Wind turbine power coefficient models based on neural networks and polynomial fitting

Carpintero-Rentería, Miguel; Santos-Martín, David; Lent, A.J.H. van; Ramos, Carlos

doi:10.1049/iet-rpg.2019.1162

Cited by 17 publications

(8 citation statements)

References 49 publications

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“…The efficiency of a wind turbine for extracting energy from incoming air flow is also referred to as the power coefficient of that wind turbine [86]. It is subject to a theoretical limit of 16/27 or 59.3%, known as the Betz limit [87,88] for conventional open wind turbines. However, this limit can be exceeded for ducted (shrouded) wind turbines [89,90], which is the case in SUTPPs.…”

Section: Discussionmentioning

confidence: 99%

Energy Generation Intensity (EGI) of Solar Updraft Tower (SUT) Power Plants Relative to CSP Plants and PV Power Plants Using the New Energy Simulator “Aladdin”

Marzouk

2024

Energies

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The current investigation provides information about solar updraft tower power plants, SUTPPs (also called solar chimney power plants, SCPPs), which form a unique method of solar-powered electricity production through a ducted wind turbine driven by induced airflow as a result of solar heating. The investigation is conducted using numerical modeling via the system-level simulation tool Aladdin (developed and released freely by the Institute for Future Intelligence, IFI) for solar energy systems, wind energy systems, or the built environment. The Aladdin energy simulator is first evaluated here by comparison with published experimental and numerical results corresponding to the historical 50 kW prototype SUTPP that was successfully tested in Manzanares (Spain) between 1982 and 1989. This prototype has a height of about 195 m for the chimney (the updraft tower) and a radius of about 122 m for the solar heat absorber (the solar air collector or the greenhouse). Next, various climate and performance characteristics are investigated and contrasted for nine different locations around the world with a similar latitude of 24°, which is within the sunbelt, assuming that the same Manzanares SUTPP prototype geometry is employed in these locations. These nine locations are Muscat (Oman), Al Jawf (Libya), Riyadh (Saudi Arabia), Karachi (Pakistan), Ahmedabad (India), Havana (Cuba), Culiacán (Mexico), Dhaka (Bangladesh), and Baise (China). The energy generation intensity (EGI) for the Manzanares-type solar updraft tower power plant in these nine examined locations was between 0.93 kWh/m2 per year (in Baise) and 2.28 kWh/m2 per year (in Muscat). Also, Muscat had the smallest seasonality index (maximum-to-minimum monthly electric output) of 1.90, while Baise had the largest seasonality index of 4.48. It was found that the main limitation of the overall SUTPP energy conversion efficiency is the chimney efficiency (the process of accelerating the air after entering the chimney). This study concludes that solar updraft towers (SUTs) cannot compete with existing mature and modular renewable energy alternatives, particularly photovoltaic (PV) panels, if the aimed use is commercial utility-scale electricity generation. Instead, SUTs may become attractive and achievable if viewed as hybrid-use projects by serving primarily as a large-scale greenhouse area for agricultural applications while secondarily allowing energy harvesting by generating clean (emissions-free) electricity from the incoming solar radiation heat.

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Section: Discussionmentioning

confidence: 99%

Energy Generation Intensity (EGI) of Solar Updraft Tower (SUT) Power Plants Relative to CSP Plants and PV Power Plants Using the New Energy Simulator “Aladdin”

Marzouk

2024

Energies

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“…here, ρ represents air density, R denotes blade length, v signifies wind speed, ω stands for angular speed, β represents the pitch angle, and C p is the power coefficient. Typically, this coefficient is expressed as an equivalent interpolated function obtained through model simulations or system identification [41]. In this article, the following expression for the power coefficient is utilized:…”

Section: Wind Turbine Modelmentioning

confidence: 99%

A Review of Fast Power-Reserve Control Techniques in Grid-Connected Wind Energy Conversion Systems

Dall’Asta,

Lazzarin

2024

Energies

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Grid-connected power-converter-interfaced systems have been sharing the responsibility of grid generation alongside conventional synchronous generators. However, these systems lack spinning reserves, leading to a decrease in system inertia and resulting in more pronounced frequency deviations during power imbalances. Therefore, grid codes require the active involvement of wind energy conversion systems in frequency control, aiming to constrain the frequency and rate of change of frequency variations within predefined limits. This paper reviews fast power-reserve control techniques without energy storage in wind energy conversion systems that do not depend on frequency or rate of change of frequency values. The resulting effects on system frequency, energy production, mechanical loadings, and electrical loadings are assessed. The techniques are classified in the maximum-power point-tracking region according to the power function during the transient response, such as constant, speed-, time-, or mechanical power-dependent methods. Both overproduction and underproduction stages are considered. Certain techniques are tested on simulation grids that include either hydro or no-reheat steam generators, followed by a comparative analysis.

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“…Its dependent on the tip speed ratio (λ) and pitch angle (β). Different techniques like exponential, sinusoidal, polynomial, or data-driven algorithms [7] can be used to model 𝐶 𝑝 . However, for this paper, this specific model will be used:…”

Section: Dynamic Modelling Of the Wind Turbinementioning

confidence: 99%

“…Update the parameter gain value 𝐾: 𝑲 = 𝑷(𝑖 − 1)𝝈 𝜇 + 𝝈 𝑇 𝑷(𝑖 − 1)𝝈 (7) Calculate the covariance matrix:…”

Section: Reference Tracking With Recursive Least Square With An Forge...mentioning

confidence: 99%

First Order Dynamic Sliding Mode Control of a Wind Turbine with Optimized Tip Speed Ratio

Padmanabhuni,

Pieper

2023

Proceedings of the 10th International Conference on Control, Dynamic Systems, and Robotics (CDSR 2023)

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This paper presents a novel sliding mode control method to enhance power generation from wind turbines, with a focus on power optimization. Generator torque only is used as an input since maximizing power using pitch and yaw control is not deemed worth decreasing the life of the turbine due to wear of the mechanical system. The controller is designed based on a 3rd-order model with rotor aerodynamic torque as a disturbance input. Simulation is done using a nonlinear wind turbine model. The first objective is to determine the optimal tip speed ratio for maximum power. To do this, Recursive Least Squares (RLS) is used to estimate a polynomial relating the Tip-Speed Ratio (TSR) and aerodynamic power coefficient. This gives the optimal operating point. To ensure that the system can adapt to changing environments, a forgetting factor is used. The second objective, a first-order dynamic sliding mode controller with integration (FODSMCI), is used to control the wind turbine and maintain it at the optimal TSR with good transient dynamics. The results show that the RLS with high forgetting factor is effective in determining the optimal TSR. FODSMCI allows the user to adjust trade-offs between controller performance and rotor speed tracking, resulting in a response without chattering.

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Wind turbine power coefficient models based on neural networks and polynomial fitting

Cited by 17 publications

References 49 publications

Energy Generation Intensity (EGI) of Solar Updraft Tower (SUT) Power Plants Relative to CSP Plants and PV Power Plants Using the New Energy Simulator “Aladdin”

Energy Generation Intensity (EGI) of Solar Updraft Tower (SUT) Power Plants Relative to CSP Plants and PV Power Plants Using the New Energy Simulator “Aladdin”

A Review of Fast Power-Reserve Control Techniques in Grid-Connected Wind Energy Conversion Systems

First Order Dynamic Sliding Mode Control of a Wind Turbine with Optimized Tip Speed Ratio

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