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WIND ASSESSMENT and POWER PREDICTION from a WIND FARM in SOUTHERN SASKATCHEWAN a Thesis Submitted to the Faculty of Graduate

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WIND ASSESSMENT and POWER PREDICTION from a WIND FARM in SOUTHERN SASKATCHEWAN a Thesis Submitted to the Faculty of Graduate WIND ASSESSMENT AND POWER PREDICTION FROM A WIND FARM IN SOUTHERN SASKATCHEWAN A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Applied Science in Industrial Systems Engineering University of Regina By Mukundhan Chakravarthy Regina, Saskatchewan July, 2010 Copyright 2010: Mukundhan Chakravarthy Library and Archives Bibliotheque et Canada Archives Canada Published Heritage Direction du Branch Patrimoine de I'edition 395 Wellington Street 395, rue Wellington Ottawa ON K1A0N4 Ottawa ON K1A 0N4 Canada Canada Your file Votre reference ISBN: 978-0-494-88543-7 Our file Notre reference ISBN: 978-0-494-88543-7 NOTICE: AVIS: The author has granted a non­ L'auteur a accorde une licence non exclusive exclusive license allowing Library and permettant a la Bibliotheque et Archives Archives Canada to reproduce, Canada de reproduire, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par I'lnternet, preter, telecommunication or on the Internet, distribuer et vendre des theses partout dans le loan, distrbute and sell theses monde, a des fins commerciales ou autres, sur worldwide, for commercial or non­ support microforme, papier, electronique et/ou commercial purposes, in microform, autres formats. paper, electronic and/or any other formats. The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in this et des droits moraux qui protege cette these. Ni thesis. Neither the thesis nor la these ni des extraits substantiels de celle-ci substantial extracts from it may be ne doivent etre imprimes ou autrement printed or otherwise reproduced reproduits sans son autorisation. without the author's permission. In compliance with the Canadian Conformement a la loi canadienne sur la Privacy Act some supporting forms protection de la vie privee, quelques may have been removed from this formulaires secondaires ont ete enleves de thesis. cette these. While these forms may be included Bien que ces formulaires aient inclus dans in the document page count, their la pagination, il n'y aura aucun contenu removal does not represent any loss manquant. of content from the thesis. Canada UNIVERSITY OF REGINA FACULTY OF GRADUATE STUDIES AND RESEARCH SUPERVISORY AND EXAMINING COMMITTEE Mukundhan Chakravarthy, candidate for the degree of Master of Applied Science in Industrial Systems Engineering, has presented a thesis titled, Wind Assessment and Power Prediction From a Wind Farm in Southern Saskatchewan, in an oral examination held on June 24, 2010. The following committee members have found the thesis acceptable in form and content, and that the candidate demonstrated satisfactory knowledge of the subject material. External Examiner: Dr. Shahid Azam, Environmental Systems Engineering Supervisor: Dr. Amr Henni, Industrial Systems Engineering Committee Member: Dr. Ahmed Deif, Industrial Systems Engineering Committee Member: Dr. Ezeddin Shirif, Petroleum Systems Engineering Chair of Defense: Dr. Chris Oriet, Department of Psychology ABSTRACT Mesoscale and Microscale Modeling are two methods used to estimate wind energy resources. The main parameters of wind resource estimation are the mean wind speed and the mean wind power density. Mesoscale Modeling was applied to three different regions, Regina, Saskatoon, and Gull Lake, located in southern Saskatchewan, Canada. The areas were selected as centers of a domain for a grid with a horizontal resolution of 3 kilometers. Mesoscale Modeling was performed using the software tool, Anemoscope. Wind resources for the regions and the areas surrounding them have been generated for three elevations (30, 50, and 80 meters). As it is a site for a large wind turbine farm, the region in and around Swift Current in southern Saskatchewan (approximately 36 km x 36 km in area) was the site of choice for this study in Microscale Modeling. A widely popular software, WAsP, was chosen to perform the study. Statistical wind data was obtained from a Swift Current meteorological station over a period of ten years (2000-2009). A wind resource grid has been set up for the area at a horizontal resolution of 200 meters, and wind resource maps have been generated for heights of 50, 65, and 80 meters above ground level as the heights are the potential wind turbine hub heights. i In order to simulate the SaskPower Centennial Wind Power Station, a wind farm was set up with 83 wind turbines in the Coulee Municipality region near Swift Current. The annual energy production for the entire farm, along with those of the individual turbines, has been calculated. Both total and individual wind turbine productions were accurately modeled. ii ACKNOWLEDGEMENTS I would like to express my gratitude to those who gave me an opportunity to complete this thesis. I am deeply indebted to my supervisor, Dr. Amr Henni, whose guidance, encouragement, suggestions and financial support helped me throughout this research. I would like to thank the Faculty of Graduate Studies and Research for their financial support in the form of Graduate Scholarships and a Research Award. Also, I would like to thank my family and friends for their wonderful support and encouragement. iii LIST OF CONTENTS ABSTRACT i ACKNOWLEDGEMENTS iii LIST OF TABLES vi LIST OF FIGURES vii LIST OF SYMBOLS AND ABBREVIATIONS x CHAPTER 1: INTRODUCTION 1 1.1 General Introduction 1 1.2 Wind Resource Assessment Methods 4 1.3 Objectives and Scope of Work 6 CHAPTER 2: BACKGROUND FOR MODELING 8 2.1 Basic Theory and Definitions 8 2.2 Description of the Anemoscope and the MC2 Model 12 2.3 Overview of the WAsP Model 20 CHAPTER 3: WIND RESOURCE ESTIMATION USING ANEMOSCOPE 28 3.1 Structure of Anemoscope for Mesoscale Modeling 28 3.2 Input Preparation and Execution 29 3.3 Simulation Results and Discussion 36 iv CHAPTER 4: WIND RESOURCE ESTMATION USING WAsP 49 4.1 Structure of WAsP for a Resource Grid and a Wind Farm 49 4.2 Input Preparation and Execution 50 4.3 Simulation Results and Discussion Regarding Wind Resource 61 4.4 Simulation Results and Discussion Regarding Wind Farm Production 70 CHAPTER 5: CONCLUSION AND RECOMMENDATIONS 79 CHAPTER 6: REFERENCES 81 CHAPTER 7: APPENDICES 87 7.1 Appendix A - Notes Regarding the MC2 Model 87 7.2 Appendix B - Centennial Wind Power Facility 90 v LIST OF TABLES Table 2.1 Atmospheric Scales of Motion 8 Table 3.1 Inputs for Grid Configuration 33 Table 3.2 Mesoscale Wind Speed (m/s) Summary from Anemoscope Modeling 46 Table 3.3 Mesoscale Wind Power Density (W/m2) Summary from Anemoscope Modeling 47 Table 4.1a Observed Wind Climate Summary 52 Table 4.lb Observed Wind Climate Summary -Sector Wise 52 Table 4.2 Regional Wind Climate Summary 60 Table 4.3 Summary of the Resource Grid Simulation 69 Table 4.4 Wind Farm Summary, Based on 10 Years (2000 - 2009) Wind Data 72 Table 4.5 Wind Farm Summary, Based on Year 2007 Wind Data 72 Table 4.6 Wind Farm Summary, Based on Year 2008 Wind Data 73 Table 4.7 Wind Farm Summary, Based on Year 2009 Wind Data 73 Table 4.8 Year 2007 Annual Energy Production 75 Table 4.9 Year 2008 Annual Energy Production 76 Table 4.10 Year 2009 Annual Energy Production 77 vi LIST OF FIGURES Figure 2.1 Anemoscope Structure for Mesoscale Modeling 15 Figure 2.2 Wind Atlas Methodology 21 Figure 2.3 Weibull Distribution 27 Figure 3.1 Coasts.mif Map File in Polar Stereographic Coordinates 31 Figure 3.2 Wind Climate Database in Polar Stereographic Coordinates 31 Figure 3.3 Cities.mif in Polar Stereographic Coordinates 32 Figure 3.4 Mesoscale Grid Generation 32 Figure 3.5 Topography (elevation in metres) - Gengeo module output 35 Figure 3.6 Land Sea mask - Gengeo Module Output 35 Figure 3.7 Wind Speed at an Elevation of 30 m on a Grid Centered at Regina 37 Figure 3.8 Wind Power Density at an Elevation of 30 m on a Grid Centered at Regina 37 Figure 3.9 Wind Speed at an Elevation of 50 m on a Grid Centered at Regina 38 Figure 3.10 Wind Power Density at an Elevation of 50 m on a Grid Centered at Regina 38 Figure 3.11 Wind Speed at an Elevation of 80 m on a Grid Centered at Regina 39 Figure 3.12 Wind Power Density at an Elevation of 80 m on a Grid Centered at Regina 39 vii Figure 3.13 Wind Speed at an Elevation of 30 m on a Grid Centered at Saskatoon 40 Figure3.14 Wind Power Density at an Elevation of 30 m on a Grid Centered at Saskatoon 40 Figure 3.15 Wind Speed at an Elevation of 50 m on a Grid Centered at Saskatoon 41 Figure 3.16 Wind Power Density at an Elevation of 50 m on a Grid Centered at Saskatoon 41 Figure 3.17 Wind Speed at an Elevation of 80 m on a Grid Centered at Saskatoon 42 Figure 3.18 Wind Power Density at an Elevation of 80 m on a Grid Centered at Saskatoon 42 Figure 3.19 Wind Speed at an Elevation of 30 m on a Grid Centered at Gull Lake 43 Figure 3.20 Wind Power Density at an Elevation of 30 m on a Grid Centered at Gull Lake 43 Figure 3.21 Wind Speed at an Elevation of 50 m on a Grid Centered at Gull Lake 44 Figure 3.22 Wind Power Density at an Elevation of 50 m on a Grid Centered at Gull Lake 44 Figure 3.23 Wind Speed at an Elevation of 80 m on a Grid Centered at Gull Lake 45 viii Figure 3.24 Wind Power Density at an Elevation of 80 m on a Grid Centered at Gull Lake 45 Figure 4.1 Observed Wind Climate Summary 53 Figure 4.2 Vector Map with Height Contour and Roughness Lines 59 Figure 4.3 Mean Wind Speed at an Elevation of 50 m for the Swift Current Area 62 Figure 4.4 Mean Wind Power Density at an Elevation of 50 m for
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