1 Copyright © 2013 by ASME Proceedings of the ASME 2013 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2013 August 4-7, 2013, Portland, Oregon, USA DRAFTDETC2013-13433 DRAFT: EFFECTS OF UNCERTAIN LAND AVAILABILITY, WIND SHEAR, AND COST ON WIND FARM LAYOUT Le Chen Ames National Laboratory Affiliated Researcher Department of Mechanical Engineering Iowa State University Ames, IA, U.S. Email:lechen@iastate.edu Erin MacDonald Ames National Laboratory Affiliated Researcher Department of Mechanical Engineering Iowa State University Ames, IA, U.S. Email:erinmacd@iastate.edu ABSTRACT The robust optimization presented in this paper is formulated to assist in early-stage wind farm development. It can help wind farm developers predict project viability and can help landowners predict where turbines will be placed on their land. A wind farm layout is optimized under multiple sources of uncertainty. Landowner participation is represented with a novel uncertain model of willingness-to-accept monetary compensation. An uncertain wind shear parameter and economies-of-scale cost reduction parameter are also included. Probability Theory, Latin Hypercube Sampling, and Compromise Programming are used to form the robust design problem and minimize the two objectives: the normalized mean and standard deviation of Cost-of-Energy. The results suggest that some landowners that will only accept high levels of compensation are worth pursuing, while others are not. 1 INTRODUCTION Price, supply uncertainty, and environmental concerns are motivating the United States to develop sources of clean and renewable energy. For example, the U.S. Department of Energy [1] has a goal of obtaining 20% of U.S. electricity from wind by the year 2030. In order to reach this goal, government, academic researchers, and industry are working together to improve the cost effectiveness of wind energy. One area to address is improving the accuracy of predicting wind farm viability earlier in the development of the project. Developers must model many important factors, such as wind resource, availability of land, topography, access of roads and transmission lines, and others to predict the cost-of- energy (COE) of a farm. COE is the basic metric by which farm viability is judged. During the early stages of a farm development, i.e. pre-feasibility and feasibility analysis [2], these factors are associated with great uncertainties. Their accuracy is limited by cost and accessibility. For example, developers cannot conduct a full site survey until they have obtained the permission from landowners to access their land. Although they have limited and uncertain information, developers must make important and expensive decisions, such as placing equipment orders or obtaining funding from potential project backers. Likewise, landowners must decide on their participation in the project without knowing exactly, or even roughly, where turbines will be placed on their land. These decisions have high levels of risk. Studying the wind farm layout optimization problem under uncertainty can mitigate this risk. Most Wind Farm Layout Optimization (WFLO) research focuses on a relatively certain environment. For a thorough literature review, refer to our previous work [3]. Several researchers consider some uncertain characteristics of WFLO. For example, Messac et al., take into account the uncertainty in farm performances due to wind resource [4], while DuPont et al. consider the variation of wind shear profile shape in the WFLO [5]. None of the previous work has investigated diversified sources of uncertainty, yet it is this interaction that causes the high level of risk in early- stage development decisions. A sensitivity analysis found two influential parameters: wind shear and the economies-of-scale cost-reduction factor for purchasing multiple turbines [6]. This paper models these two parameters as uncertain. Additionally, landowner decisions are