Effects of Power Generation on the Opportunistic Maintenance Strategy for Wind Turbines Considering Reliability

2018 ◽  
Author(s):  
Chen Zhang ◽  
Wei Gao ◽  
Tao Yang ◽  
Sheng Guo ◽  
Honggang Ding
Keyword(s):  
Power Generation ◽  
Wind Turbines ◽  
Manufacturing System ◽  
Wind Farms ◽  
Research Trend ◽  
Maintenance Strategy ◽  
Opportunistic Maintenance ◽  
Great Progress ◽  
Optimal Maintenance ◽  
A Current

Corrective maintenance and preventive maintenance are two common maintenance strategies used in the wind farms, whose drawbacks are obvious and significant. Opportunistic maintenance strategy takes advantage of the dependencies existing among the wind turbine components and implement combined maintenance actions to reduce the huge downtime cost. The opportunistic maintenance strategy for wind turbines has made a great progress, as well as the strategy considering imperfect and condition-based maintenance. However, existing maintenance strategy researches are usually concerned with the maintenance itself and the effects of power generation are barely considered. Nowadays, a current research trend in manufacturing system is the integration of maintenance and production planning. In this paper, the effects of power generation on opportunistic maintenance strategy for wind turbines considering reliability are researched. The opportunistic maintenance reliability threshold is not constant and depends on the real-time power generation. Numerical examples are used to illustrate the economical advantages of this proposed strategy over traditional opportunistic maintenance strategy. Moreover, the optimal maintenance combination is also provided.

Wind farm cooperative control for optimal power generation

2018 ◽  
Vol 42 (6) ◽  
pp. 547-560 ◽  
Author(s):  
Fa Wang ◽  
Mario Garcia-Sanz
Keyword(s):  
Power Generation ◽  
Wind Turbines ◽  
Cooperative Control ◽  
Wind Farm ◽  
Wind Farms ◽  
Practical Method ◽  
Individual Case ◽  
Power Coefficient ◽  
The Individual ◽  
Large Wind

The power generation of a wind farm depends on the efficiency of the individual wind turbines of the farm. In large wind farms, wind turbines usually affect each other aerodynamically at some specific wind directions. Previous studies suggest that a way to maximize the power generation of these wind farms is to reduce the generation of the first rows wind turbines to allow the next rows to generate more power (coordinated case). Yet, other studies indicate that the maximum generation of the wind farm is reached when every wind turbine works at its individual maximum power coefficient CPmax (individual case). This article studies this paradigm and proposes a practical method to evaluate when the wind farm needs to be controlled according to the individual or the coordinated case. The discussion is based on basic principles, numerical computations, and wind tunnel experiments.

scholarly journals Managing Wind Power Generation via Indexed Semi-Markov Model and Copula

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4246 ◽  
Author(s):  
Guglielmo D’Amico ◽  
Giovanni Masala ◽  
Filippo Petroni ◽  
Robert Adam Sobolewski
Keyword(s):  
Power Generation ◽  
Power Systems ◽  
Wind Energy ◽  
Output Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Energy Systems ◽  
Wind Farms ◽  
Energy System ◽  
Spatial Dependencies

Because of the stochastic nature of wind turbines, the output power management of wind power generation (WPG) is a fundamental challenge for the integration of wind energy systems into either power systems or microgrids (i.e., isolated systems consisting of local wind energy systems only) in operation and planning studies. In general, a wind energy system can refer to both one wind farm consisting of a number of wind turbines and a given number of wind farms sited at the area in question. In power systems (microgrid) planning, a WPG should be quantified for the determination of the expected power flows and the analysis of the adequacy of power generation. Concerning this operation, the WPG should be incorporated into an optimal operation decision process, as well as unit commitment and economic dispatch studies. In both cases, the probabilistic investigation of WPG leads to a multivariate uncertainty analysis problem involving correlated random variables (the output power of either wind turbines that constitute wind farm or wind farms sited at the area in question) that follow different distributions. This paper advances a multivariate model of WPG for a wind farm that relies on indexed semi-Markov chains (ISMC) to represent the output power of each wind energy system in question and a copula function to reproduce the spatial dependencies of the energy systems’ output power. The ISMC model can reproduce long-term memory effects in the temporal dependence of turbine power and thus understand, as distinct cases, the plethora of Markovian models. Using copula theory, we incorporate non-linear spatial dependencies into the model that go beyond linear correlations. Some copula functions that are frequently used in applications are taken into consideration in the paper; i.e., Gumbel copula, Gaussian copula, and the t-Student copula with different degrees of freedom. As a case study, we analyze a real dataset of the output powers of six wind turbines that constitute a wind farm situated in Poland. This dataset is compared with the synthetic data generated by the model thorough the calculation of three adequacy indices commonly used at the first hierarchical level of power system reliability studies; i.e., loss of load probability (LOLP), loss of load hours (LOLH) and loss of load expectation (LOLE). The results will be compared with those obtained using other models that are well known in the econometric field; i.e., vector autoregressive models (VAR).

scholarly journals Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2650 ◽  
Author(s):  
Lubing Xie ◽  
Xiaoming Rui ◽  
Shuai Li ◽  
Xin Hu
Keyword(s):  
Wind Turbines ◽  
Preventive Maintenance ◽  
Weather Conditions ◽  
Offshore Wind ◽  
Maintenance Optimization ◽  
Maintenance Strategy ◽  
Distribution Method ◽  
Opportunistic Maintenance ◽  
Maintenance Costs ◽  
Offshore Wind Turbines

Owing to the late development of offshore wind power in China, operational data and maintenance experience are relatively scarce. Due to the harsh environmental conditions, a reliability analysis based on limited sample fault data has been regarded as an effective way to investigate maintenance optimization for offshore wind farms. The chief aim of the present work is to develop an effective strategy to reduce the maintenance costs of offshore wind turbines in consideration of their accessibility. The three-parameter Weibull distribution method was applied to failure rate estimation based on limited data. Moreover, considering the impacts of weather conditions on the marine maintenance activities, the Markov method and dynamic time window were used to depict the weather conditions. The opportunistic maintenance strategy was introduced to cut down on the maintenance costs through optimization of the preventive maintenance age and opportunistic maintenance age. The simulation analysis we have performed showed that the maintenance costs of the opportunistic maintenance strategy were 10% lower than those of the preventive maintenance strategy, verifying the effectiveness of the proposed maintenance strategy.

scholarly journals Two methods for estimating limits to large-scale wind power generation

2015 ◽  
Vol 112 (36) ◽  
pp. 11169-11174 ◽  
Author(s):  
Lee M. Miller ◽  
Nathaniel A. Brunsell ◽  
David B. Mechem ◽  
Fabian Gans ◽  
Andrew J. Monaghan ◽  
...  
Keyword(s):  
Power Generation ◽  
Kinetic Energy ◽  
Wind Power ◽  
Energy Flux ◽  
Wind Turbines ◽  
Large Scale ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Flux Method ◽  
Free Atmosphere

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 105 km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m−2, whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m−2, with VKE capturing this combination in a comparatively simple way.

scholarly journals Wind Energy Education through Low-Power Wind Turbines and Advanced Software Tools

2021 ◽  
Vol 19 ◽  
pp. 534-539
Author(s):  
R. Baños ◽  
◽  
A. Alcayde ◽  
F.G. Gil Montoya ◽  
F.R. Arrabal-Campos ◽  
...  
Keyword(s):  
Power Generation ◽  
Wind Energy ◽  
Wind Turbines ◽  
Engineering Students ◽  
Wind Farms ◽  
Software Tools ◽  
Academic Excellence ◽  
Energy Education ◽  
Undergraduate Engineering ◽  
Didactic Strategies

Wind energy has become a major source of power generation in recent years. This fact, along with the growing expectations for future decades, makes the study of renewable generation systems based on wind energy a subject of great importance for engineers from different disciplines. Although there are numerous research articles that deal with the technoeconomic aspects of this type of system, there are few works focused on the development of new didactic strategies to improve the academic excellence of undergraduate engineering students. This paper describes how to boost the student understanding regarding wind power generation by combining the use of advanced software tools normally used in the design of wind farms, such as System Advisor Model (National Renewable Energy Laboratory, NREL) and WindFarm (RESOFT) with lowpower wind turbines operating in self-consumption and gridconnected modes. Moreover, it is also described how wind turbines constitute an interesting option for distributed generation system in microgrids.

scholarly journals An Analysis of Wind Power Generation on the Electric Transmission System of Southern Vietnam

2021 ◽  
Vol 16 ◽  
pp. 204-212
Author(s):  
Minh-Hoa Nguyen ◽  
Van-Tan Tran ◽  
Tan-Hung Pham ◽  
Thanh-Luu Cao
Keyword(s):  
Power Generation ◽  
Power Systems ◽  
Power System ◽  
Wind Energy ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Southern Vietnam ◽  
Three Phase

Renewable energy is an emerging candidate in power generation for the compensation of the exhausted fossil fuel, in which wind energy plays an important role. However, how wind farms impact existing power systems has still been a subject on which many researchers are studying. This study has analyzed and evaluated the four wind farms consisting of Ca-Mau (300 MW), Bac-Lieu (99 MW), Soc-Trang (100 MW) and Tra-Vinh (33 MW) located in Southern Vietnam via using the commercial package, WAsP software. Ca-Mau wind farm has the highest planned rated capacity with 51.7% among the wind farms. Each wind farm is built from three different types of wind turbines (1 MW, 2 MW and 3 MW). The estimation has shown that all of the wind farms could produce 2,265 GWh annually, and the 3-MW wind turbines are the most efficient and give the smallest losses for producing wind energy. The wind farms, with respect to environmentally friendly aspects, could avoid 978,544 tCO2 emitted to the environment annually. Additionally, the ETAP program has also been applied to simulate the effects of the proposed wind farms on the national power system including the disturbances from wind speeds, three-phase bus faults, tripping off wind farms and three-phase line faults on the power system. The results show that the wind farms are only slightly impacted.

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