Improved frequency control from wind power plants considering wind speed variation

2016 ◽  
Author(s):  
Jayachandra N. Sakamuri ◽  
Kaushik Das ◽  
Mufit Altin ◽  
Nicolaos A. Cutululis ◽  
Anca D. Hansen ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Power Plants ◽  
Frequency Control ◽  
Speed Variation ◽  
Wind Power Plants

Wind Speed Forecasting Based on FNN in Wind Farm

2014 ◽  
Vol 651-653 ◽  
pp. 1117-1122
Author(s):  
Zheng Ning Fu ◽  
Hong Wen Xie
Keyword(s):  
Neural Network ◽  
Wind Speed ◽  
Power Systems ◽  
Wind Power ◽  
Power Plants ◽  
Fuzzy Neural Network ◽  
Negative Impact ◽  
Wind Speed Forecasting ◽  
Wind Power Plants ◽  
Fuzzy Neural

Wind speed forecasting plays a significant role to the operation of wind power plants and power systems. An accurate forecasting on wind power can effectively relieve or avoid the negative impact of wind power plants on power systems and enhance the competition of wind power plants in electric power market. Based on a fuzzy neural network (FNN), a method of wind speed forecasting is presented in this paper. By mining historical data as the learning stylebook, the fuzzy neural network (FNN) forecasts the wind speed. The simulation results show that this method can improve the accuracy of wind speed forecasting effectively.

Coordinated Frequency Control Using MT-HVDC Grids With Wind Power Plants

2016 ◽  
Vol 7 (1) ◽  
pp. 213-220 ◽  
Author(s):  
Fernando D. Bianchi ◽  
Jose Luis Dominguez-Garcia
Keyword(s):  
Wind Power ◽  
Power Plants ◽  
Frequency Control ◽  
Wind Power Plants

Short-Term Power Fluctuations of Large Wind Power Plants*

2002 ◽  
Vol 124 (4) ◽  
pp. 427-431 ◽  
Author(s):  
Yih-huei Wan ◽  
Demy Bucaneg,
Keyword(s):  
Wind Speed ◽  
Power Systems ◽  
Wind Power ◽  
Power Plants ◽  
Power Level ◽  
Short Term ◽  
Wind Power Plants ◽  
Weather Events ◽  
Power Fluctuations ◽  
Large Wind

To evaluate short-term wind power fluctuations and their impact on electric power systems, the National Renewable Energy Laboratory, in cooperation with Enron Wind, has started a project to record output power from several large commercial wind power plants at the 1-Hertz rate. This paper presents statistical properties of the data collected so far and discusses the results of data analysis. From the available data, we can already conclude that despite the stochastic nature of wind power fluctuations, the magnitudes and rates of wind power changes caused by wind speed variations are seldom extreme, nor are they totally random. Their values are bounded in narrow ranges. Power output data also show significant spatial variations within a large wind power plant. The data also offer encouraging evidence that accurate wind power forecasting is feasible. To the utility system, large wind power plants are not really random burdens. The narrow range of power level step changes provides a lot of information with which system operators can make short-term predictions of wind power. Large swings of wind power do occur, but those infrequent large changes (caused by wind speed changes) are always related to well-defined weather events, most of which can be accurately predicted in advance.

Wind speed trends and the potential of electricity generation at new wind power plants in Northeast Brazil

2021 ◽  
Vol 43 (4) ◽  
Author(s):  
Amanda Ribeiro de Andrade ◽  
Victor Felipe Moura Bezerra Melo ◽  
Daisy Beserra Lucena ◽  
Raphael Abrahão
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Electricity Generation ◽  
Power Plants ◽  
Northeast Brazil ◽  
Wind Power Plants

scholarly journals Development of Nonlinear Optimization Models for Wind Power Plants Using Box-Behnken Design of Experiment: A Case Study for Turkey

2020 ◽  
Vol 12 (15) ◽  
pp. 6017
Author(s):  
Yasemin Ayaz Atalan ◽  
Mete Tayanç ◽  
Kamil Erkan ◽  
Abdulkadir Atalan
Keyword(s):  
Wind Speed ◽  
Nonlinear Optimization ◽  
Wind Power ◽  
Design Of Experiment ◽  
Power Plants ◽  
Energy Output ◽  
Optimization Models ◽  
Box Behnken Design ◽  
Wind Power Plants ◽  
The Future

This study aims to develop an optimization model for obtaining the maximum benefit from wind power plants (WPPs) to help with reducing external dependence in terms of energy. In this sense, design of experiment and optimization methods are comprehensively combined in the wind energy field for the first time. Existing data from installed WPPs operating in Turkey for the years of 2017 and 2018 are analyzed. Both the individual and interactive effects of controllable factors, namely turbine power (MW), hub height (m) and rotor diameter (m), and uncontrollable factor as wind speed (m/s) on WPPs are investigated with the help of Box-Behnken design. Nonlinear optimization models are utilized to estimate optimum values for each decision variable in order to maximize the amount of energy to be produced for the future. Based on the developed nonlinear optimization models, the optimum results with high desirability value (0.9587) for the inputs of turbine power, hub height, rotor diameter and wind speed are calculated as 3.0670 MW, 108.8424 m, 106.7597 m, and 6.1684 m/s, respectively. The maximum energy output with these input values is computed as 9.952 million kWh per unit turbine, annually. The results of this study can be used as a guideline in the design of new WPPs to produce the maximum amount of energy contributing to supply escalating energy needs by more sustainable and clean ways for the future.

Sign in / Sign up

Export Citation Format

Share Document