A Review of Wind Energy Technologies

Renewable and Sustainable Energy Reviews 11 (2007) 1117–1145 resources assessment models, site selection models and aerodynamic models including wake effect. 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1118 2. World wind energy scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1119 ARTICLE IN PRESS www.elsevier.com/locate/rser � 1364-0321/$ - see front matter r 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.rser.2005.08.004 Corresponding author. Tel.: +9144 235 1723. E-mail address: iniyan777@hotmail.com (S. Iniyan). The different existing performance and reliability evaluation models, various problems related to wind turbine components (blade, gearbox, generator and transformer) and grid for wind energy system have been discussed. This paper also reviews different techniques and loads for design, control systems and economics of wind energy conversion system. r 2005 Elsevier Ltd. All rights reserved. Keywords:Wind power technology; Reliability evaluation model; Aerodynamic model; Wind resource assessment Contents A review of wind energy technologies G.M. Joselin Herberta, S. Iniyanb,�, E. Sreevalsanc, S. Rajapandiand aDepartment of Mechanical Engineering, St. Joseph’s College of Engineering, Chennai-119, India bDepartment of Mechanical Engineering, Anna University, Chennai-25, India cCenter for Wind Energy Technology (C-WET), Chennai 601-302, India dElectrical Department, Sathyabama Institute of Science and Technology, Chennai-119, India Received 17 August 2005; accepted 25 August 2005 Abstract Energy is an essential ingredient of socio-economic development and economic growth. Renewable energy sources like wind energy is indigenous and can help in reducing the dependency on fossil fuels. Wind is the indirect form of solar energy and is always being replenished by the sun. Wind is caused by differential heating of the earth’s surface by the sun. It has been estimated that roughly 10 million MW of energy are continuously available in the earth’s wind. Wind energy provides a variable and environmental friendly option and national energy security at a time when decreasing global reserves of fossil fuels threatens the long-term sustainability of global economy. This paper reviews the wind 1. Introduction ARTICLE IN PRESS The wind turbine technology has a unique technical identity and unique demands in terms of the methods used for design. Remarkable advances in the wind power design have been achieved due to modern technological developments. Since 1980, advances in aerodynamics, structural dynamics, and ‘‘micrometeorology’’ have contributed to a 5% annual increase in the energy yield of the turbines. Current research techniques are producing stronger, lighter and more efficient blades for the turbines. The annual energy output for turbine has increased enormously and the weights of the turbine and the noise they emit have been halved over the last few years. We can generate more power from wind energy by establishment of more number of wind monitoring stations, selection of wind farm site with suitable wind electric generator, improved maintenance procedure of wind turbine to increase the machine availability, use of high capacity machine, low wind regime turbine, higher tower height, wider swept area of the rotor blade, better aero- dynamic and structural design, faster computer-based machining technique, increasing power factor and better policies from Government. Even among other applications of renewable energy technologies, power generation through wind has an edge because of its technological maturity, good infrastructure and relative cost competitiveness. Wind energy is expected to play an increasingly important role in the future national energy scene [1,2]. Wind turbines convert the kinetic energy of the wind to electrical energy by rotating the blades. Greenpeace states that about 10% electricity can be supplied by the wind by the year 2020. At good windy sites, it is already competitive with that of traditional fossil fuel generation technologies. With this improved 2.1. Wind turbine sizes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1119 2.2. Wind power in selected countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1119 2.3. Future wind power development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1121 3. Wind resource assessment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1121 4. Site selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1123 5. Wind turbine aerodynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1123 5.1. Wake effect . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1125 6. Performance and reliability of wind turbines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1125 6.1. Reliability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1127 7. Problems associated with wind turbines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1127 8. Wind turbine technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1128 8.1. Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1128 8.2. Loads . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1129 8.3. Blade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1130 8.4. Gearbox . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1132 8.5. Generator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1132 8.6. Transformer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1134 9. Grid connection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1134 10. Control system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1135 11. Economics of wind turbine system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1136 12. Application of wind turbine converters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1136 13. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1137 G.M. Joselin Herbert et al. / Renewable and Sustainable Energy Reviews 11 (2007) 1117–11451118 technology and superior economics, experts predict wind power would capture 5% of the ARTICLE IN PRESS world energy market by the year 2020. Advanced wind turbine must be more efficient, more robust and less costly than current turbines. Ministry of Non-conventional Energy Sources (MNES), Indian Renewable Energy Development Agency (IREDA) and the wind industry are working together to accomplish these improvements through various research and development programs. This article gives a brief overview of various wind turbine technologies. 2. World wind energy scenario The technical potential of onshore wind energy is very large—20,000� 109–50,000� 109 kWh per year against the current total annual world electricity consumption of about 15,000� 109 kWh. The economic potential depends upon factors like average wind speed, statistical wind speed distribution, turbulence intensities and the cost of wind turbine systems. The Global Wind Energy Council is the global forum for the wind energy sector, uniting the wind industry and its representative associations. The members operate in more than 50 countries and represent over 1500 organizations involved in hardware manufacturer, project development, power generation, finance and consultancy, as well as researchers and academics. The global wind power industry installed 6614MW in the year 2004, an increase in total installed generating capacity of nearly 20%. The cumulative global wind power capacity has grown to 46,048MW. The countries with the highest total installed wind power capacity are Germany 16,500MW, Spain 8000MW, The United States 6800MW, Denmark 3121MW and India 2800MW. The top five countries account for nearly 80% of total wind energy installation worldwide. A number of countries, including Italy, the Netherlands, Japan and the UK, are above near the 1000MW mark. The detailed operating wind power capacity for different countries are shown in Table 1. Europe continued to dominate the global market in 2004, accounting for 73% of new installations, 4825MW. Asia had a 12.4% share 822MW and the Pacific Region 4.4%, 291MW, Middle East Africa 1.1%, 71MW followed by Latin America 0.64%, 42MW. 2.1. Wind turbine sizes In the early and mid-1980s, the typical wind turbine size was less than 100 kW. By the late 1980s and early 1990s, turbine sizes had increased from 100 to 500 kW. Further, in the mid-1990s, the typical size ranged from 750 to 1000 kW. And by the late 1990s, the turbine size had gone up to 2500 kW. Now turbines are available with capacities up to 3500 kW. 2.2. Wind power in selected countries Till the early 1980s, the Unites States possessed 95% of the world’s installed capacity. In the early 1980s, combined Federal and State investment tax credits amounted to 50–55% of the investment. In United States, the cost of wind-generated electricity has fallen from 35b/kWh in the mid-1980s to 4b/kWh at prime wind sites in 2001. In United States, wind- generating capacity is growing by leaps and bounds. The 300MW Stateline Wind Project under construction on the border between Oregon and Washington will be the world’s G.M. Joselin Herbert et al. / Renewable and Sustainable Energy Reviews 11 (2007) 1117–1145 1119 largest wind farm. ARTICLE IN PRESS Table 1 Operating wind power capacity in MW Europe Start 2004 End 2004 USA Start 2004 End 2004 Pacific Region Start 2004 End 2004 Germany 14,609 16,500 California 2016 2045 Japan 644 740 Spain 6202 8000 Texas 1305 1396 Australia 198 252 Denmark 3115 3121 Lowa 472 632 New Zealand 38 168 Netherlands 912 1077 Minnesota 562 577 Pacific 0 11 G.M. Joselin Herbert et al. / Renewable and Sustainable Energy Reviews 11 (2007) 1117–11451120 Europe is the global leader in wind energy, and witnessing the globalization of the wind energy markets. In Europe, the market has experienced average annual growth rates of 22% over the past 6 years. The European Wind Energy Association has recently revised its 2010 wind capacity projections for Europe from 4� 104MW to 6� 104MW. In Europe, offshore projects are now springing up off the coasts of Belgium, Denmark, France, Germany, Ireland, Netherlands, Scotland, Sweden and United Kingdom. Once a country has developed 100MW of wind-generating capacity, it tends to move quickly to develop its wind resources. The United States crossed this threshold in 1983. In Denmark, this occurred in 1987. In Germany, it was 1991, followed by India in 1994 and Spain in 1995. Island Italy 891 1020 Wyoming 284 284 Total 880 1171 UK 704 944 New Mexico 206 266 Asia Austria 415 585 Oregon 261 261 India 2120 2800 Sweden 399 428 Washington 244 244 China 566 700 Portugal 299 409 Colorado 223 229 Taiwan 8 16 Greece 398 398 Oklahoma 176 176 South Korea 8 8 France 240 390 Pennsylvania 128 129 Sri Lanka 3 3 Ireland 225 256 Kansas 113 113 Total 2705 3527 Norway 112 160 Illinois 50 105 Middle East & Africa Finland 47 82 North Dakota 66 66 Egypt 69 140 Belgium 68 68 West Virginia 66 66 Morocco 54 54 Poland 58 58 Wisconsin 53 53 Tunisia 20 20 Ukraine 51 57 New York 49 49 Iran 11 11 Latvia 24 24 South Dakota 44 44 Israel 8 8 Luxembourg 16 24 Tennessee 2 29 Cape Verde 3 3 Turkey 20 20 Nebraska 15 15 South Africa 3 3 Czech Republic 10 10 Ohio 4 8 Jordan 2 2 Russia 7 7 Vermont 6 6 Total 170 241 Switzerland 5 8 Michigan 3 3 Latin America Hungary 2 6 Hawaii 2 2 Costa Rica 71 71 Estonia 5 5 Alaska 1 1 Caribbean 13 55 Slovakia 0 2 Massachusetts 1 1 Brazil 29 29 Romania 1 1 Total 6352 6800 Argentina 26 26 Total 28,835 33,660 Canada 326 441 Columbia 20 20 World total wind power capacity is 46,048MW Mexico 5 5 Chile 2 2 Total 166 208 Source: Wind power monthly, January 2005. ARTICLE IN PRESS Germany has made impressive gains in installed wind capacity since 1991, and is now setting the trend for Europe’s future. In mid-1997, Germany surpassed the US as the country with the largest wind capacity. There is 1891MW capacity increase in 2004, while the installed capacity at end 2004 is 16,500MW. Denmark ranks as the world’s largest manufacturer and exporter of wind turbines and it has the third largest capacity in the world. Almost 60% of the world’s wind turbines are manufactured in Denmark. The Danish government has set substantial targets for growth in wind-powered electricity generation and expects it to account for 50% of domestic generation by 2030. Spain has seen substantial growth in wind power capacity in the past several years. The current capacity stands at 8000MW. The government encourages the development by offering producers a choice of incentives. Australia has some of the most powerful and abundant untapped wind resources on the planet and a grid capacity that can potentially accommodate up to 8000MW of wind energy with minor adjustments. The year 2004 was a record year for the Canadian wind energy industry with 116MW of new installed capacity. Recent developments in Federal and Provincial energy policy promise a 10-fold increase in Canada’s total installed wind energy capacity over the next 5 years said CanWEA (Canadian Wind Energy Association) President Robert Hournung. India ranks fifth in installed wind capacity. India has witnessed unprecedented growth in the wind energy sector. During the last fiscal year, i.e. 2003–2004, wind energy capacity in India grew by more than 35%. Japan plans to attain the wind power target of 3000MW by the year 2010 after the Kyoto Protocol. It has installed about 740MW to date, which is 20 times in comparison to 5 years ago and one third of the national target [3]. 2.3. Future wind power development Under the international agreements on Environment commitments scenario, the penetration is expected to be faster and the 10% level is achieved by the year 2016. The expected saturation level capacity is 1.9� 109 kW occurring at 2030–35. 3. Wind resource assessment The study of geographical distribution of wind speeds, characteristic parameters of the wind, topography and local wind flow and measurement of the wind speed are very essential in wind resource assessment for successful application of wind turbines. A brief review of these assessment techniques have been reviewed in this literature. Kocak was concerned with speed persistence, which is an important factor in maintaining wind energy production [4]. Wood determined the optimum tower height using power law and by algorithmic law. The optimum height increases as the wind shear increases for village and suburban terrain [5]. The site with annual mean wind speed of 20 km/h with a hub height of 30m and power density of 150W/m2 is economically viable annual wind speed for power generations. The Weibull density function had been used by Weisser for the analysis of wind energy potential of Grenada (West Indies) based on historic recordings of mean hourly wind velocity [6]. Panda et al. made a stochastic analysis of the wind energy potential at seven representative weather stations in India. A probability model for the wind data and potential has been developed. They used Box–Cox G.M. Joselin Herbert et al. / Renewable and Sustainable Energy Reviews 11 (2007) 1117–1145 1121 transformation to transform the data for all of the stations to a normal distribution [7]. ARTICLE IN PRESS Lambert et al. described full-scale instrumentation and analysis of tall-guyed lattice masts to correlate wind speed and direction with structural stresses, particularly in welds [8]. Sami et al. proposed a probabilistic model to assess the energy resources available from wind energy conversion systems at two sites, which enables the representation of equipment failure modes and the intermittent nature of the wind resource [9]. Jamil et al. used Weibull probability distribution function to find out the wind energy density and other wind characteristics with the help of the statistical data of 50 days wind speed measurements the Materials and Energy Research Centre (MERC)-solar site, Tehran in Iran [10]. A Cumulative Semi-Varigram (CSV) model had been derived by Zekai Sen and Ahmet D. Sahin to assess the regional patterns of wind energy potential along the western Aegean Sea coastal part of Turkey. This innovative technique provides clues about regional variations along any direction. The CSV technique yielded the radius of influence for wind velocity and Weibull distribution parameters. The dimensionless standard regional dependence (SRD) functions are obtained from the sample CSV, which has been used to make simple regional predictions for the wind energy or wind velocity distribution parameters [11]. Youcef Ettoumi et al. used first-order Markov chain and Weibull distribution methods for statistical bivariate modeling of wind using the data wind speed and wind direction measurements collected every 3 h at the meteorological station of Essenia (Oran, a state in Algeria). Also, a detailed study has been made on the statistical features of the wind at Oran [12]. Torre et al. proposed Markovian model for studying wind speed time series in Corsica because a stochastic model like a Markov chain seems to be more accurate [13]. Feijoo et al. suggested two methods for assessing the effect of multiple wind turbines on a large power system based on Monte Carlo wind speed simulation of different wind farms where measurements of average values and correlation are included [14]. Ulgen et al. studied the wind variation for a typical site using Weibull distribution and Rayleigh distribution was found to be suitable to represent the actual probability of wind speed data for the site studied [15]. The detailed description of the various types of equipments, instruments, site specifications and other technical needs for the wind assessment project in Saudi Arabia had been presented by Alawaji [16]. Emeis measured 10min average wind speed using mini sodar at different sites in Germany. He also discussed implications for the siting of wind turbines [17]. A comparison work on various forecasting techniques applied to mean hourly wind speed was done by Sfetsos using time series analysis, traditional linear models, feed forward and recurrent neural networks, Adaptive Neurofuzzy Interference Systems (ANFIS) and neural logic network [18]. The mean hourly wind speed data-forecasting model using time series analysis has been presented by Sfetses [19]. Poggi et al. have discussed an autoregressive time series model for forecasting and simulating wind speed in Corsica [20]. Aksoy et al. had presented synthetic data generation techniques, which were used in practice for cares where long wind speed data were required. In this study, a new wind speed data generation scheme based upon wavelet transformation is introduced and compared to the existing wind speed generation methods [21]. Cyclone hit in Gujarat in 1998 still proves beyond doubt