Micrositing Optimization of the Block Island Wind Farm, RI, USA

2013 ◽  
Author(s):  
Christopher M. O’Reilly ◽  
Annette R. Grilli ◽  
Gopu R. Potty
Keyword(s):  
Renewable Energy ◽  
Objective Function ◽  
Rhode Island ◽  
Wind Farm ◽  
Clustering Algorithm ◽  
Cost Model ◽  
Wind Farms ◽  
Offshore Wind ◽  
Mitigating Factors ◽  
Initial Objective

The Rhode Island Ocean Special Area Management Plan (RIOSAMP) has been implemented in Rhode Island since 2008 to provide guidance to local regulators in the zoning of renewable energy, with a focus on the siting of offshore wind farms. The project culminated in the siting of the first North American offshore wind project, optimized using a spatial planning approach combining exclusionary and mitigating factors. The optimization of mitigating factors is based on a standard cost model approach and extended to include ecological and societal factors. This macro-siting optimization phase provided the framework to define a Renewable Energy Zone (REZ) for wind farm development and the present study seeks the siting optimization of the wind farm layout within this zone. The optimization considers the loss in power resulting from turbine wake interaction, a cable cost clustering algorithm, and the spatial variation of both foundation cost and the available wind resource within the REZ through a micrositing objective function. This initial objective function is extended to include ecological and social costs. The layout optimization is based on a Genetic Algorithm (GA) optimization scheme. The method is applied to the REZ area, demonstrating that a gain of approximately $10 million over 20 years could be obtained if an “optimal layout” would be selected over the initial layout chosen by the developers.

An Extended Pattern Search Method for Offshore Floating Wind Layout and Turbine Geometry Optimization

2016 ◽  
Author(s):  
Caitlin Forinash ◽  
Bryony DuPont
Keyword(s):  
Wind Farm ◽  
Cost Model ◽  
Geometry Optimization ◽  
Interaction Model ◽  
Solution Space ◽  
Wind Farms ◽  
Power Production ◽  
Pattern Search ◽  
Offshore Wind ◽  
Extended Pattern Search

An Extended Pattern Search (EPS) method is developed to optimize the layout and turbine geometry for offshore floating wind power systems. The EPS combines a deterministic pattern search with stochastic extensions. Three advanced models are incorporated: (1) a cost model considering investment and lifetime costs of a floating offshore wind farm comprised of WindFloat platforms; (2) a wake propagation and interaction model able to determine the reduced wind speeds downstream of rotating blades; and (3) a power model to determine power produced at each rotor, and includes a semi-continuous, discrete turbine geometry selection to optimize the rotor radius and hub height of individual turbines. The objective function maximizes profit by minimizing cost, minimizing wake interactions, and maximizing power production. A multidirectional, multiple wind speed case is modeled which is representative of real wind site conditions. Layouts are optimized within a square solution space for optimal positioning and turbine geometry for farms containing a varying number of turbines. Resulting layouts are presented; optimized layouts are biased towards dominant wind directions. Preliminary results will inform developers of best practices to include in the design and installation of offshore floating wind farms, and of the resulting cost and power production of wind farms that are computationally optimized for realistic wind conditions.

Application of Offshore Concrete Constructions for Ocean Renewable Energy Storage (ORES)

2014 ◽  
Vol 521 ◽  
pp. 703-706 ◽  
Author(s):  
Wei Feng Li ◽  
Su Hua Ma ◽  
Xiao Dong Shen
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Wind Farm ◽  
Wind Farms ◽  
Excess Energy ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Offshore Wind Farms ◽  
Ocean Renewable Energy ◽  
Renewable Energy Storage

Storage of energy generated by offshore wind farms still addresses one of the vexing problems inherent in offshore renewable energy such as offshore wind or solar energy how to store excess energy. Researchers tried to apply concrete in the energy storage of offshore wind farm recently, including the OTEC artificial energy islands, the MITS Ocean Renewable Energy Storage (ORES) and Belgiums energy atoll, and the progresses were reviewed.

scholarly journals OFFSHORE WIND FARM MACRO AND MICRO SITING PROTOCOL APPLICATION TO RHODE ISLAND

2012 ◽  
Vol 1 (33) ◽  
pp. 73 ◽  
Author(s):  
Annette Renee Grilli ◽  
Malcolm Spaulding ◽  
Christopher O'Reilly ◽  
Gopu Potty
Keyword(s):  
Rhode Island ◽  
Wind Farm ◽  
Cost Benefit ◽  
Principal Component ◽  
Wind Farms ◽  
Management Plan ◽  
Offshore Wind ◽  
Multivariate Statistical ◽  
Offshore Wind Farms ◽  
Special Area

Since 2008, the Rhode Island (RI) Coastal Resources Management Council has been leading the development of an Ocean Special Area Management Plan (Ocean SAMP), in partnership with the University of Rhode Island, resulting in an extensive multidisciplinary analysis of the Rhode Island offshore environment and its suitability to site offshore wind farms. As part of SAMP, a comprehensive macro-siting optimization tool: the Wind Farm Siting Index (WIFSI), integrating technical, societal, and ecological constraints, was developed within the conceptual framework of ecosystem services. WIFSI uses multivariate statistical analyses (principal component and k-means cluster analyses) to define homogeneous regions, which integrate and balance ecological and societal constraints as part of a Cost/Benefit tool. More recently, a Wind Farm micro-Siting Optimization Tool was developed (WIFSO), which uses a genetic algorithm to derive the optimal layout of a wind farm sited within one of the macro-siting selected regions. In this work, we present an overview of the current state of development of the integrated macro- and micro- siting tools.

scholarly journals A Minimalistic Prediction Model to Determine Energy Production and Costs of Offshore Wind Farms

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 448
Author(s):  
Jens Nørkær Sørensen ◽  
Gunner Christian Larsen
Keyword(s):  
Prediction Model ◽  
Wind Turbines ◽  
Water Depth ◽  
Energy Production ◽  
Wind Farm ◽  
Cost Model ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
The Cost

A numerical framework for determining the available wind power and associated costs related to the development of large-scale offshore wind farms is presented. The idea is to develop a fast and robust minimal prediction model, which with a limited number of easy accessible input variables can determine the annual energy output and associated costs for a specified offshore wind farm. The utilized approach combines an energy production model for offshore-located wind farms with an associated cost model that only demands global input parameters, such as wind turbine rotor diameter, nameplate capacity, area of the wind farm, number of turbines, water depth, and mean wind speed Weibull parameters for the site. The cost model includes expressions for the most essential wind farm cost elements—such as costs of wind turbines, support structures, cables and electrical substations, as well as costs of operation and maintenance—as function of rotor size, interspatial distance between the wind turbines, and water depth. The numbers used in the cost model are based on previous but updatable experiences from offshore wind farms, and are therefore, in general, moderately conservative. The model is validated against data from existing wind farms, and shows generally a very good agreement with actual performance and cost results for a series of well-documented wind farms.

scholarly journals Multi-Criteria Fuzzy Evaluation of the Planned Offshore Wind Farm Investments in Poland

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 978
Author(s):  
Paweł Ziemba
Keyword(s):  
Renewable Energy ◽  
Wind Farm ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
Offshore Wind ◽  
Fuzzy Evaluation ◽  
Offshore Wind Farms ◽  
Multi Criteria Evaluation ◽  
Total Capacity ◽  
Polish Economy

In recent years, the dynamic development of renewable energy has been visible all over the world, including Poland. Wind energy is one of the most used renewable energy sources. In Poland, by 2030, it is planned to commission at least six offshore wind farms with a total capacity of 3.8 GW. It is estimated that these investments will increase Poland’s GDP by approximately PLN 60 billion and increase tax revenues by PLN 15 billion. Therefore, they could be a strong stimulus for the development of the Polish economy and may be of great importance in recovering from the crisis caused by the economic constraints related to the COVID-19 pandemic. The aim of the article is a multi-criteria evaluation of the investments planned in Poland in offshore wind farms and identification of potentially the most economically effective investments. To account for the uncertainty in this decision problem, a modified fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was used and a comprehensive sensitivity analysis was performed. As a result of the research, a ranking of the considered projects was constructed and the most preferred investments were identified. Moreover, it has been shown that all the investments considered are justified and recommended.

scholarly journals A Review of Rapid Distortion Theory

2022 ◽  
Author(s):  
S.L. Basu
Keyword(s):  
Renewable Energy ◽  
Wind Farm ◽  
Renewable Energy Sources ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Rapid Distortion Theory ◽  
Wake Turbulence ◽  
Counter Rotation ◽  
Increasing Demand

Abstract. With the depleting non-renewable fuel sources like coal and an ever-increasing demand for energy, we need to start looking into renewable energy sources. These are of paramount importance for a sustainable and green future. Wind Energy is one of the most important sources of renewable energy. But, setting up a wind farm requires considerable land area and land acquisitions are often faced with legal hurdles. This necessitates setting up offshore wind turbines. But, when we talk about offshore wind farms, we need to address the age-old phenomenon: “Turbulence”. Presently, we are trying to develop enhanced controllers for wind farms which will increase the efficiency of the wind farms. The effects of rapidly changing wake aerodynamics i.e. breakdown of strong tip and hub vortices mixed up with low intensity turbulence in the inflow of the rotor and counter-rotation of the wake i.e. determinate velocity component in wake turbulence field will affect the overall performance of the wind farm. This paper provides a brief review on Rapid Distortion Theory (RDT) to model the turbulence.

scholarly journals Managing the Volatility Risk of Renewable Energy: Index Insurance for Offshore Wind Farms in Taiwan

2021 ◽  
Vol 13 (16) ◽  
pp. 8985
Author(s):  
Shih-Chieh Liao ◽  
Shih-Chieh Chang ◽  
Tsung-Chi Cheng
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Wind Power ◽  
Wind Farm ◽  
Wind Farms ◽  
Insurance Contract ◽  
Offshore Wind ◽  
Total Power ◽  
Index Insurance ◽  
Offshore Wind Power

Renewable energy is produced using renewable natural resources, including wind power. The Taiwan government aims to have renewable energy account for 20% of its total power supply by 2025, in which offshore wind power plays an important role. This paper explores the application of index insurance to renewable energy for offshore wind power in Taiwan. We employ autoregressive integrated moving average models to forecast power generation on a monthly and annual basis for the Changhua Demonstration Offshore Wind Farm. These predictions are based on an analysis of 39 years of hourly wind speed data (1980–2018) from the Modern-Era Retrospective analysis for Research and Applications, Version 2, of the National Aeronautics and Space Administration. The data analysis and forecasting models describe the methodology used to design the insurance contract and its index for predicting offshore wind power generation. We apply our forecasting results to insurance contract pricing.

Potential Impacts from a Worst Case Discharge from an United States Offshore Wind Farm

2014 ◽  
Vol 2014 (1) ◽  
pp. 869-877
Author(s):  
CDR Tim Gunter
Keyword(s):  
United States ◽  
Wind Energy ◽  
New England ◽  
Rhode Island ◽  
Wind Farm ◽  
Wind Farms ◽  
The United States ◽  
Offshore Wind ◽  
Offshore Wind Energy ◽  
Worst Case

ABSTRACT The main purpose of this research is to explore potential environmental impacts of a worst case discharge (WCD) from an offshore commercial wind farm electric service platform (ESP) in the Northeast United States. Wind farms in the continental United States are a growing industry as an energy alternative to traditional oil, coal, and natural gas energy sources. While many offshore wind farms already exist in Europe and around the world, the Cape Wind Project in New England received the first federally approved lease for an offshore wind energy production facility in the United States. While offshore wind energy is a green source of energy, wind driven energy has its own set of environmental risks, including the risks of an oil spill. A systematic review of scholarly journals, federal government websites and other academic resources was conducted to identify previous spills in the Northeast with the closest match in volume and location to the Cape Wind Project. The oil spills from the barge North Cape in 1996 near Point Judith, Rhode Island and from the barge Florida in Buzzards Bay, Massachusetts, in 1996, had the most similarities to a potential WCD spill from the Cape Wind Project. Both of these spills adversely impacted the environment, and provide useful information that can be used for the planning efforts surrounding a WCD event from the Cape Wind Project.

scholarly journals Wind Turbine Clustering Algorithm of Large Offshore Wind Farms considering Wake Effects

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Binbin Zhang ◽  
Jun Liu
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Clustering Algorithm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Wake Effect ◽  
Offshore Wind Farms ◽  
Power Simulation ◽  
Value Decomposition

This paper proposed the SVD (singular value decomposition) clustering algorithm to cluster wind turbines into some group for a large offshore wind farm, in order to reduce the high-dimensional problem in wind farm power control and numerical simulation. Firstly, wind farm wake relationship matrixes are established considering the wake effect in an offshore wind farm, and the SVD of wake relationship matrixes is used to cluster wind turbines into some groups by the fuzzy clustering algorithm. At last, the Horns Rev offshore wind farm is analyzed to test the clustering algorithm, and the clustering result and the power simulation show the effectiveness and feasibility of the proposed clustering strategy.

Sign in / Sign up

Export Citation Format

Share Document