the commonly encountered scenario of building roof-top based PV arrays that mainly occur due to the shadow of the neighbouring buildings and clouds resulting in unexpected losses and deteriorated system performance. The arrays are connected in various configurations to enhance the system performance during shading. In this paper, various conventional and hybrid interconnection configurations based on series-parallel (SP), bridge-linked (BL), and total cross tied (TCT) topologies of the roof-top PV arrays are examined under various partial shading scenarios caused by the neighbouring building and clouds. The investigation is done for a 9x9 roof-top array in MATLAB/Simulink environment considering various comparison parameters. It has been found that during 1.23%, 7.40%, 11.11%, 17.75%, 18.51%%, 22.22%, and 24.69% of total array shading, SP generated the maximum power whereas, during 30.86%, 61.72% shading, TCT has the generated only a slightly higher power as compared to SP. Hence, the study concludes that the configurations have a puny effect on the power generation of the arrays during uneven shading patterns caused by buildings and clouds.

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“…Meta-heuristics algorithms, which include particle swarm optimization (PSO) [17,18], artificial bee colony (ABC) [19], simulated annealing (SA) [20], cuckoo search (CS) [21,22], ant colony optimization (ACO) [23], moth fly optimization (MFO) [24], grey wolf optimization (GWO) [25], and pattern search (PS) [26] have recently proven to be effective for global optimization problems. There are many factors on which the performance of bio-inspired optimization techniques depend, namely population size, number of iterations, convergence speed, information sharing mechanism, computational time, and parametric tuning [27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

“…Individually every ant is a member of a set representing a probable solution, so a cautious selection mechanism is required. Scout ants are also utilized to explore the search space [29]. In CSA random values are assigned using Levy flight, which causes unwanted fluctuations in output [20].…”

Section: Introductionmentioning

confidence: 99%

Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

et al. 2020

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The most cost-effective electrical energy is produced by photovoltaic (PV) systems, and with the smallest carbon footprint, making it a sustainable renewable energy. They provide an excellent alternative to the existing fossil fuel-based energy systems, while providing 4% of global electricity demand. PV system efficiency is significantly reduced by the intrinsic non-linear model, maximum power point (MPP), and partial shading (PS) effects. These two problems cause major power loss. To devise the maximum power point tracking (MPPT) control of the PV system, a novel group teaching optimization algorithm (GTOA) based controller is presented, which effectively deals with the PS and complex partial shading (CPS) conditions. Four case studies were employed that included fast-changing irradiance, PS, and CPS to test the robustness of the proposed MPPT technique. The performance of the GTOA was compared with the latest bio-inspired techniques, i.e., dragon fly optimization (DFO), cuckoo search (CS), particle swarm optimization (PSO), particle swarm optimization gravitational search (PSOGS), and conventional perturb and observe (P&O). The GTOA tracked global MPP with the highest 99.9% efficiency, while maintaining the magnitude of the oscillation <0.5 W at global maxima (GM). Moreover, 13–35% faster tracking times, and 54% settling times were achieved, compared to existing techniques. Statistical analysis was carried out to validate the robustness and effectiveness of the GTOA. Comprehensive analytical and statistical analysis solidified the superior performance of the proposed GTOA based MPPT technique.

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A Salp-Swarm Optimization based MPPT technique for harvesting maximum energy from PV systems under partial shading conditions

Cited by 157 publications

References 33 publications

A Scheme-Based Review of MPPT Techniques With Respect to Input Variables Including Solar Irradiance and PV Arrays’ Temperature

A Scheme-Based Review of MPPT Techniques With Respect to Input Variables Including Solar Irradiance and PV Arrays’ Temperature

Impact of Uneven Shading by Neighboring Buildings and Clouds on the Conventional and Hybrid Configurations of Roof-Top PV Arrays

Group Teaching Optimization Algorithm Based MPPT Control of PV Systems under Partial Shading and Complex Partial Shading

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