scholarly journals The Wind Observation and Energy Production Estimation for Offshore Wind Farm

2008 ◽  
Vol 2008 (115) ◽  
pp. 119-122
Author(s):  
Manabu TSUCHIYA ◽  
Yukinari FUKUMOTO ◽  
Takeshi ISHIHARA
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Wind Observation

scholarly journals A Feasibility Study on Annual Energy Production of the Offshore Wind Farm using MERRA Reanalysis Data

2015 ◽  
Vol 35 (2) ◽  
pp. 33-41 ◽  
Author(s):  
Yuan Song ◽  
Hyungyu Kim ◽  
Junho Byeon ◽  
Insu Paek ◽  
Neungsoo Yoo
Keyword(s):  
Feasibility Study ◽  
Energy Production ◽  
Wind Farm ◽  
Reanalysis Data ◽  
Offshore Wind ◽  
Offshore Wind Farm

scholarly journals Balancing profitability of energy production, societal impacts and biodiversity in offshore wind farm design

2022 ◽  
Vol 158 ◽  
pp. 112087
Author(s):  
E.A. Virtanen ◽  
J. Lappalainen ◽  
M. Nurmi ◽  
M. Viitasalo ◽  
M. Tikanmäki ◽  
...  
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Wind Farm Design ◽  
Societal Impacts ◽  
Farm Design

Effects of Wind Farm Down-Regulation in the Offshore Wind Farm Alpha Ventus

2019 ◽  
Author(s):  
Matthias Kretschmer ◽  
Vasilis Pettas ◽  
Po Wen Cheng
Keyword(s):  
Wind Turbine ◽  
Wind Direction ◽  
Energy Production ◽  
Wind Farm ◽  
Measurement Data ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Down Regulation ◽  
Maximum Reduction ◽  
High Reduction

Abstract In recent years wind turbine down-regulation has been used or investigated for a variety of applications such as wind farm power optimisation, energy production curtailment and lifetime management. This study presents results from measurement data of tower loads and power obtained from two turbines located in the German offshore wind farm alpha ventus. The free streaming turbine, located closely to a fully equipped meteorological mast, was down-regulated to 50% for a period of 8 months, while the downwind turbine was operating normally. The results are compared to periods where both turbines were operated in normal conditions. Changes in loads and power are analysed according to incoming wind direction and magnitude. Results show a high reduction in the loads of the down regulated turbine, up to a level of 40%. For the turbine in wake the effects in loads are more prominent, showing a maximum reduction of 30%, compared to the effects in power and are seen in a wider sector of about 20° for loads and 10° for power.

Identification and Optimization of Most Relevant Variables When Creating a Maintenance Strategy of an Offshore Wind Farm

2017 ◽  
Author(s):  
Ana Beatriz Gomes Zanforlin ◽  
Adriana Miralles Schleder ◽  
Marcelo Ramos Martins
Keyword(s):  
Wind Energy ◽  
Energy Production ◽  
Wind Farm ◽  
Production Costs ◽  
Offshore Wind ◽  
Maintenance Strategy ◽  
Offshore Wind Energy ◽  
Offshore Wind Farm ◽  
Failure Data ◽  
Farm Model

A lot has been researched recently in order to enable economically feasible use of offshore wind energy. Although these figures have been falling, offshore wind energy generation has in average still much higher costs associated with the inherent drawbacks of installing and operating assets at the sea’s hostile environment. As much of these costs are related to unplanned maintenance tasks, one promising approach to make wind energy more competitive is to optimize the resources involved in it. This paper was developed with the purpose of analyzing the viability of an algorithm that offers valuable information when defining a maintenance strategy for the operation of an offshore wind farm, aiming at the availability and the expected profit optimization, with a different approach than usual. Initially, an algorithm to conduct a reliability, availability and maintainability (RAM) analysis was created based on a Monte Carlo Simulation (MCS). Given a simplified wind farm model, as well as its components’ failure data and configuration, it is possible to obtain its availability and energy production costs. The algorithm was validated by comparing known failure data with the stochastically obtained after running the algorithm. A case study was defined based on extensive literature research and the simulation was executed considering restrictions typically found in modern wind farms. A sensitivity analysis was conducted in order to understand how each model’s parameter affects the energy production costs. Given this analysis, it was possible to determine the most relevant optimization variables when creating a maintenance strategy. Following, an algorithm for optimizing those parameters is presented.

Optimizing the Layout of Offshore Wind Energy Systems

2008 ◽  
Vol 42 (2) ◽  
pp. 19-27 ◽  
Author(s):  
Christopher N. Elkinton ◽  
James F. Manwell ◽  
Jon G. McGowan
Keyword(s):  
Wind Energy ◽  
Energy Production ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Offshore Wind Farm ◽  
Wind Farm Layout ◽  
Trade Offs ◽  
Cost Of Energy ◽  
The Cost

Offshore wind energy technology is a reality in Europe and is poised to make a significant contribution to the U.S. energy supply in the near future as well. The layout of an offshore wind farm is a complex problem involving many trade-offs. For example, energy production increases with turbine spacing, as do electrical costs and losses. Energy production also increases with distance from shore, but so do O&M (operations and maintenance), foundation, transmission, and installation costs. Determining which of these factors dominates requires a thorough understanding of the physics behind these trade-offs, can lead to the optimal layout, and helps lower the cost of energy from these farms. This paper presents the results of a study carried out to investigate these trade-offs and to develop a method for optimizing the wind farm layout during the micrositing phase of an offshore wind energy system design. It presents a method for analyzing the cost of energy from offshore wind farms as well as a summary of the development of an offshore wind farm layout optimization tool. In addition to an initial validation of the optimization tool, an example of the use of this tool for the design of an offshore wind farm in Hull, Massachusetts, is also given.

scholarly journals The Wind Observation for Offshore Wind Farm and A New Normal Turbulence Model

2011 ◽  
Vol 36 (1) ◽  
pp. 9-14
Author(s):  
Manabu TSUCHIYA ◽  
Takeshi ISHIHARA ◽  
Yukinari FUKUMOTO
Keyword(s):  
Turbulence Model ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
New Normal ◽  
Wind Observation

Damping of Frequency Fluctuations of Hybrid Power System by Variable Deloaded Operation of PMSG Based Offshore Wind Farm

2019 ◽  
Vol 139 (4) ◽  
pp. 259-268
Author(s):  
Effat Jahan ◽  
Md. Rifat Hazari ◽  
Mohammad Abdul Mannan ◽  
Atsushi Umemura ◽  
Rion Takahashi ◽  
...  
Keyword(s):  
Power System ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Hybrid Power System ◽  
Hybrid Power ◽  
Frequency Fluctuations
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