Maximum Power Point Tracking Strategies of Grid-Connected Wind Energy Conversion Systems

Eltamaly, Ali M.; Mohamed, Mohamed A.; Abo‐Khalil, Ahmed G.

doi:10.1007/978-3-030-64336-2_8

Cited by 9 publications

(4 citation statements)

References 61 publications

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“…In the literature, MPPT is a high-performance technology that regulates the output current and voltage of photovoltaic panels [42]. It estimates the optimal global electrical power point in real-time to efficiently transfer power to the battery or grid working with programmable device controls [43], [44].…”

Section: Integration Of Vrementioning

confidence: 99%

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

Tadjeddine,

Bendelhoum,

Bendjillali

et al. 2023

EAI Endorsed Trans Energy Web

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The Fluctuations in demand and weather conditions have a significant impact on the frequency and the voltage of Algeria's isolated PIAT power grid. To maintain stability and reliable power supply, it is crucial to keep these quantities close to their expected levels. An automatic (FRR) is employed to regulate real-time frequency deviations caused by integrating variable renewable energy (VRE), specifically wind and solar power in the Kabertene region. In order to mitigate wind power fluctuations, a power system stabilizer is implemented, which helps dampen oscillations. The use of Maximum Power Point Tracking (MPPT) techniques optimizes the extraction of power from solar panels under varying conditions. For efficient scheduling and dispatch of VRE generation, particle swarm optimization (PSO)-based algorithms are used. These algorithms ensure optimal utilization of renewable energy sources by considering their intermittent nature. This study proves the effectiveness of these techniques in enhancing grid stability, reducing frequency deviations, and improving VRE integration. Valuable insights are provided on their practical implementation, playing a crucial role in transitioning to a cleaner and more sustainable energy system.

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Section: Integration Of Vrementioning

confidence: 99%

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

Tadjeddine,

Bendelhoum,

Bendjillali

et al. 2023

EAI Endorsed Trans Energy Web

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“…Wind turbines transform the kinetic energy of the wind into electrical energy. Using Equation (4), [36][37][38] wind speeds obtained from anemometers at a certain height, h a , should be adapted to the hub height of WT. The power generated by WTs is heavily dependent on wind speed.…”

Section: Wind Energy System Modelingmentioning

confidence: 99%

“…The BESS life is calculated from Equation (18). The replacements of any component can be determined from Equation (37). This component's replacement cost may be calculated using Equation (38) and is equal to the total of all replacement costs that were discounted at the project's commencement.…”

Section: Replacement Costmentioning

confidence: 99%

A novel energy storage and demand side management for entire green smart grid system for NEOM city in Saudi Arabia

Eltamaly

2023

Energy Storage

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Hybrid renewable energy systems (HRES) are gaining high interest in supplying electric energy for remote communities. Energy storage systems (ESS) are utilized by green autonomous HRESs to accommodate the variability of renewable resources such as wind and solar energy systems. The lack of any traditional energy source is adding a great reliability challenge which should be compensated using expensive ESS. This challenge can be avoided by using a pumped hydro energy storage system (PHES) in harmony with batteries. The PHES is an excellent option to be used in NEOM city due to the perfect topographical characteristic of this site. The minimum cost of energy and the highest reliability is used as an objective for sizing the proposed entire green HRES. Using smart grid principles (SGP) and demand‐side management (DSM) in the design and operation stages will minimize system size and cost, which can result in a significant reduction in consumer bills. As a result, this paper introduces an innovative DSM based on a dynamic tariff. The suggested DSM technique was developed utilizing a unique fuzzy logic that takes into account the present and day‐ahead ESS situations to intelligently determine the ideal tariff for the lowest cost and maximum reliability of the HRES. This paper introduces a modified grey wolf optimization (MGWO) technique to shorten convergence time while preserving the best accuracy. The suggested MGWO is assessed against 10 swarm optimization techniques. The payback period of the project is 7 years. The findings acquired from this unique program demonstrated its superiority, with conversion times reduced by 22% to 80% when compared to previous optimization procedures. Furthermore, as compared to the flat rate pricing tariff, the usage of the dynamic tariff lowered the LCOE by 53%.

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“…The main idea of applying the maximum power point tracking (MPPT) algorithmes to wind turbines is maintaining the speed rotor angle at the optimum operating point at every wind speed [11][12][13]. This can be done by changing the rotation speed of the system as a function of the wind speed to vary the operating point on the power coefficient curve [14,15]. The MPPT methods developed vary in the technique used, complexity, necessary sensors, convergence speed, memory requirement, and efficiency range [16].…”

Section: Figure 1 Configuration Of a Wecs Based On Pmsgmentioning

confidence: 99%

Multiple Linear Regression Approach for Sensorless MPPT of PMSG Wind Power Generation Systems

Abo‐Khalil

Sobhy

Sayed

2022

Preprint

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In this paper, a novel approach for extracting the maximum power from a wind energy conversion system (WECS) eqquiped with a permanent magnet synchronous generator (PMSG) is presented. Wind power generation systems have gained prominence as an alternative to conventional power plants worldwide, being the renewable energy source with the best growth prospects. However, the intermittent nature of wind power reduces energy reliability and hinders the development of technologies in this area. Therefore, a sensorless controller for a WECS with a PMSG is developed to enhance the conversion efficiency of the wind enegy system. The proposed control algorithm predicts the wind speed from the wind turbine power-speed characteristics. It uses the predicted speed to determine the optimum reference rotating speed to extract the maximum power point (MPPT) based on the optimum tip-speed ratio. The proposed control approach is based on a multiple linear regression (MLR) algorithms which is used to predict the wind speed value by calculating the regression coefficients from the predetermined training samples of the turbine power, rotating speed, and wind speed. The MPPT operating mode is maintained as long as the available power is less than the rated power of the converter. Otherwise, the MPPT algorithm is disabled, and a mechanical power control loop guarantees nominal power. A complete theoretical analysis and the experimental results considering the prototype with the nominal power of the 3 kW wind turbine used are presented. The experimental results has proven the effectiveness and robustness of the proposed control approach.

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Maximum Power Point Tracking Strategies of Grid-Connected Wind Energy Conversion Systems

Cited by 9 publications

References 61 publications

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

VRE Integrating in PIAT grid with aFRR using PSS, MPPT, and PSO-based Techniques: A Case Study Kabertene

A novel energy storage and demand side management for entire green smart grid system for NEOM city in Saudi Arabia

Multiple Linear Regression Approach for Sensorless MPPT of PMSG Wind Power Generation Systems

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