scholarly journals CREATION OF WIND ENERGY FACILITIES AND DEVELOPMENT PERSPECTIVE OF THE SERVICES LOGISTICS MARKET: AN INTEGRATED APPROACH

2021 ◽  
Vol 1 (1-2) ◽  
pp. 3-12
Author(s):  
Iryna Rykovanova ◽  
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Wind Farms ◽  
Integrated Approach ◽  
Production Equipment ◽  
Wind Power Generation ◽  
Current State ◽  
Logistics Market ◽  
Management Functions ◽  
The Eu

We analyzed the current state and development prospects of wind power generation in the EU and Ukraine. We detected the trends on many wind power generation impactors in the EU and the Ukrainian's interest in building wind parks. Such trends led to the market development of specialized technical aids for assuring transportation of equipment production elements of wind power units to the installation place. The obtained results gave grounds for directions on developing the logistic services market in the segment of delivery of non-standard on all characteristics of the production equipment for wind installations: weight, geometrical sizes, transportation conditions. We proposed an approach to delegate the management functions and delivery of production equipment for wind-power units to a logistics operator (logistics provider) 4pl-level with a package of services "industry logistics" and "project logistics" as an integrator of material and of accompanying flows. This approach should be helpful to optimize financial costs, time and reduce the level of risks in the implementation of a project to create wind power generation facilities. The involvement of a representative, a logistics operator in project activities, opens up prospects for the life cycle of logistics service for the supply of goods of non-standard dimensions and diversification of the activities of logistics operators in the logistics services market, including through the determination of the KPI for further cooperation in wind farms servicing.

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 Impacts of Integration of Wind Farms on Power System Transient Stability

2018 ◽  
Vol 8 (8) ◽  
pp. 1289 ◽  
Author(s):  
Shiwei Xia ◽  
Qian Zhang ◽  
S.T. Hussain ◽  
Baodi Hong ◽  
Weiwei Zou
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Power System ◽  
Wind Power ◽  
Transient Stability ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Wind Generation ◽  
System Operation ◽  
Power System Operation

To compensate for the ever-growing energy gap, renewable resources have undergone fast expansions worldwide in recent years, but they also result in some challenges for power system operation such as the static security and transient stability issues. In particular, as wind power generation accounts for a large share of these renewable energy and reduces the inertia of a power network, the transient stability of power systems with high-level wind generation is decreased and has attracted wide attention recently. Effectively analyzing and evaluating the impact of wind generation on power transient stability is indispensable to improve power system operation security level. In this paper, a Doubly Fed Induction Generator with a two-lumped mass wind turbine model is presented firstly to analyze impacts of wind power generation on power system transient stability. Although the influence of wind power generation on transient stability has been comprehensively studied, many other key factors such as the locations of wind farms and the wind speed driving the wind turbine are also investigated in detail. Furthermore, how to improve the transient stability by installing capacitors is also demonstrated in the paper. The IEEE 14-bus system is used to conduct these investigations by using the Power System Analysis Tool, and the time domain simulation results show that: (1) By increasing the capacity of wind farms, the system instability increases; (2) The wind farm location and wind speed can affect power system transient stability; (3) Installing capacitors will effectively improve system transient stability.

scholarly journals The Impact of Future Offshore Wind Farms on Wind Power Generation in Great Britain

Resources ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 155-171 ◽  
Author(s):  
Daniel Drew ◽  
Dirk Cannon ◽  
David Brayshaw ◽  
Janet Barlow ◽  
Phil Coker
Keyword(s):  
Power Generation ◽  
Great Britain ◽  
Wind Power ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
The Impact

scholarly journals Estimating Wind Farm Transformers Rating through Lifetime Characterization Based on Stochastic Modeling of Wind Power

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1498
Author(s):  
Maurizio Fantauzzi ◽  
Davide Lauria ◽  
Fabio Mottola ◽  
Daniela Proto
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Wind Farm ◽  
Wind Farms ◽  
Mineral Oil ◽  
Wind Power Generation ◽  
Numerical Application ◽  
Stochastic Characterization ◽  
Large Wind

This paper deals with the problem of the optimal rating of mineral-oil-immersed transformers in large wind farms. The optimal rating is derived based on the probabilistic analyses of wind power generation through the Ornstein–Uhlenbeck stochastic process and on thermal model of the transformer through the integration of stochastic differential equations. These analyses allow the stochastic characterization of lifetime reduction of the transformer and then its optimal rating through a simple closed form. The numerical application highlights the effectiveness and easy applicability of the proposed methodology. The proposed methodology allows deriving the rating of transformers which better fits the specific peculiarities of wind power generation. Compared to the conventional approaches, the proposed method can better adapt the transformer size to the intermittence and variability of the power generated by wind farms, thus overcoming the often-recognized reduced lifetime.

scholarly journals Estimation of the Daily Variability of Aggregate Wind Power Generation in Alberta, Canada

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1998 ◽  
Author(s):  
Yilan Luo ◽  
Deniz Sezer ◽  
David Wood ◽  
Mingkuan Wu ◽  
Hamid Zareipour
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Wind Farm ◽  
Wind Farms ◽  
Gaussian Random Fields ◽  
Wind Power Generation ◽  
Temporal Correlations ◽  
Prevailing Wind Direction ◽  
Full Symmetry ◽  
Spatio Temporal

This paper describes a hierarchy of increasingly complex statistical models for wind power generation in Alberta applied to wind power production data that are publicly available. The models are based on combining spatial and temporal correlations. We apply the method of Gaussian random fields to analyze the wind power time series of the 19 existing wind farms in Alberta. Following the work of Gneiting et al., three space-time models are used: Stationary, Separability, and Full Symmetry. We build several spatio-temporal covariance function estimates with increasing complexity: separable, non-separable and symmetric, and non-separable and non-symmetric. We compare the performance of the models using kriging predictions and prediction intervals for both the existing wind farms and a new farm in Alberta. It is shown that the spatial correlation in the models captures the predominantly westerly prevailing wind direction. We use the selected model to forecast the mean and the standard deviation of the future aggregate wind power generation of Alberta and investigate new wind farm siting on the basis of reducing aggregate variability.

scholarly journals On the wake effect in wind farm power forecasting: a new data-driven approach

2020 ◽  
Vol 197 ◽  
pp. 08016
Author(s):  
Fabio Famoso ◽  
Sebastian Brusca ◽  
Antonio Galvagno ◽  
Michele Messina ◽  
Rosario Lanzafame
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Physical Models ◽  
Production Forecast ◽  
Innovative Method ◽  
Power Forecasting

Wind power generation differs from other energy sources, such as thermal, solar or hydro, due to the inherent stochastic nature of wind. For this reason wind power forecasting, especially for wind farms, is a complex task that cannot be accurately solved with traditional statistical methods or needs large computational systems if physical models are used. Recently, the so-called learning approaches are considered a good compromise among the previous methods since they are able to integrate physical phenomena such as wake effects without presenting heavy computational loads. The present work deals with an innovative method to forecast wind power generation in a wind farm with a combination of GISbased methods, neural network approach and a wake physical model. This innovative method was tested with a wind farm located in Sicily (Italy), used as a case study. It consists of 30 identical wind turbines (850 kW each one), located at different heights, for an overall Power peak of 25 MW. The time series dataset consists of one year with a sampling time of 10 minutes considering wind speeds and wind directions. The output of this innovative model leaded to good results, especially for medium-term overall energy production forecast for the case study.

Effects of Large Scale Wind Power on Total System Variability and Operation: Case Study of Northern Ireland

2003 ◽  
Vol 27 (1) ◽  
pp. 3-20 ◽  
Author(s):  
Shashi Persaud ◽  
Brendan Fox ◽  
Damian Flynn
Keyword(s):  
Power Generation ◽  
Northern Ireland ◽  
Wind Power ◽  
Large Scale ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Wind Generation ◽  
Total System ◽  
Power Capacity ◽  
Spinning Reserve

The paper simulates the potential impact of significant wind power capacity on key operational aspects of a medium-sized grid-power system, viz. generator loading levels, system reserve availability and generator ramping requirements. The measured data, from Northern Ireland, consist of three years of 1/2 hourly metered records of (i) total energy generation and (ii) five wind farms, each of 5 MW capacity. These wind power data were scaled-up to represent a 10% annual energy contribution, taking account of diversity on the specific variability of total wind power output. The wind power generation reduced the system non-wind peak-generation. This reduction equalled 20% of the installed wind power capacity. There was also a reduction in the minimum non-wind generation, which equalled 43% of the wind power capacity. The analysis also showed that the spinning-reserve requirement depended on the accuracy of forecasting wind power ahead of scheduling, i.e. on the operational mode. When wind power was predicted accurately, (i) it was possible to reduce non-wind generation without over-commitment, but, (ii) the spinning-reserve non-wind conventional generation would usually have to be increased by 25% of the wind power capacity, unless quick-start gas generation was available. However, with unpredicted wind power generation, (i) despite reductions in non-wind generation, there was frequent over-commitment of conventional generation, but (ii) usually the spinning-reserve margin could be reduced by 10% of the wind power capacity with the same degree of risk. Finally, it was shown that wind power generation did not significantly increase the ramping duty on the system. For accurately predicted and unpredicted wind power the increases were only 4% and 5% respectively.

scholarly journals Current Status and Prospective of Offshore Wind Power to Achieve Korean Renewable Energy 3020 Plan

2021 ◽  
Vol 43 (3) ◽  
pp. 196-205
Author(s):  
Minkyu Park ◽  
Seongjun Park ◽  
Byungcheol Seong ◽  
Yeonjeong Choi ◽  
Sokhee P. Jung
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Wind Power ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Offshore Wind Power ◽  
Wind Power Development

This review comprehensively reviewed floating offshore wind power generation technology, which is being newly developed as a mid- to long-term plan for wind energy. From the perspective of investment per megawatt (MW), offshore wind power is still about 50 percent more expensive than land wind power. Nevertheless, many advanced countries began to investigate the data because they wondered why they were immersed in development and investment, and why offshore wind facilities installed on the beach and floating offshore wind installed in the middle of the sea, unlike the land wind we knew. We looked at the basic principles of offshore wind power generation and the technologies used in facilities, and looked at the advantages and disadvantages of offshore wind power generation compared to land wind power generation, and what differences between fixed offshore wind farms and floating offshore wind farms. It is investigated whether it is a realistic plan to verify residents’ opposition to the installation of offshore wind power facilities, the possibility of commercialization such as high operational management costs, and the feasibility of installing facilities for renewable energy 3020 as mid- to long-term goals. In addition, it compares foreign cases with offshore wind power development complexes in Korea, marine wind power generation complexes in operation, and high wind power in Scotland, the first floating offshore wind power in Ulsan, Korea, to overcome difficulties in installing facilities and suggest directions for domestic offshore wind power development. In addition, in Korea, where there are not many countries suitable for wind power generation unlike overseas, it was decided to investigate whether floating offshore wind power could be the answer as planned. The reason why the government is pushing for investment in renewable energy such as solar power and wind power is because energy sources from the sun are eco-friendly. However, the U.S. and Europe, which started the wind power project early, are having difficulty in handling the wings of wind power generators. The energy source looked at the contradictions caused by environmental pollution in the treatment of waste, although it was environmentally friendly, and investigated how waste was treated and utilized overseas. Compared to other countries that entered the offshore wind power business earlier, domestic power generation projects are in their infancy and should focus on developing technology and co-prosperity with neighboring residents rather than on excessive expansion.

Modeling Large-Scale Wind Farms for Reliability Analysis Considering Wake Effect

2014 ◽  
Vol 543-547 ◽  
pp. 647-652
Author(s):  
Ye Zhou Hu ◽  
Lin Zhang ◽  
Pai Liu ◽  
Xin Yuan Liu ◽  
Ming Zhou
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Power ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Wake Effect ◽  
Effect Model ◽  
The Individual

Large scale wind power penetration has a significant impact on the reliability of the electric generation systems. A wind farm consists of a large number of wind turbine generators (WTGs). A major difficulty in modeling wind farms is that the WTG not have an independent capacity distribution due to the dependence of the individual turbine output on the same energy source, the wind. In this paper, a model of the wind farm output power considering multi-wake effects is established according to the probability distribution of the wind speed and the characteristic of the wind generator output power: based on the simple Jenson wake effect model, the wake effect with wind speed sheer model and the detail wake effect model with the detail shade areas of the upstream wind turbines are discussed respectively. Compared to the individual wake effect model, this model takes the wind farm as a whole and considers the multi-wakes effect on the same unit. As a result the loss of the velocity inside the wind farm is considered more exactly. Furthermore, considering the features of sequentially and self-correlation of wind speed, an auto-regressive and moving average (ARMA) model for wind speed is built up. Also the reliability model of wind farm is built when the output characteristics of wind power generation units, correlation of wind speeds among different wind farms, outage model of wind power generation units, wake effect of wind farm and air temperature are considered. Simulation results validate the effectiveness of the proposed models. These models can be used to research the reliability of power grid containing wind farms, wind farm capacity credit as well as the interconnection among wind farms

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