A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems

Koad, Ramdan B. A.; Zobaa, Ahmed F.; El-Shahat, Adel

doi:10.1109/tste.2016.2606421

Cited by 275 publications

(126 citation statements)

References 18 publications

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“…where (Acc) is the acceleration ratio, SOC(0) indicates the initial state of charge, and a bat is the battery model factor. Equation (18) demonstrates that even the acceleration ratio is high, the needed power can increase. Therefore, the state of charge of the battery will decrease.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…40 In this work, the PSO-MPPT method has been chosen in order to compare it with IC-MPPT. This method was used in more than one application as shown in Koad et al 18 and Durand et al 41 The procedure of this method is given by Figure 7. After setting the PSO configuration, the algorithm will start searching the best duty cycle corresponding to the global best position of the ith particle.…”

Section: Pso-mpptmentioning

confidence: 99%

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The efficiency of PSO-based MPPT technique of an electric vehicle within the city

Kariem

Touti

Fetouh

2020

Measurement and Control

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Electrical vehicle fed by photovoltaic energy represents a complex system, which needs a high-performance control algorithm. Regarding the real situations, mostly the electric vehicle will be moving inside the city. If this system is covered by photovoltaic cells, the efficiency of this renewable energy source will depend on various factors. The shade areas or sunlight zones which exist in the city make the solar system unstable. Resolving this problem can increase the battery autonomy and allow addition of some running kilometers to the vehicle. Based on this objective, this study deals with the problem of solar variation and its influence on vehicle efficiency within the city. The problem is how to extract the maximum energy in this case. In order to maximize the global energy performance and increase vehicle autonomy, the optimal control method will be applied to this photovoltaic system taking into account some performance indicators such as the obtained power, the tracking speed, and the chattering level. Therefore, this study explores two control techniques in order to extract the maximum power from the solar energy system, which are the incremental method and the particle swarm optimization method. Simulink/MATLAB tool is used for simulation and comparison study based on the offered performance indicators. The obtained results show that the particle swarm optimization method has high global performance and an energy gain is obtained.

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Section: Mathematical Modelmentioning

confidence: 99%

Section: Pso-mpptmentioning

confidence: 99%

The efficiency of PSO-based MPPT technique of an electric vehicle within the city

Kariem

Touti

Fetouh

2020

Measurement and Control

View full text Add to dashboard Cite

show abstract

“…Persistent work is continuing in the development of MPPT innovations [2] to conquer disadvantages of previous algorithms. PSO algorithm for MPPT calculation is a proficient MPPT methods [3] for finest grabing of largest power from PV array.…”

Section: Introductionmentioning

confidence: 99%

PI and Fuzzy Controller Utilizing PV-HESS Based Zeta Converter for BLDC Motor Drive

Rajani*,

Seshadri,

Kumar

et al. 2020

IJRTE

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Due to speedy enfeeblement of finite resources in the early modern period of development, non conventional resources of energy, are being focused in various countries to reach the growing demand of electrical energy. Increased importance of non conventional energy in the auto mobile industry needs the use of brushless DC (BLDC) motor drives to fuel solar photo voltaic (PV). To overcome the disadvantages in the conservative DC-DC converters, Zeta converters are enterprising to optimize power processing. By regulating the duty cycle of the Zeta converter through particle swam optimization (PSO) we obtain the maximum power from PV array. To mitigate changes in output of PV, the Hybrid Energy Storage System (HESS) is implemented into the PV system to maintain a continuous voltage at the BLDC motor input. The robust power management algorithm controls the PV-HESS system .By keeping the power management of maximum power point tracking the Zeta converter can meet the trouble free performance of the system. The interpretation of the BLDC motor with zeta converter relic verified using proportional integral(pi) and fuzzy logic(FL) controller. Design method and parametric analysis is carried out in MATLAB simulation and results are validated. Keywords: Brushless DC motor (BLDC), Fuzzy logic(FL), Hybrid energy storage system(HESS), maximum power point (MPP), Proportional integral (PI),Solar Photo voltaic (SPV).

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“…The tracking performance of this method is established by experimental results. In [30], the algorithm computes the value of initial particles' dMPP (duty cycle at MPP) based on the voltage at maximum power. Therefore, the algorithm can start the optimization process with an initial value that is already close to the MPP.…”

Section: Introductionmentioning

confidence: 99%

Maximum Power Point Tracking Implementation by Dspace Controller Integrated Through Z-Source Inverter Using Particle Swarm Optimization Technique for Photovoltaic Applications

et al. 2018

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Maximum Power Point Tracking (MPPT) technique is used to extract maximum power from the photovoltaic system. This paper involves working on an enhanced Particle Swarm Optimization (PSO) based MPPT method for the photovoltaic (PV) system integrated through Z-Source inverter. The main benefit of the proposed method is the diminishing of the steady-state oscillation when the maximum power point (MPP) is located. Additionally, during an extreme environmental condition, such as partial shading and large fluctuations of irradiance and temperature, the proposed method has the capability to track the MPP. This algorithm is implemented in dspace 1104 controller. MATLAB simulations are carried out under varying irradiance and temperature conditions to evaluate its effectiveness. Its performance is compared with a conventional method like Perturb and observe (P&O) method.

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A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems

Cited by 275 publications

References 18 publications

The efficiency of PSO-based MPPT technique of an electric vehicle within the city

The efficiency of PSO-based MPPT technique of an electric vehicle within the city

PI and Fuzzy Controller Utilizing PV-HESS Based Zeta Converter for BLDC Motor Drive

Maximum Power Point Tracking Implementation by Dspace Controller Integrated Through Z-Source Inverter Using Particle Swarm Optimization Technique for Photovoltaic Applications

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