A Maximum Power Point Tracking Technique for a Wind Power System Based on the Trapezoidal Rule

Pande, Jayshree; Nasikkar, Paresh

doi:10.3390/en16062799

Cited by 5 publications

(3 citation statements)

References 44 publications

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“…The technique presented in [41], [42] uses the trapezoidal rule with CPO to track the MPP for a solar photovoltaic system. The work in [43] has presented a three-step procedure: a P&O-based MPPT method for WECS using the trapezoidal rule (TRPO). The maximum values of power and reference voltage obtained after the application of the trapezoidal rule are passed on to further apply CPO to get the duty cycle, which is employed to track the MPP.…”

Section: A Nomenclaturementioning

confidence: 99%

An Ingenious Technique to Track the Maximum Power Point for a Wind Energy System

Pande,

Nasikkar,

Kotecha

et al. 2024

IEEE Access

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The conventional techniques employed for tracking maximum power suffer from several issues. The perturb and observe (P&O) algorithm is extremely popular among the conventional techniques for WECS to track and capture the maximum power point. The major issue with this algorithm is opting for an appropriate step size. A new technique is developed and described in this paper, which combines the trapezoidal rule and the fuzzy logic control technique, to address this issue. Two techniques are compared with the proposed algorithm: the trapezoidal rule-based P&O (TRPO) algorithm and the conventional P&O method to prove the superiority of the technique presented in this work. MATLAB/Simulink simulation showcases the enhancement of power by this technique. Randomly varying wind speeds were used to examine the power output of all three algorithms. The results obtained after simulation portray significant enhancement in DC output current, voltage, and power with considerable reduction in the oscillations by employing the proposed technique.

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Section: A Nomenclaturementioning

confidence: 99%

An Ingenious Technique to Track the Maximum Power Point for a Wind Energy System

Pande,

Nasikkar,

Kotecha

et al. 2024

IEEE Access

Self Cite

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“…Conversely, solar radiation presents a complex layer of uncertainties. The Beta distribution function proves to be an effective tool for modeling the PDF of these solar radiation variations [50]. The following equations represent the Weibull PDF of wind speed f (V w ) and the cumulative distribution function (CDF) F(V w ), respectively.…”

Section: Modeling Stochastic Wind/solar Power Along With the Associat...mentioning

confidence: 99%

Giant Trevally Optimization Approach for Probabilistic Optimal Power Flow of Power Systems Including Renewable Energy Systems Uncertainty

Hashish,

Hasanien,

Ullah

et al. 2023

Sustainability

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In this study, the Giant Trevally Optimizer (GTO) is employed to solve the probabilistic optimum power flow (P-OPF) issue, considering Renewable Energy Source (RES) uncertainties, achieving notable cost reduction. The objective function is established to minimize the overall generation cost, including the RES cost, which significantly surpassing existing solutions. The uncertain nature of the RES is represented through the employment of a Monte Carlo Simulation (MCS), strengthened by the K-means Clustering approach and the Elbow technique. Various cases are investigated, including various combinations of PV systems, WE systems, and both fixed and fluctuating loads. The study demonstrates that while considering the costs of solar, wind, or both might slightly increase the total generation cost, the cumulative generation cost remains significantly less than the scenario that does not consider the cost of RESs. The superior outcomes presented in this research underline the importance of considering RES costs, providing a more accurate representation of real-world system dynamics and enabling more effective decision making.

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“…The drawbacks can be addressed by adopting the followings: Variable, Adaptive, and hybrid step sizes concept [9]. The step size was calculated using trapezoidal rule in [38] which successfully reduce computational complexity of the algorithms and eliminated power oscillation at the MPP.…”

Section: Pandomentioning

confidence: 99%

Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems

Umar,

Alkawsi,

Jailani

et al. 2023

Processes

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As wind energy is widely available, an increasing number of individuals, especially in off-grid rural areas, are adopting it as a dependable and sustainable energy source. The energy of the wind is harvested through a device known as a wind energy harvesting system (WEHS). These systems convert the kinetic energy of wind into electrical energy using wind turbines (WT) and electrical generators. However, the output power of a wind turbine is affected by various factors, such as wind speed, wind direction, and generator design. In order to optimize the performance of a WEHS, it is important to track the maximum power point (MPP) of the system. Various methods of tracking the MPP of the WEHS have been proposed by several research articles, which include traditional techniques such as direct power control (DPC) and indirect power control (IPC). These traditional methods in the standalone form are characterized by some drawbacks which render the method ineffective. The hybrid techniques comprising two different maximum power point tracking (MPPT) algorithms were further proposed to eliminate the shortages. Furtherly, Artificial Intelligence (AI)-based MPPT algorithms were proposed for the WEHS as either standalone or integrated with the traditional MPPT methods. Therefore, this research focused on the review of the AI-based MPPT and their performances as applied to WEHS. Traditional MPPT methods that are studied in the previous articles were discussed briefly. In addition, AI-based MPPT and different hybrid methods were also discussed in detail. Our study highlights the effectiveness of AI-based MPPT techniques in WEHS using an artificial neural network (ANN), fuzzy logic controller (FLC), and particle swarm optimization (PSO). These techniques were applied either as standalone methods or in various hybrid combinations, resulting in a significant increase in the system’s power extraction performance. Our findings suggest that utilizing AI-based MPPT techniques can improve the efficiency and overall performance of WEHS, providing a promising solution for enhancing renewable energy systems.

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A Maximum Power Point Tracking Technique for a Wind Power System Based on the Trapezoidal Rule

Cited by 5 publications

References 44 publications

An Ingenious Technique to Track the Maximum Power Point for a Wind Energy System

An Ingenious Technique to Track the Maximum Power Point for a Wind Energy System

Giant Trevally Optimization Approach for Probabilistic Optimal Power Flow of Power Systems Including Renewable Energy Systems Uncertainty

Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems

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