Jellyfish Search Algorithm for MPPT in Photovoltaic Systems Under Partial Shading Conditions

Karthikeyan, M.; Manimegalai, D.

doi:10.1142/s021947752350013x

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…The first part of the composite control is the WBOA search process, and the second part is the variablestep P&O tracking process. [12] The control schematic is shown in Fig. 3.…”

Section: Composite Control Strategymentioning

confidence: 99%

Multi-peak MPPT Control Based on Variable Step Disturbance Observation Method and Butterfly Optimization Algorithm

2023

jeis

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Photovoltaic power generation has attracted more and more attention in the field of new energy applications, and the maximum power point tracking technology is the critical link of the photovoltaic power generation system. In the case of partial shading, the output power curve of the photovoltaic array presents a multi-peak phenomenon, and the traditional MPPT algorithm is easy to fall into the optimal local solution when tracking the maximum power, while the traditional butterfly algorithm has slow convergence and low optimization accuracy in the tracking process. In order to reduce the loss of output power of photovoltaic system, an MPPT control method combining butterfly algorithm with adaptive inertia weight and variable step size disturbance observation method is proposed. In the butterfly algorithm, the population randomly generates the initial solution, and the crossover mutation operation is carried out on the population. The inertia weight is constantly updated with the increase of iteration times, which can reduce the oscillation amplitude in the tracking process, increase the robustness of the algorithm search, and achieve the purpose of global search. Then, the perturbation observation method with variable step size is used to accelerate the convergence speed and accuracy. The simulation results show that compared with the traditional perturbation observation method and butterfly optimization algorithm, the proposed algorithm can find the maximum power point stably, quickly, and accurately in the case of sudden illumination change, which significantly improves the performance of MPPT.

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“…The first part of the composite control is the WBOA search process, and the second part is the variablestep P&O tracking process. [12] The control schematic is shown in Fig. 3.…”

Section: Composite Control Strategymentioning

confidence: 99%

Multi-peak MPPT Control Based on Variable Step Disturbance Observation Method and Butterfly Optimization Algorithm

2023

jeis

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“…Through the coordinated control among power generation units, energy storage units and load units in photovoltaic buildings [1][2][3], their internal laws are locally optimized, and the characteristics of electric load fluctuation are formed, which provides a guarantee for the optimization of distributed photovoltaic utilization rate [4][5][6] . This paper analyzes the load variation trend of distributed photovoltaic power generation by mining the load characteristics, which can ensure the stable operation of the power grid and the peak-shaving dispatching effect of the building complex.…”

Section: Introductionmentioning

confidence: 99%

Design of distributed photovoltaic utilization optimization method for large buildings considering load deviation and fluctuation characteristics mining algorithms

Huo,

Wang

2024

Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023)

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The conventional optimization method of distributed photovoltaic utilization ratio is mainly based on demand response optimization, and the load difference between peak load and trough load in buildings is large, which affects the optimization effect of photovoltaic utilization ratio. Therefore, an optimization method of distributed photovoltaic utilization rate of large buildings considering the mining algorithm of load deviation and fluctuation characteristics is designed. The load fluctuation characteristics of distributed photovoltaic power supply in buildings are excavated, and the load sequence of distributed photovoltaic power supply is analyzed, so that the load sequence is transformed into a stationary sequence to meet the stable power supply demand of buildings. Based on the load deviation degree, the peak load of distributed photovoltaic power supply in large buildings is balanced. By analyzing the peak load of distributed photovoltaic power supply in buildings, the load of building photovoltaic wiring is transferred reasonably, so as to optimize the load utilization ratio of photovoltaic equipment. Comparative experiments show that the optimization effect of this method is better and can be applied to real life.

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Jellyfish Search Algorithm for MPPT in Photovoltaic Systems Under Partial Shading Conditions

Cited by 2 publications

References 15 publications

Multi-peak MPPT Control Based on Variable Step Disturbance Observation Method and Butterfly Optimization Algorithm

Multi-peak MPPT Control Based on Variable Step Disturbance Observation Method and Butterfly Optimization Algorithm

Design of distributed photovoltaic utilization optimization method for large buildings considering load deviation and fluctuation characteristics mining algorithms

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