Optimal power dispatch in wind farm with life extension of wind turbine blades as target

2013 ◽  
Vol 5 (3) ◽  
pp. 033115 ◽  
Author(s):  
Jinhua Zhang ◽  
Yongqian Liu ◽  
De Tian ◽  
Gouhong Chen
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Turbine Blades ◽  
Life Extension ◽  
Wind Turbine Blades ◽  
Optimal Power ◽  
Power Dispatch

scholarly journals Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2319
Author(s):  
Hyun-Goo Kim ◽  
Jin-Young Kim
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Farm ◽  
Free Stream ◽  
Turbine Blades ◽  
Wind Farms ◽  
Lidar Measurement ◽  
Wind Turbine Blades ◽  
Wake Effect

This study analyzed the performance decline of wind turbine with age using the SCADA (Supervisory Control And Data Acquisition) data and the short-term in situ LiDAR (Light Detection and Ranging) measurements taken at the Shinan wind farm located on the coast of Bigeumdo Island in the southwestern sea of South Korea. Existing methods have generally attempted to estimate performance aging through long-term trend analysis of a normalized capacity factor in which wind speed variability is calibrated. However, this study proposes a new method using SCADA data for wind farms whose total operation period is short (less than a decade). That is, the trend of power output deficit between predicted and actual power generation was analyzed in order to estimate performance aging, wherein a theoretically predicted level of power generation was calculated by substituting a free stream wind speed projecting to a wind turbine into its power curve. To calibrate a distorted wind speed measurement in a nacelle anemometer caused by the wake effect resulting from the rotation of wind-turbine blades and the shape of the nacelle, the free stream wind speed was measured using LiDAR remote sensing as the reference data; and the nacelle transfer function, which converts nacelle wind speed into free stream wind speed, was derived. A four-year analysis of the Shinan wind farm showed that the rate of performance aging of the wind turbines was estimated to be −0.52%p/year.

Optimal power dispatch within wind farm based on two approaches to wind turbine classification

2017 ◽  
Vol 102 ◽  
pp. 487-501 ◽  
Author(s):  
Zhang Jinhua ◽  
Liu Yongqian ◽  
David Infield ◽  
Ma Yuanchi ◽  
Cao Qunshi ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Optimal Power ◽  
Power Dispatch

scholarly journals Editorial on Special Issue “Wind Turbine Power Optimization Technology”

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1796
Author(s):  
Francesco Castellani ◽  
Davide Astolfi
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Power Optimization ◽  
Turbine Blades ◽  
Energy Yield ◽  
Optimization Approach ◽  
Special Issue ◽  
Wind Turbine Blades ◽  
Industry Practice

This Special Issue collects innovative contributions in the field of wind turbine optimization technology. The general motivation of the present Special Issue is given by the fact that there has recently been a considerable boost of the quest for wind turbine efficiency optimization in the academia and in the wind energy practitioners communities. The optimization can be focused on technology and operation of single turbine or a group of machines within a wind farm. This perspective is evidently multi-faced and the seven papers composing this Special Issue provide a representative picture of the most ground-breaking state of the art about the subject. Wind turbine power optimization means scientific research about the design of innovative aerodynamic solutions for wind turbine blades and of wind turbine single or collective control, especially for increasing rotor size and exploitation in offshore environment. It should be noticed that some recently developed aerodynamic and control solutions have become available in the industry practice and therefore an interesting line of development is the assessment of the actual impact of optimization technology for wind turbines operating in field: this calls for non-trivial data analysis and statistical methods. The optimization approach must be 360 degrees; for this reason also offshore resource should be addressed with the most up to date technologies such as floating wind turbines, in particular as regards support structures and platforms to be employed in ocean environment. Finally, wind turbine power optimization means as well improving wind farm efficiency through innovative uses of pre-existent control techniques: this is employed, for example, for active control of wake interactions in order to maximize the energy yield and minimize the fatigue loads.

scholarly journals Extending the life of wind turbine blade leading edges by reducing the tip speed during extreme precipitation events

2018 ◽  
Vol 3 (2) ◽  
pp. 729-748 ◽  
Author(s):  
Jakob Ilsted Bech ◽  
Charlotte Bay Hasager ◽  
Christian Bak
Keyword(s):  
Wind Turbine ◽  
Extreme Precipitation ◽  
Turbine Blades ◽  
Leading Edge ◽  
Life Extension ◽  
Wind Turbine Blades ◽  
Worst Case ◽  
Severe Problem ◽  
Extreme Precipitation Events ◽  
Leading Edges

Abstract. Impact fatigue caused by collision with rain droplets, hail stones and other airborne particles, also known as leading-edge erosion, is a severe problem for wind turbine blades. Each impact on the leading edge adds an increment to the accumulated damage in the material. After a number of impacts the leading-edge material will crack. This paper presents and supports the hypothesis that the vast majority of the damage accumulated in the leading edge is imposed at extreme precipitation condition events, which occur during a very small fraction of the turbine's operation life. By reducing the tip speed of the blades during these events, the service life of the leading edges significantly increases from a few years to the full expected lifetime of the wind turbine. This life extension may cost a negligible reduction in annual energy production (AEP) in the worst case, and in the best case a significant increase in AEP will be achieved.

scholarly journals Optimal Power Dispatch of an Offshore Wind Farm under Generator Fault

2019 ◽  
Vol 9 (6) ◽  
pp. 1184 ◽  
Author(s):  
Kuichao Ma ◽  
Jiangsheng Zhu ◽  
Mohsen Soltani ◽  
Amin Hajizadeh ◽  
Zhe Chen
Keyword(s):  
Power Generation ◽  
Wind Turbine ◽  
Power Loss ◽  
Wind Farm ◽  
Wind Farms ◽  
Pso Algorithm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Optimal Power ◽  
Power Dispatch

For offshore wind farms, the power loss caused by the wake effect is large due to the large capacity of the wind turbine. At the same time, the operating environment of the offshore wind farm is very harsh, and the cost of maintenance is higher than that of the onshore wind farm. Therefore, it is worthwhile to study through reasonable control how to reduce the wake loss of the wind farm and minimize the losses caused by the fault. In this paper, the Particle Swarm Optimization (PSO) algorithm is used to optimize the active power dispatch of wind farms under generator cooling system faults. The optimization objectives include avoiding the further deterioration of the generator fault, reducing unnecessary power loss of the faulty wind turbine, tracking the power demand from the Transmission System Operator (TSO), and reducing the power fluctuation caused by the PSO algorithm. The proposed optimal power dispatch strategy was compared with the two generally-used fault-handling methods and the proportional dispatch strategy in simulation. The result shows that the proposed strategy can improve the power generation capacity of the wind farm and achieve an efficient trade-off between power generation and fault protection.

scholarly journals A Binary Integer Programming Method for Optimal Wind Turbines Allocation

2021 ◽  
Vol 3 (2) ◽  
pp. 462-473
Author(s):  
Nikolaos M. Manousakis ◽  
Constantinos S. Psomopoulos ◽  
George Ch. Ioannidis ◽  
Stavros D. Kaminaris
Keyword(s):  
Integer Programming ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Binary Integer Programming ◽  
Wake Effect ◽  
Square Cells ◽  
Virtual Grid

The present study introduces a Binary Integer Programming (BIP) method to minimize the number of wind turbines needed to be installed in a wind farm. The locations of wind turbines are selected in a virtual grid which is constructed considering a minimum distance between the wind turbines to avoid the wake effect. Additional equality constraints are also included to the proposed formulation to prohibit or enforce the installation of wind turbines placement at specific locations of the wind farmland. Moreover, a microscopic wind turbine placement considering the local air density is studied. To verify the efficiency of this proposal, a square site was subdivided into 25 square cells providing a virtual grid with 36 candidate placement locations. Moreover, a virtual grid with 121 vertices related with a Greek island is also tested. All simulations conducted considering the area of geographical territory, the length of wind turbine blades, as well as the capacity of each turbine.

scholarly journals Diagnosis of Blade Icing Using Multiple Intelligent Algorithms

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2975
Author(s):  
Xiyun Yang ◽  
Tianze Ye ◽  
Qile Wang ◽  
Zhun Tao
Keyword(s):  
Neural Network ◽  
Random Forest ◽  
Wind Turbine ◽  
Wind Farm ◽  
Turbine Blades ◽  
Back Propagation ◽  
Active Power ◽  
K Nearest Neighbor ◽  
Wind Turbine Blades ◽  
Fully Connected

The icing problem of wind turbine blades in northern China has a serious impact on the normal and safe operation of the unit. In order to effectively predict the icing conditions of wind turbine blades, a deep fully connected neural network optimized by machine learning (ML) algorithms based on big data from the wind farm is proposed to diagnose the icing conditions of wind turbine blades. This study first uses the random forest model to reduce the features of the supervisory control and data acquisition (SCADA) data that affect blade icing, and then uses the K-nearest neighbor (KNN) algorithm to enhance the active power feature. The features after the random forest reduction and the active power mean square error (MSE) feature enhanced by the KNN algorithm are combined and used as the input of the fully connected neural network (FCNN) to perform and an empirical analysis for the diagnosis of blade icing. The simulation results show that the proposed model has better diagnostic accuracy than the ordinary back propagation (BP) neural network and other methods.

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