Wind Speed Data Collected at a Proposed Site for Wind Energy Development
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A Statistical Analysis and Fuzzy Logic Approach in Assessing the Performance of Wind Turbine in Ohio A Thesis Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University By Mikail Suleiman, M.S. Graduate Program in Civil Engineering 2010 Thesis Committee: Fabian Hadipriono Tan, Advisor William E. Wolfe Qian Chen Copyright by Mikail Suleiman 2010 ABSTRACT The global demand for petroleum products has caused the rise in their cost. In fact, the cost of petroleum products to generate electricity supply to meet the United States’ energy demand is on a continuous rise. As a result, this rise in cost of petroleum products has challenged our nation to seek an alternative source of renewable energy generation. Wind energy generation is one of the fastest growing forms of electricity generation in the world today compared to other sources of renewable energy. According to the National Renewable Energy Laboratory, the United States currently generate more than 25,000 megawatts (MW) of electricity from the wind, which is enough to power electricity supply to almost 7 million homes, and experts in wind power development predict that, with proper development, wind energy could provide 20% of the nation's energy needs. To perform an assessment for a feasible wind energy project and wind turbine performance, an empirical analysis using statistical models was performed on wind speed data collected at a proposed site for wind energy development. Because of the variability in wind speed and wind turbine location, a subjective description of wind turbine location using a fuzzy logic approach was used to define the two variables, and quantify the different components and elements of the wind turbine performance and wind turbine location, and subsequently to evaluate the total wind farm development project ii performance using two forms of fuzzy member. Two software programs were developed using the concept of fuzzy logic, which transforms the linguistic expressions such as “Low,” “Fairly Low,” “Medium,” “Fairly High” and “High,” into mathematical representations. The two fuzzy logic models created were the “angular model” and the “triangular model,” which were used to complement the statistical models in assessing the wind turbine location and turbine performance. The angular model and triangular model incorporate users’ subjective preferences and choices based on the information available to them. This study advances the assessment of a wind energy development project by harnessing the available wind resource to help meet the nation’s goal of providing 20% of the nation electricity demand 2030. If properly implemented, wind energy development would help reduce the consumption of 4 trillion gallons of water and reduce CO2 emissions, reduce total natural gas consumption by 11%, reduce electric utility coal consumption by 18%, reduce electric utility natural gas consumption by 50% and avoid construction of 80 GW of new coal power plants through year 2030. iii DEDICATION This research work is dedicated to my parent, Mr. Suleiman Aka’aba & Mrs. Halima Aka’aba iv ACKNOWLEDGEMENTS First and foremost, I would like to express my gratitude to Mrs. Dr. Tan for her patience and understanding while Dr. Fabian Hadipriono Tan stayed late in his office to work with his student. My sincere appreciation to Dr. Fabian Hadipriono Tan for over the years, he has dedicated himself to the student he has taught, mentored and shared his experiences and above all providing me with the best advice and guidance, and he challenged and extended me to a new academic heights. His patience and genuine concern had no boundaries. Dr. Tan, …yes as always, you are simply the best and you were the best advisor I could have ever hoped, prayed, and asked for, and to that end I am forever grateful to you. I would like to thank the Masters Examination committee members; Dr. William Wolfe and Dr. Qian Chen for their valuable suggestions to this research work. I would like to thank my parents, Mr. Suleiman Aka’aba and Mrs. Halima Aka’aba for their continuous support, encouragement and constant prayers, and to all my siblings and their spouse for their support and tireless prayers; Amina, Sadiya, Fatima, Zubair and Hafsat… to you all, I say thank you. To my wife Alisha for I may not have say “thank you” at all times, but your support and patience during this research work and at all time are very well appreciated and I say thank you for all your help and I love you. v This is to you my very good friend, Aous Al-Khalidi, whom I owe a thank you, for your help and all incessant support and enlightening discussions during my graduate studies. Thank you Emily Sautter, for all your help in guiding me through the review process of the data sets collected for this research work and to you Charm Damon for editing this research work. Also, I would like to thank my family and friends for their much needed support, Dr. Abdulshafi & Family, Brigadier Saka Abubakar, Dr. William Olorunto & Family, Mr. Ben Bosah & Family, Mr. Val Mbah & Family, Mr. Abdirahim Abdi, and to all my friends not mentioned, but not forgotten, I thank you all for your friendship and support during my graduate studies! To Mikail Zayd Aka’aba for you are the future greatest Engineer! vi VITA September 1964…………………………...Born-Sokoto, Nigeria 1990……………………………………….B.S. Civil Engineering, Kaduna Polytechnic, Kaduna Polytechnic, Kaduna 2003……………………………………….M.S. Administration, Central Michigan University, Mt. Pleasant, Michigan, U.S.A 2003 to present……………………………Member, American Military Engineers 2003 to present……………………………Member, American Society of Civil Engineers 2003 to present……………………………Member, Institute of Transportation Engineers 2003 to present……………………………Member, IEEE Computational Intelligence Society 2009 – 2010……………………………….Emmett Karrer Scholarship Award 2008 – 2010.………………………………Graduate Student, The Ohio State University 1997 – 2000….……………………………Field Engineer – Construction Padia Environmental, Inc. Worthington, Ohio 2000 to present……………………………Project Manager – Construction Inspection Division of Design & Construction City of Columbus, Columbus, Ohio FIELDS OF STUDY Major Field: Civil Engineering Specialization: Construction Engineering & Management vii TABLE OF CONTENTS Page Abstract….…………………………………………………………………………….ii Dedication.…………………………………………………………………………….iv Acknowledgements..………………………………………………….........................v Vita..…………………………………………………………………………………..vii List of Tables..………………………………………………………………………...xii List of Figures.………………………………………………………………………..xiii Chapter 1: Introduction.……………………………………………………………….1 1.1 Introduction .……………………………………………………....1 1.2 Objectives of the Study…………………………………………....3 1.3 Benefits of the Study ………………………………......................4 1.4 Scope & Limitation………………………………….....................5 1.5 Organization of the Study ………………………………………...6 Chapter 2: Literature Review………………………………………………………….7 2.1 Introduction………………………………………………………..7 2.1.1 Characteristics of Wind Resource & Atmospheric Boundary Layer ……………………………………...10 2.2 Wind Data Collection & Measurement…………………………..17 2.2.1 Wind Measurement & Instrumentation…………………17 2.2.2 Wind Data Acquisition & Analysis..…………………...18 2.2.3 Raw Data Collection…………………………………....18 viii 2.2.4 Data Storage, Retrieval & Documentation…………….19 2.2.5 Data Validation……………………….………………..19 2.3 Statistical Analysis Studies………………………………………22 2.3.1 Statistical Data…………………………..……………. 22 2.3.2 Wind Data Analysis & Resource Estimation………….31 2.3.3 Structure of Wind Measuring System…..……………..33 2.3.4 Wind Power Cost and Financing………………………34 2.3.5 Wind Turbine Energy Production Estimate…………...38 2.3.6 Accuracy of Period for Return on Investment.………..39 2.4 Wind Speed Predictive Models..………………………………...41 2.5 Fuzzy Logic Studies..……………………………………………44 Chapter 3: Methodology of Studies.…………………………………………………47 3.1 Introduction..…………………………………………………….47 3.2 Statistical Analysis Studies..…………………………………….47 3.2.1 Wind Direction..………………………..……………...51 3.2.2 Cubic Wind Speed..………………..…..………………58 3.2.3 Wind Shear Analysis..…………………………………60 3.2.4 Wind Turbulent Intensity..…………………. ………...64 3.2.5 Air Density..…………………………………………...67 3.2.6 Wind Power Density..…………………..…………......69 3.2.7 Regression Fit Analysis and Trend Analysis..………...72 3.2.8 Wind Power Generation Analysis……………………..79 ix Chapter 4: Assessment of Wind Turbine System Using Angular Model……………87 4.1 Introduction……………………………………………...87 4.2 Approximate Reasoning…………………………………………90 4.3 Angular Fuzzy Set Model..………………………………………92 4.3.1 TFM Using Angular Model…………………………....92 4.3.2 ITFM Using Angular Model…………………………...96 4.3.3 Fuzzy Modus Ponens Deduction……………………………….99 4.4 Illustration of Angular Model…………………………………...104 Chapter 5: Assessment of Wind Turbine System Using Triangular Model.………..110 5.1 Introduction...…………………………………………………...110 5.2 The Triangular Fuzzy Set Model………………………………..111 5.3 Mamdani Inference System Approach………………………….112 5.3.1 The Fuzzification Unit………………………………...113 5.3.2 The Fuzzy Rule Base Unit…………………………….114 5.3.3 Fuzzy Inference Engine Unit………………………….114 5.3.4 The Defuzzification Unit……………………………...117 5.3.4.1 The Centroid Method………………………..117 5.3.4.2 The Weighted Average Method……………..118 5.3.4.3 The Mean Max Membership Method.………123 5.3.4.4 The Max Membership Method.……………..124 5.3.4.5 The Center of Sums Method.………………..125 5.3.4.6 The Center of Largest Area Method.………..128 5.3.4.7 The First (or Last) of Maxima Method………129 x 5.4 Illustration