General introduction to wind turbines

Zhao, Dan; Han, Nuomin; Goh, Ernest; Cater, John; Reinecke, Arne

doi:10.1016/b978-0-12-817135-6.00001-6

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…The aerodynamic shape influences the way the wind turbine captures energy, as well as the efficiency. However, wind turbines, up to this point in time, are unable to draw more energy than the Betz limit of 16/27, estimated at 59% [34,35]. This is due to the aerodynamic shape, no matter what type of generator is connected to the turbine.…”

Section: Wind Turbine Generationmentioning

confidence: 94%

“…The system follows a process to eliminate error reproduction from the previous prediction to the subsequent one. The process starts by deciding the significant information that we will keep for the next prediction and the one that we need to eliminate to avoid potential errors: this process is described by Equation (34). In fact, a value near to 0 needs to be eliminated and values near to 1 should be kept.…”

Section: Lstm Predictionmentioning

confidence: 99%

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Hybrid Renewable Production Scheduling for a PV–Wind-EV-Battery Architecture Using Sequential Quadratic Programming and Long Short-Term Memory–K-Nearest Neighbors Learning for Smart Buildings

Chakir,

Tabaa

2024

Sustainability

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Electricity demand in residential areas is generally met by the local low-voltage grid or, alternatively, the national grid, which produces electricity using thermal power stations based on conventional sources. These generators are holding back the revolution and the transition to a green planet, being unable to cope with climatic constraints. In the residential context, to ensure a smooth transition to an ecological green city, the idea of using alternative sources will offer the solution. These alternatives must be renewable and naturally available on the planet. This requires a generation that is very responsive to the constraints of the 21st century. However, these sources are intermittent and require a hybrid solution known as Hybrid Renewable Energy Systems (HRESs). To this end, we have designed a hybrid system based on PV-, wind-turbine- and grid-supported battery storage and an electric vehicle connected to a residential building. We proposed an energy management system based on nonlinear programming. This optimization was solved using sequential quadrature programming. The data were then processed using a long short-term memory (LSTM) model to predict, with the contribution and cooperation of each source, how to meet the energy needs of each home. The prediction was ensured with an accuracy of around 95%. These prediction results have been injected into K-nearest neighbors (KNN), random forest (RF) and gradient boost (GRU) repressors to predict the storage collaboration rates handled by the local battery and the electric vehicle. Results have shown an R2_score of 0.6953, 0.8381, and 0.739, respectively. This combination permitted an efficient prediction of the potential consumption from the grid with a value of an R²-score of around 0.9834 using LSTM. This methodology is effective in allowing us to know in advance the amount of energy of each source, storage, and excess grid injection and to propose the switching control of the hybrid architecture.

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Section: Wind Turbine Generationmentioning

confidence: 94%

Section: Lstm Predictionmentioning

confidence: 99%

Hybrid Renewable Production Scheduling for a PV–Wind-EV-Battery Architecture Using Sequential Quadratic Programming and Long Short-Term Memory–K-Nearest Neighbors Learning for Smart Buildings

Chakir,

Tabaa

2024

Sustainability

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Theoretical Investigation of Heat Production Feasibility by Means of Wind Mechanical Plants

Holovko

Volodimir²,

Mikola³

et al. 2021

INMATEH

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A widespread use of wind turbines can fully or partly provide energy for the consumers, but with due regards to certain investments and instability of energy generation. Technologies of using wind energy imply the conversion of the mechanical energy of a wind flow into the electrical or heat energy. The work is concerned with the estimation of the amount of heat in the process of heating liquid coolants and heat-transfer fluids when using wind mechanical plants. In the paper was made a numerical analysis of the temperature rise of the liquid which circulates in a closed loop of a gear-type pump, whose productivity is 3 l/m and which is driven by a wind turbine 5 kW of power capacity under a nominal wind speed of 7 m/s and under cycle duration of 2 s. The analysis showed that the temperature increased by 0.290 °К/s. If such wind speed is observed during one hour, the temperature of 100 kg of water will increase by 8.1°С. Heating of a heat-transfer fluid with a supply of mechanical energy to a working part can be achieved by a centrifugal fan. Assuming that the given process occurs without supplying and removing heat energy (it is adiabatic), for the capacity of 1.5 kW and under the revolution in a range of 1000….3000 r/m, the changes in temperature will range from 0.38 to 0.87 °К/s, but for the capacity of 7.5 kW and under 750 – 1500 r/m, the changes in temperature will range from 0.56 to 1.23 °К/s.

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General introduction to wind turbines

Cited by 2 publications

References 18 publications

Hybrid Renewable Production Scheduling for a PV–Wind-EV-Battery Architecture Using Sequential Quadratic Programming and Long Short-Term Memory–K-Nearest Neighbors Learning for Smart Buildings

Hybrid Renewable Production Scheduling for a PV–Wind-EV-Battery Architecture Using Sequential Quadratic Programming and Long Short-Term Memory–K-Nearest Neighbors Learning for Smart Buildings

Theoretical Investigation of Heat Production Feasibility by Means of Wind Mechanical Plants

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