Multi-Stage Optimization of Wind Farms With Limiting Factors

2013 ◽  
Author(s):  
Bryony L. DuPont ◽  
Jonathan Cagan
Keyword(s):  
Wind Farm ◽  
Solution Space ◽  
Wind Farms ◽  
Objective Evaluation ◽  
Pattern Search ◽  
Limiting Factors ◽  
Limiting Factor ◽  
Test Case ◽  
Wind Speeds ◽  
Multi Stage

Larger onshore wind farms are often installed in phases, with discrete smaller sub-farms being installed and becoming operational in succession until the farm as a whole is completed. An extended pattern search (EPS) algorithm that selects both local turbine position and geometry is presented that enables the installation of a complete farm in discrete stages, exploring optimality of both incremental sub-farm solutions and the completed project as a whole. The objective evaluation is the maximization of profit over the life of the farm, and the EPS uses modeling of cost based on an extensive cost analysis by the National Renewable Energy Laboratory (NREL). The EPS uses established wake modeling to calculate the power development of the farm, and allows for the consideration of multiple or overlapping wakes. A limiting factor is used to determine the size of wind farm stages: optimization stages based on the number of turbines currently available for development (representative of limitations in initial capital, which is commonly encountered in wind farm stage development). Two wind test cases are considered: a unidirectional test case with constant wind speed and a single wind direction, and a multidirectional test case, with three wind speeds and a defined probability of occurrence for each. The test case shown in the current work is employed on a 4000 km by 4000 km solution space. In addition, two different methods are performed: the first uses the optimal layout of a complete farm and then systematically “removes” turbines to create smaller sub-farms; the second uses a weighted multi-objective optimization over sequential, adjacent land that concurrently optimizes each sub-farm and the complete farm. The exploration of these resulting layouts indicates the value of full-farm optimization (in addition to optimization of the individual stages) and gives insight into how to approach optimality in sub-farm stages. The behavior exhibited in these tests cases suggests a heuristic that can be employed by wind farm developers to ensure that multi-stage wind farms perform at their peak throughout their completion.

An Extended Pattern Search Method for Offshore Floating Wind Layout and Turbine Geometry Optimization

2016 ◽  
Author(s):  
Caitlin Forinash ◽  
Bryony DuPont
Keyword(s):  
Wind Farm ◽  
Cost Model ◽  
Geometry Optimization ◽  
Interaction Model ◽  
Solution Space ◽  
Wind Farms ◽  
Power Production ◽  
Pattern Search ◽  
Offshore Wind ◽  
Extended Pattern Search

An Extended Pattern Search (EPS) method is developed to optimize the layout and turbine geometry for offshore floating wind power systems. The EPS combines a deterministic pattern search with stochastic extensions. Three advanced models are incorporated: (1) a cost model considering investment and lifetime costs of a floating offshore wind farm comprised of WindFloat platforms; (2) a wake propagation and interaction model able to determine the reduced wind speeds downstream of rotating blades; and (3) a power model to determine power produced at each rotor, and includes a semi-continuous, discrete turbine geometry selection to optimize the rotor radius and hub height of individual turbines. The objective function maximizes profit by minimizing cost, minimizing wake interactions, and maximizing power production. A multidirectional, multiple wind speed case is modeled which is representative of real wind site conditions. Layouts are optimized within a square solution space for optimal positioning and turbine geometry for farms containing a varying number of turbines. Resulting layouts are presented; optimized layouts are biased towards dominant wind directions. Preliminary results will inform developers of best practices to include in the design and installation of offshore floating wind farms, and of the resulting cost and power production of wind farms that are computationally optimized for realistic wind conditions.

About the Extension of Wind Turbine Power Curve in the High Wind Region

2018 ◽  
Vol 141 (1) ◽  
Author(s):  
Davide Astolfi ◽  
Francesco Castellani ◽  
Andrea Lombardi ◽  
Ludovico Terzi
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Test Case ◽  
Power Curve ◽  
High Wind ◽  
High Wind Speed ◽  
Wind Speeds

The financial sustainability and the profitability of wind farms strongly depend on the efficiency of the conversion of wind kinetic energy. This motivates further research about the improvement of wind turbine power curve. If the site is characterized by a considerable occurrence of very high wind speeds, it can become particularly profitable to update the power curve management. This is commonly done by raising the cut-out velocity and the high wind speed cut-in regulating the hysteresis logic. Doing this, on one side, the wind turbine possibly undergoes strong vibration and loads. On the other side, the energy improvement is almost certain and the point is quantifying precisely its magnitude. In this work, the test case of an onshore wind farm in Italy is studied, featuring 17 2.3 MW wind turbines. Through the analysis of supervisory control and data acquisition (SCADA) data, the energy improvement from the extension of the power curve in the high wind speed region is simulated and measured. This could be useful for wind farm owners evaluating the realistic profitability of the installation of the power curve upgrade on their wind turbines. Furthermore, the present work is useful for the analysis of wind turbine behavior under extremely stressing load conditions.

scholarly journals Analysis of offshore wind farm located on Baltic Sea

2019 ◽  
Vol 137 ◽  
pp. 01049
Author(s):  
Anna Sobotka ◽  
Kajetan Chmielewski ◽  
Marcin Rowicki ◽  
Justyna Dudzińska ◽  
Przemysław Janiak ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
The European Union ◽  
European Union Policy ◽  
Offshore Wind Farms ◽  
Wind Speeds ◽  
Wind Measurements ◽  
The Baltic

Poland is currently at the beginning of the energy transformation. Nowadays, most of the electricity generated in Poland comes from coal combustion. However, in accordance to the European Union policy of reducing the emission of carbon dioxide to the atmosphere, there are already plans to switch to low-emission energy sources in Poland, one of which are offshore wind farms. The article presents the current regulatory environment of the offshore wind energy in Poland, along with a reference to Polish and European decarbonisation plans. In the further part of the article, the methods of determining the kinetic energy of wind and the power curve of a wind turbine are discussed. Then, on the basis of historical data of wind speeds collected in the area of the Baltic Sea, calculations are carried out leading to obtain statistical distributions of power that could be generated by an exemplary wind farm with a power capacity of 400 MW, located at the place of wind measurements. On their basis, statistical differences in the wind power generation between years, months of the year and hours of the day are analysed.

Simulation Study on Dynamic Reactive Power Compensation of Grid-Connected Wind Farms

2013 ◽  
Vol 756-759 ◽  
pp. 4171-4174 ◽  
Author(s):  
Xiao Ming Wang ◽  
Xing Xing Mu
Keyword(s):  
Voltage Stability ◽  
Wind Farm ◽  
Reactive Power ◽  
Wind Farms ◽  
Reactive Power Compensation ◽  
Wind Speeds ◽  
Wind Generators ◽  
Reactive Compensation ◽  
Farm Model ◽  
Set Up

With the Asynchronous wind generators as research object, this paper analyzes the problems of the voltage stability and the generation mechanism of the reactive power compensation during the wind farms connected operation. For paralleling capacitor bank has shown obvious defects, therefore this paper employs dynamic reactive power compensation to improve reactive characteristics of grid-connected wind farms. With the influences of different wind disturbances and grid faults on wind farms, wind farm model is set up and dynamic reactive power compensation system and wind speeds are built in the Matlab/Simulink software, The simulation result shows that they can provide reactive power compensation to ensure the voltage stability of the wind farms. But STATCOM needs less reactive compensation capacity to make sure the voltage and active power approaching steady state before the faults more quickly, Therefore STATCOM is more suitable for wind farms connected dynamic reactive power compensation.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

Research on Reliability Assessment of Power System with Wind Farms

2012 ◽  
Vol 608-609 ◽  
pp. 588-591
Author(s):  
Wen Jiang ◽  
Ye Xia Cheng ◽  
Ye Jian Cheng
Keyword(s):  
Power System ◽  
Wind Farm ◽  
Sequential Monte Carlo ◽  
Moving Average ◽  
Reliability Assessment ◽  
Arma Model ◽  
Wind Farms ◽  
Test System ◽  
Wind Speeds ◽  
State Models

Due to randomness and fluctuation of wind speed, reliability of power system will be affected severely with increasing wind energy injected into power grid. In order to evaluate the effect on reliability of power system with wind farms, the author considers feature of time-sequential and self-correlation of wind speeds and builds an auto-regressive and moving average (ARMA) model to forecast wind speeds. Combining with state models of conventional generating units, transmission lines and transformers, a time-sequential Monte Carlo simulation reliability model is proposed to do reliability assessment of composite generation and transmission system with wind farm. IEEE-RTS test system is introduced to prove the proposed model. Analysis and comparison of results show that reliability can be improved clearly after integration of wind farm.

Assessment of wind energy potential and characteristics in Qatar for clean electricity generation

2021 ◽  
pp. 0309524X2110438
Author(s):  
Carlos Méndez ◽  
Yusuf Bicer
Keyword(s):  
Wind Energy ◽  
Wind Power ◽  
Power Density ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Rose ◽  
Energy Potential ◽  
Wind Power Density ◽  
Wind Speeds ◽  
Wind Energy Potential

The present study analyzes the wind energy potential of Qatar, by generating a wind atlas and a Wind Power Density map for the entire country based on ERA-5 data with over 41 years of measurements. Moreover, the wind speeds’ frequency and direction are analyzed using wind recurrence, Weibull, and wind rose plots. Furthermore, the best location to install a wind farm is selected. The results indicate that, at 100 m height, the mean wind speed fluctuates between 5.6054 and 6.5257 m/s. Similarly, the Wind Power Density results reflect values between 149.46 and 335.06 W/m2. Furthermore, a wind farm located in the selected location can generate about 59.7437, 90.4414, and 113.5075 GWh/y electricity by employing Gamesa G97/2000, GE Energy 2.75-120, and Senvion 3.4M140 wind turbines, respectively. Also, these wind farms can save approximately 22,110.80, 17,617.63, and 11,637.84 tons of CO2 emissions annually.

Modeling of Flow Acceleration Around Wind Farms

2007 ◽  
Author(s):  
Patrick Moriarty ◽  
Tetsuya Kogaki
Keyword(s):  
Wind Farm ◽  
Computational Models ◽  
Three Dimensional ◽  
Wind Farms ◽  
Navier Stokes ◽  
Local Wind ◽  
Flow Acceleration ◽  
Wind Speeds ◽  
Optimum Spacing ◽  
Future Work

Recent measurements from operating wind farms demonstrate that the layout of the farm and interactions between turbine wakes strongly affects the overall efficiency of the wind farm. In some wind farms arranged in rectangular layouts, winds coming from the direction of the rectangular corner create a potential acceleration around the wind farm. This acceleration inherently leads to stronger local wind speeds at wind turbines downstream of the corner turbine, thereby increasing the power output of the downstream turbines. In this study, computational models are developed to predict this complex behavior seen in wind farms. The model used to examine these effects is a fully three-dimensional unsteady incompressible Navier-Stokes code, with the turbulence model turned off. Preliminary results show an optimum spacing configuration is possible. However, the results have yet to be verified at higher Reynolds number, which will be the effort of future work. Ultimately, these tools may lead to more optimal wind farm layouts.

On the Necessity of Technology Qualification in the Offshore Wind Energy Industry

2011 ◽  
Author(s):  
S. M. S. M. K. Samarakoon ◽  
O. T. Gudmestad
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Energy Industry ◽  
Offshore Wind Farms ◽  
Best Available Techniques ◽  
Remote Areas ◽  
Wind Speeds ◽  
Available Energy ◽  
Financial Losses

Wind farm technology can be considered as one of the best available techniques to deliver renewable energy. Similarly, the number of wind farms has been growing rapidly owing to their contribution to sustainable development. Recently also, there has been a growing awareness of the need to develop a plentiful number of wind farms offshore rather than onshore. This is due to the consideration that the offshore wind farms are more beneficial than onshore with respect to their exposure to higher wind speeds while covering extensive areas. Less turbulence offshore also allows the turbines to harvest the available energy more effectively than onshore and to reduce the fatigue on turbines. Furthermore, most of the offshore wind farms are located in remote areas, which helps to avoid noise effects and the visual burden (shadows) on society. However, the malfunctioning of the turbines in offshore wind farms after a few months or years from their commissioning is a one of the challenging issue. The outcome of the failures leads to large financial losses owing to cost-intensive repairs and weather-related delays. Therefore, identification of potential failures at the early stages of development through a technology qualification procedure will help to minimize the loss of financial resources by increasing the reliability of the systems and the availability of wind power. Basically, appraisal of risk and reliability aspects is playing a key role in this qualification process in order to confirm that the system will perform as intended. This study identifies some recent historical failures in offshore wind farms causing significant financial losses. Further, it discusses the reasons of the failures and the possibility to overcome future obstacles in developing offshore wind farms using a technology qualification procedure. Finally, this paper discusses whether the existing technology qualification procedure can be directly applied for offshore wind farms, and what important modifications are necessary.

Optimization of Floating Offshore Wind Energy Systems Using an Extended Pattern Search Method

2016 ◽  
Author(s):  
Caitlin Forinash ◽  
Bryony DuPont
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Power Production ◽  
Pattern Search ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Power Development ◽  
Offshore Wind Farms ◽  
Onshore Wind ◽  
Extended Pattern Search

An Extended Pattern Search (EPS) approach is developed for offshore floating wind farm layout optimization while considering challenges such as high cost and harsh ocean environments. This multi-level optimization method minimizes the costs of installation and operations and maintenance, and maximizes power development in a unidirectional wind case by selecting the size and position of turbines. The EPS combines a deterministic pattern search algorithm with three stochastic extensions to avoid local optima. The EPS has been successfully applied to onshore wind farm optimization and enables the inclusion of advanced modeling as new technologies for floating offshore wind farms emerge. Three advanced models are incorporated into this work: (1) a cost model developed specifically for this work, (2) a power development model that selects hub height and rotor radius to optimize power production, and (3) a wake propagation and interaction model that determines aerodynamic effects. Preliminary results indicate the differences between proposed optimal offshore wind farm layouts and those developed by similar methods for onshore wind farms. The objective of this work is to maximize profit; given similar parameters, offshore wind farms are suggested to have approximately 24% more turbines than onshore farms of the same area. EPS layouts are also compared to those of an Adapted GA; 100% efficiency is found for layouts containing twice as many turbines as the layout presented by the Adapted GA. Best practices are derived that can be employed by offshore wind farm developers to improve the layout of platforms, and may contribute to reducing barriers to implementation, enabling developers and policy makers to have a clearer understanding of the resulting cost and power production of computationally optimized farms; however, the unidirectional wind case used in this work limits the representation of optimized layouts at real wind sites. Since there are currently no multi-turbine floating offshore wind farm projects operational in the United States, it is anticipated that this work will be used by developers when planning array layouts for future offshore floating wind farms.

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