Date of Award

2013

Degree Type

Thesis

Degree Name

Master of Science in Ocean Engineering

Department

Ocean Engineering

First Advisor

Anette R. Grilli

Abstract

Since 2008, the Rhode Island Coastal Resources Management Council (CRMC) has been leading a Rhode Island Ocean Area Management Plan (RIOSAMP) in partnership with the University of Rhode Island, resulting in an extensive multidisciplinary analysis of the Rhode Island offshore environment and its suitability for siting an offshore wind farm. As part of the RIOSAMP project, a standard siting optimization approach was first developed based on a siting index defined as the ratio of costs associated with the wind farm deployment to the available wind resource. This index, combined within a marine spatial planning approach to address ecological and societal constraints, provided an initial macro-siting tool (Spaulding et al., 2010). The multiple GIS layers required in this approach and the absence of theoretical support to optimize the resulting zoning, led to an extension of the initial optimization approach into a more comprehensive macro-siting optimization tool, integrating societal and ecological constraints into the siting tool, the Wind Farm Siting Index (WIFSI) (Grilli et al, 2012). The projects led to the definition of several favorable development areas including a Renewable Energy Zone (REZ) off of Block Island, in State Waters. Deep Water Wind Inc. (DWW) plans to install and commission five 6 MW direct drive Siemens lattice jacket turbines in the REZ area, by 2014.

In this thesis two major steps are accomplished to refine and expand the RIOSAMP macro-siting tool. First the macro-siting tool is expanded to include a model simulating the exclusionary zones defined by the Federal Aviation Administration (FAA) regulations. Second a micro-siting model is developed, optimizing the relative position of each turbine within a wind farm area. The micro-siting objective is to minimize, (1) the loss in power due to the loss of wind resource in the wake of the turbines (wake “effect”), and (2) the cable costs that inter-connect the turbines and connecting the farm to the land. The REZ area is chosen as test site for the algorithm, and an optimal layout for the 5 turbines is found and discussed. Similarly the FAA tool is applied to the Block Island airport demonstrating the complexity of the FAA exclusionary area, and defining the limits of the exclusionary areas.

The FAA regulation model is a geometric model in which all major (FAA) regulations within RI and the RI topography are embedded. The user specifies the dimension of the proposed turbines and an airport of interest, and a map of exclusionary zones specific to the turbine height and rules applying to the airport is generated. The model is validated for the entire state of Rhode Island.

The micro-siting model finds the optimum placement of each turbine for a given number of turbines within an area. It includes the aerodynamic constraints (loss in wind speed within the wake of a turbine) associated to the deployment of arrays of turbines and the cable interconnection cost. It is combined with the technical, ecological, and social constraints used in the RIOSAMP macro-siting tool to provide a comprehensive micro-siting tool. In the optimization algorithm, a simple wake model and turbine-clustering algorithm are combined with the WIFSI in an objective function; the objective function is optimized with a genetic algorithm (GA).

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