skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Mapping Operation and Maintenance Strategy for U.S. Offshore Wind Farms

Abstract

This presentation provides an overview of a collaborative effort between ECN and the National Renewable Energy Laboratory that focused on an operation and maintenance study of six offshore wind power plants in the United States.

Authors:
;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1365708
Report Number(s):
NREL/PR-6A20-68494
DOE Contract Number:
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2nd US Offshore Wind Conference and Exhibition 2017, 8-9 May 2017, Long Island, New York
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY; offshore wind energy; operation and maintenance; analysis; research; collaboration; ECN

Citation Formats

Dewan, Ashish, and Stehly, Tyler. Mapping Operation and Maintenance Strategy for U.S. Offshore Wind Farms. United States: N. p., 2017. Web.
Dewan, Ashish, & Stehly, Tyler. Mapping Operation and Maintenance Strategy for U.S. Offshore Wind Farms. United States.
Dewan, Ashish, and Stehly, Tyler. Thu . "Mapping Operation and Maintenance Strategy for U.S. Offshore Wind Farms". United States. doi:. https://www.osti.gov/servlets/purl/1365708.
@article{osti_1365708,
title = {Mapping Operation and Maintenance Strategy for U.S. Offshore Wind Farms},
author = {Dewan, Ashish and Stehly, Tyler},
abstractNote = {This presentation provides an overview of a collaborative effort between ECN and the National Renewable Energy Laboratory that focused on an operation and maintenance study of six offshore wind power plants in the United States.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jun 22 00:00:00 EDT 2017},
month = {Thu Jun 22 00:00:00 EDT 2017}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share:
  • Optimising the operation and maintenance (O&M) and logistics strategy of offshore wind farms implies the decision problem of selecting the vessel fleet for O&M. Different strategic decision support tools can be applied to this problem, but much uncertainty remains regarding both input data and modelling assumptions. Our paper aims to investigate and ultimately reduce this uncertainty by comparing four simulation tools, one mathematical optimisation tool and one analytic spreadsheet-based tool applied to select the O&M access vessel fleet that minimizes the total O&M cost of a reference wind farm. The comparison shows that the tools generally agree on the optimalmore » vessel fleet, but only partially agree on the relative ranking of the different vessel fleets in terms of total O&M cost. The robustness of the vessel fleet selection to various input data assumptions was tested, and the ranking was found to be particularly sensitive to the vessels' limiting significant wave height for turbine access. Also the parameter with the greatest discrepancy between the tools, implies that accurate quantification and modelling of this parameter is crucial. The ranking is moderately sensitive to turbine failure rates and vessel day rates but less sensitive to electricity price and vessel transit speed.« less
  • The United States Department of Energy (DOE) awarded a grant to GL Garrad Hassan (GL GH) to investigate the logistics, opportunities, and costs associated with existing and emerging installation and operation and maintenance (O&M) activities at offshore wind projects as part of the DOE’s program to reduce barriers facing offshore wind project development in the United States (U.S.). This report (the Report) forms part of Subtopic 5.3 “Optimized Installation, Operation and Maintenance Strategies Study” which in turn is part of the “Removing Market Barriers in U.S. Offshore Wind” set of projects for the DOE. The purpose of Subtopic 5.3 ismore » to aid and facilitate informed decision-making regarding installation and O&M during the development, installation, and operation of offshore wind projects in order to increase efficiency and reduce the levelized cost of energy (LCoE). Given the large area of U.S. territorial waters, the generally higher mean wind speeds offshore, and the proximity to the coast of many large U.S. cities, offshore wind power has the potential to become a significant contributor of energy to U.S. markets. However, for the U.S. to ensure that the development of offshore wind energy projects is carried out in an efficient and cost-effective manner, it is important to be cognizant of the current and emerging practices in both the domestic and international offshore wind energy industries. The U.S. can harness the experience gained globally and combine this with the skills and assets of an already sizeable onshore wind industry, as well as the resources of a mature offshore oil and gas industry, to develop a strong offshore wind sector. The work detailed in this report is aimed at assisting with that learning curve, particularly in terms of offshore specific installation and O&M activities. This Report and the Installation and O&M LCoE Analysis Tool, which were developed together by GL GH as part of this study, allow readers to identify, model and probe the economic merits and sensitivities of various approaches to construction and O&M practices, using illustrative offshore projects across a wide range of alternative offshore development areas located in U.S. waters. The intention is to assist decision-makers in clearly understanding the relative economic benefits of both conventional and novel construction installation methodologies and maintenance techniques within the critical parameters of a Project’s LCoE.« less
  • Electricity markets in the United States are evolving. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast makes it possible for grid operators to schedule the economically efficient generation to meet the demand of electrical customers. In the evolving markets, some form of auction is held for various forward markets, such as hour ahead or day ahead. This paper develops several statistical forecasting models that can be useful in hour-ahead markets that have a similar tariff. Although longer-term forecasting relies on numerical weather models, the statistical models used here focus onmore » the short-term forecasts that can be useful in the hour-ahead markets. We investigate the extent to which time-series analysis can improve on simplistic persistence forecasts. This project applied a class of models known as autoregressive moving average (ARMA) models to both wind speed and wind power output.« less
  • Electricity markets in the United States are evolving. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. The evolving markets hold some form of auction for various forward markets, such as hour ahead or day ahead. This paper describes several statistical forecasting models that can be useful in hour-ahead markets. Although longer-term forecasting relies on numerical weather models, the statistical models used here focus on the short-term forecasts that can be useful in the hour-ahead markets.more » The purpose of the paper is not to develop forecasting models that can compete with commercially available models. Instead, we investigate the extent to which time-series analysis can improve simplistic persistence forecasts. This project applied a class of models known as autoregressive moving average (A RMA) models to both wind speed and wind power output. The results from wind farms in Minnesota, Iowa, and along the Washington-Oregon border indicate that statistical modeling can provide a significant improvement in wind forecasts compared to persistence forecasts.« less
  • This paper discusses how the American Petroleum Institute oil and gas standards were interfaced with International Electrotechnical Commission and other wind turbine and offshore industry standards to provide guidance for reliable engineering design practices for offshore wind energy systems.