scholarly journals Supplying Baseload Power and Reducing Transmission Requirements by Interconnecting Wind Farms

2007 ◽  
Vol 46 (11) ◽  
pp. 1701-1717 ◽  
Author(s):  
Cristina L. Archer ◽  
Mark Z. Jacobson
Keyword(s):  
Wind Speed ◽  
Electric Power ◽  
Wind Power ◽  
Electric Energy ◽  
Wind Farms ◽  
Long Distance ◽  
Annual Average ◽  
Transmission Grid ◽  
Wind Speeds ◽  
Average Wind

Abstract Wind is the world’s fastest growing electric energy source. Because it is intermittent, though, wind is not used to supply baseload electric power today. Interconnecting wind farms through the transmission grid is a simple and effective way of reducing deliverable wind power swings caused by wind intermittency. As more farms are interconnected in an array, wind speed correlation among sites decreases and so does the probability that all sites experience the same wind regime at the same time. The array consequently behaves more and more similarly to a single farm with steady wind speed and thus steady deliverable wind power. In this study, benefits of interconnecting wind farms were evaluated for 19 sites, located in the midwestern United States, with annual average wind speeds at 80 m above ground, the hub height of modern wind turbines, greater than 6.9 m s−1 (class 3 or greater). It was found that an average of 33% and a maximum of 47% of yearly averaged wind power from interconnected farms can be used as reliable, baseload electric power. Equally significant, interconnecting multiple wind farms to a common point and then connecting that point to a far-away city can allow the long-distance portion of transmission capacity to be reduced, for example, by 20% with only a 1.6% loss of energy. Although most parameters, such as intermittency, improved less than linearly as the number of interconnected sites increased, no saturation of the benefits was found. Thus, the benefits of interconnection continue to increase with more and more interconnected sites.

scholarly journals The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality

2019 ◽  
Vol 4 (2) ◽  
pp. 343-353 ◽  
Author(s):  
Tyler C. McCandless ◽  
Sue Ellen Haupt
Keyword(s):  
Machine Learning ◽  
Standard Deviation ◽  
Wind Speed ◽  
Wind Power ◽  
Power Conversion ◽  
Jensen’S Inequality ◽  
Jensen's Inequality ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Abstract. Wind power is a variable generation resource and therefore requires accurate forecasts to enable integration into the electric grid. Generally, the wind speed is forecast for a wind plant and the forecasted wind speed is converted to power to provide an estimate of the expected generating capacity of the plant. The average wind speed forecast for the plant is a function of the underlying meteorological phenomena being predicted; however, the wind speed for each turbine at the farm is also a function of the local terrain and the array orientation. Conversion algorithms that assume an average wind speed for the plant, i.e., the super-turbine power conversion, assume that the effects of the local terrain and array orientation are insignificant in producing variability in the wind speeds across the turbines at the farm. Here, we quantify the differences in converting wind speed to power at the turbine level compared with a super-turbine power conversion for a hypothetical wind farm of 100 2 MW turbines as well as from empirical data. The simulations with simulated turbines show a maximum difference of approximately 3 % at 11 m s−1 with a 1 m s−1 standard deviation of wind speeds and 8 % at 11 m s−1 with a 2 m s−1 standard deviation of wind speeds as a consequence of Jensen's inequality. The empirical analysis shows similar results with mean differences between converted wind speed to power and measured power of approximately 68 kW per 2 MW turbine. However, using a random forest machine learning method to convert to power reduces the error in the wind speed to power conversion when given the predictors that quantify the differences due to Jensen's inequality. These significant differences can lead to wind power forecasters overestimating the wind generation when utilizing a super-turbine power conversion for high wind speeds, and indicate that power conversion is more accurately done at the turbine level if no other compensatory mechanism is used to account for Jensen's inequality.

scholarly journals Seasonality, Interannual Variability, and Linear Tendency of Wind Speeds in the Northeast Brazil from 1986 to 2011

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Alexandre Torres Silva dos Santos ◽  
Cláudio Moisés Santos e Silva
Keyword(s):  
Wind Speed ◽  
Interannual Variability ◽  
Trend Analysis ◽  
Wind Power Generation ◽  
Northeast Brazil ◽  
Annual Average ◽  
Wind Speeds ◽  
Wind Circulation ◽  
Average Wind ◽  
Weather Stations

Wind speed analyses are currently being employed in several fields, especially in wind power generation. In this study, we used wind speed data from records of Universal Fuess anemographs at an altitude of 10 m from 47 weather stations of the National Institute of Meteorology (Instituto Nacional de Meteorologia-INMET) from January 1986 to December 2011. The objective of the study was to investigate climatological aspects and wind speed trends. To this end, the following methods were used: filling of missing data, descriptive statistical calculations, boxplots, cluster analysis, and trend analysis using the Mann-Kendall statistical method. The seasonal variability of the average wind speeds of each group presented higher values for winter and spring and lower values in the summer and fall. The groups G1, G2, and G5 showed higher annual averages in the interannual variability of wind speeds. These observed peaks were attributed to the El Niño and La Niña events, which change the behavior of global wind circulation and influence wind speeds over the region. Trend analysis showed more significant negative values for the G3, G4, and G5 groups for all seasons of the year and in the annual average for the period under study.

scholarly journals The Super-Turbine Wind Power Conversion Paradox: Using Machine Learning to Reduce Errors Caused by Jensen’s Inequality

2019 ◽  
Author(s):  
Tyler C. McCandless ◽  
Sue Ellen Haupt
Keyword(s):  
Machine Learning ◽  
Standard Deviation ◽  
Wind Speed ◽  
Wind Power ◽  
Power Conversion ◽  
Jensen’S Inequality ◽  
Jensen's Inequality ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Abstract. Wind power is a variable generation resource and therefore requires accurate forecasts to enable integration into the electric grid. Generally, the wind speed is forecast for a wind plant and the forecasted wind speed is converted to power to provide an estimate of the expected generating capacity of the plant. The average wind speed forecast for the plant is a function of the underlying meteorological phenomena being predicted; however, the wind speed for each turbine at the farm is also a function of the local terrain and the array orientation. Conversion algorithms that assume an average wind speed for the plant, i.e., the super-turbine power conversion, assume that the effects of the local terrain and array orientation are insignificant in producing variability in the wind speeds across the turbines at the farm. Here, we quantify the differences in converting wind speed to power at the turbine level compared to a super-turbine power conversion for a hypothetical wind farm of 100 2-MW turbines as well as from empirical data. The simulations with simulated turbines show a maximum difference of approximately 3 % at 11 m s−1 with 1 m s−1 standard deviation of wind speeds and 8 % at 11 m s−1 with 2 m s−1 standard deviation of wind speeds as a consequence of Jensen’s Inequality. The empirical analysis shows similar results with mean differences between converted wind speed to power and measured power of approximately 68 kW per 2 MW turbine. However, using a random forest machine learning method to convert to power reduces the error in the wind speed to power conversion when given the predictors that quantify the differences due to Jensen’s Inequality. These significant differences can lead to wind power forecasters over-estimating the wind generation when utilizing a super-turbine power conversion for high wind speeds, and indicates that power conversion is more accurately done at the turbine level if no other compensatory mechanism is used to account for Jensen’s Inequality.

scholarly journals Wind speed analysis based on the logarithmic wind shear model: a case study for some brazilian cities

2020 ◽  
Vol 9 (7) ◽  
pp. e298973984
Author(s):  
Anny Key de Souza Mendonça ◽  
Antonio Cezar Bornia
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Wind Shear ◽  
Wind Farms ◽  
Shear Model ◽  
The Public ◽  
Wind Speeds ◽  
Generating Capacity ◽  
Mean Wind Speed ◽  
The Mean

The wind power’ share in electricity generating capacity has increased significantly in recent years. Due to the variability in wind power generation, given the variations in wind speed and considering the increase in wind participation in the Brazilian energy matrix, a fact that reinforces the relevance of the source, this article aims to present the methods used to analyze the wind speed more used in the literature and to analyze the wind speed in several Brazilian cities. The logarithmic wind shear model was used to analyze mean wind speeds based on historical data of twelve Brazilian cities available to the public on the ESRL database for a period of eight years 2010 to 2018. The study showed that in localities such as Uruguaiana/RS, Campo Grande/MS, Uberlândia/MG, São Luiz/MA and Corumba/MS, mean wind speeds are strong in all altitudes of reference, with a gain of ± 2m/s of wind speed as the operational altitude increases. The logarithmic wind gain in high altitudes or low altitudes can be seen in z = 100 meters, where the mean wind speed found was Wn ≈ 8 m/s in Uruguaiana/RS and Campo Grande/MS, whereas in Manaus it was Wn ≈ 5 m/s. In Porto Alegre (RS), Florianópolis (SC), Curitiba/PR and Brasília/DF, the mean wind speed in altitudes ≥ 250 m becomes significant, allowing the implementation of wind farms if the technology proves to be economically feasible.

A Study of Estimation of Wind Potential and Prediction of Grid-Connected Wind Power Development in Vietnam

2020 ◽  
Vol 11 (2) ◽  
pp. 27-37
Author(s):  
Co Xuan Hoang ◽  
Linh Thi Hai Dang ◽  
Da Van Ta ◽  
Cuong Manh Dinh ◽  
Chinh Van Kim ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Power Plants ◽  
Wind Farms ◽  
Ground Level ◽  
Correlation Equation ◽  
Electricity Production ◽  
Average Wind Speed ◽  
Average Wind ◽  
Wind Potential

The construction of grid-connected wind power plants has increased sharply in Vietnam due to the rapid rise of energy demands. Previous studies of wind energy have shown that the wind potential of Vietnam compared to other countries of Southeast Asia and examined wind speed levels of each region of Vietnam. In this study, the annual electricity production (AEP), which is an important factor of project's cost and benefit calculation, was calculated for 13 study areas. A correlation equation between AEP and the average wind speed at 60m above ground level was also developed to estimate AEP where there exists only data of the annual average wind speed. Moreover, other resources of the development of grid-connected wind power were discussed in this research such as the Vietnamese supporting mechanism, international co-operation, turbine technology development, etc. The article then predicts the trend, and proposes some recommendations of developing grid-connected wind farms in Vietnam.

scholarly journals Selection of design structure and method of energy transformation in wind power plant

2019 ◽  
Vol 298 ◽  
pp. 00124
Author(s):  
Andrey Pushkarev ◽  
Dmitriy Khvorenkov ◽  
Olga Varfolomeeva ◽  
Mikhail Dyagelev ◽  
Ivan Pushkarev
Keyword(s):  
Wind Speed ◽  
Power Plant ◽  
Wind Power ◽  
High Efficiency ◽  
Electric Energy ◽  
Spin Axis ◽  
Wind Power Plant ◽  
Friction Forces ◽  
Wind Speeds ◽  
Design Structure

The purpose of the work is to select the design concept of the wind power plant and the method of transformation of mechanical wind energy into electric energy depending on the wind speed in the given area. In order to solve the first task, it is proposed to approximate the distribution of wind speed with the help of the Raleigh Law, to use incomplete gamma functions and to compare the average annual power of wind plants with the vertical and horizontal spin axis. At low wind speeds dependence of wind plant mass with vertical spin axis with different types of generators is analyzed. The multiplication unit design is selected. Friction forces are determined in planetary multiplication unit having high efficiency. The effect of these forces on wind power plant efficiency is analyzed.

scholarly journals STUDY OF EFFECTIVE OMNI-DIRECTIONAL VERTICAL AXIS WIND TURBINE FOR LOW SPEED REGIONS

2021 ◽  
Vol 22 (2) ◽  
pp. 149-160
Author(s):  
Alisher Safarov ◽  
Rasul Mamedov
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
Experimental Studies ◽  
Vertical Axis ◽  
Power Device ◽  
Vertical Axis Wind Turbine ◽  
Average Wind Speed ◽  
Matlab Simulink ◽  
Wind Speeds ◽  
Average Wind

This article presents theoretical and experimental studies of an improved vertical axis wind power device that generates electricity in areas with an average wind speed of 3.5-4.5 m/s. An algorithm has been developed for determining the geometrically optimal dimensions of the outer guiding surfaces to improve the efficiency of the device at low wind speeds. The device uses an AFPMG generator with opposite rotation of the stator and rotor. Matlab/Simulink and Solidworks were used to develop a mathematical and physical model of the wind power device. According to the results of the study, it was found that the developed wind power device can reach a rated power of 700 W at a wind speed of 8 m/s. The use of the device in areas with low wind speed is based on the possibility of increasing the efficiency of work by 5-10% at an average wind speed lower than that of other types of wind power devices. ABSTRAK: Artikel ini memaparkan kajian teori dan eksperimen berkenaan alat kuasa angin paksi menegak yang diperbaharui dan menghasilkan tenaga elektrik di kawasan kelajuan angin berpurata 3.5-4.5 m/s. Algoritma telah dibangunkan bagi menentukan dimensi optimum geometri permukaan berpandu luar dalam meningkatkan kecekapan peranti pada kelajuan angin yang kurang. Peranti ini menggunakan penjana AFPMG dengan putaran stator dan rotor yang berlawanan. Matlab/Simulink dan Solidworks digunakan bagi menghasilkan model matematik dan fizikal peranti tenaga angin. Berdasarkan dapatan kajian, didapati bahawa alat tenaga angin yang dibangunkan ini dapat mencapai daya kuasa sebanyak 700 W pada kecepatan angin 8 m/s. Penggunaan alat ini di kawasan kurang kelajuan angin berkemungkinan meningkatkan efisiensi purata kerja sebanyak 5-10% pada kelajuan angin rendah, iaitu lebih rendah daripada segala jenis peranti tenaga angin lain.

SHAPING OF AN AUTONOMOUS POWER SYSTEM FOR GUARANTEED POWER SUPPLY WITH THE PREDOMINANCE WIND ENERGY

2018 ◽  
pp. 28-50
Author(s):  
S. G. Ignatiev ◽  
S. V. Kiseleva
Keyword(s):  
Energy Storage ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Demand ◽  
Diesel Generator ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Optimization of the autonomous wind-diesel plants composition and of their power for guaranteed energy supply, despite the long history of research, the diversity of approaches and methods, is an urgent problem. In this paper, a detailed analysis of the wind energy characteristics is proposed to shape an autonomous power system for a guaranteed power supply with predominance wind energy. The analysis was carried out on the basis of wind speed measurements in the south of the European part of Russia during 8 months at different heights with a discreteness of 10 minutes. As a result, we have obtained a sequence of average daily wind speeds and the sequences constructed by arbitrary variations in the distribution of average daily wind speeds in this interval. These sequences have been used to calculate energy balances in systems (wind turbines + diesel generator + consumer with constant and limited daily energy demand) and (wind turbines + diesel generator + consumer with constant and limited daily energy demand + energy storage). In order to maximize the use of wind energy, the wind turbine integrally for the period in question is assumed to produce the required amount of energy. For the generality of consideration, we have introduced the relative values of the required energy, relative energy produced by the wind turbine and the diesel generator and relative storage capacity by normalizing them to the swept area of the wind wheel. The paper shows the effect of the average wind speed over the period on the energy characteristics of the system (wind turbine + diesel generator + consumer). It was found that the wind turbine energy produced, wind turbine energy used by the consumer, fuel consumption, and fuel economy depend (close to cubic dependence) upon the specified average wind speed. It was found that, for the same system with a limited amount of required energy and high average wind speed over the period, the wind turbines with lower generator power and smaller wind wheel radius use wind energy more efficiently than the wind turbines with higher generator power and larger wind wheel radius at less average wind speed. For the system (wind turbine + diesel generator + energy storage + consumer) with increasing average speed for a given amount of energy required, which in general is covered by the energy production of wind turbines for the period, the maximum size capacity of the storage device decreases. With decreasing the energy storage capacity, the influence of the random nature of the change in wind speed decreases, and at some values of the relative capacity, it can be neglected.

scholarly journals Analysis of Performance of the Wind-Driven Pulverizing Aerator Based on Average Wind Speeds in the Conditions of Góreckie Lake

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2796
Author(s):  
Andrzej Osuch ◽  
Ewa Osuch ◽  
Stanisław Podsiadłowski ◽  
Piotr Rybacki
Keyword(s):  
Mathematical Model ◽  
Wind Speed ◽  
Water Pump ◽  
Average Wind Speed ◽  
Flow Rates ◽  
Wind Speeds ◽  
Average Wind ◽  
Flow Through ◽  
Analysis Of Performance ◽  
Research Period

In the introduction to this paper, the characteristics of Góreckie lake and the construction and operation of the wind-driven pulverizing aerator are presented. The purpose of this manuscript is to determine the efficiency of the pulverizing aerator unit in the windy conditions of Góreckie Lake. The efficiency of the pulverization aerator depends on the wind conditions at the lake. It was necessary to conduct thorough research to determine the efficiency of water flow through the pulverization segment (water pump). It was necessary to determine the rotational speed of the paddle wheel, which depended on the average wind speed. Throughout the research period, measurements of hourly average wind speed were carried out. It was possible to determine the efficiency of the machine by developing a dedicated mathematical model. The latest method was used in the research, consisting of determining the theoretical volumetric flow rates of water in the pulverizing aerator unit, based on average hourly wind speeds. Pulverization efficiency under the conditions of Góreckie Lake was determined based on 6600 average wind speeds for spring, summer and autumn, 2018. Based on the model, the theoretical efficiency of the machine was calculated, which, under the conditions of Góreckie Lake, amounted to 75,000 m3 per year.

scholarly journals Optimization of a Small Wind Power Plant for Annual Wind Speed Distribution

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1587
Author(s):  
Krzysztof Wrobel ◽  
Krzysztof Tomczewski ◽  
Artur Sliwinski ◽  
Andrzej Tomczewski
Keyword(s):  
Wind Speed ◽  
Power Plant ◽  
Wind Power ◽  
Power Plants ◽  
Control Method ◽  
Wind Power Plant ◽  
Switched Reluctance ◽  
Wind Speeds ◽  
Wind Speed Distribution ◽  
And Control

This article presents a method to adjust the elements of a small wind power plant to the wind speed characterized by the highest annual level of energy. Tests were carried out on the basis of annual wind distributions at three locations. The standard range of wind speeds was reduced to that resulting from the annual wind speed distributions in these locations. The construction of the generators and the method of their excitation were adapted to the characteristics of the turbines. The results obtained for the designed power plants were compared with those obtained for a power plant with a commercial turbine adapted to a wind speed of 10 mps. The generator structure and control method were optimized using a genetic algorithm in the MATLAB program (Mathworks, Natick, MA, USA); magnetostatic calculations were carried out using the FEMM program; the simulations were conducted using a proprietary simulation program. The simulation results were verified by measurement for a switched reluctance machine of the same voltage, power, and design. Finally, the yields of the designed generators in various locations were determined.

Sign in / Sign up

Export Citation Format

Share Document