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Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007 (Revised)
Abstract
This report focuses on key trends in the U.S. wind power market, with an emphasis on the latest year, and presents a wealth of data, some of which has not historically been mined by wind power analysts.
... To meet the growing demand for wind energy, U.S. manufacturers have expanded their capacity to produce and assemble the essential components. Despite this growth, U.S. components continue to represent a relatively small share of total turbine and tower materials, and U.S. manufacturers are struggling to keep pace with rising demand (Wiser & Bolinger 2007). ...
... By early 2007, global wind power capacity exceeded 74 GW, and U.S. wind power capacity totaled 11.6 GW. This domestic wind power has been installed across 35 states and delivers roughly 0.8% of the electricity consumed in the nation (Wiser and Bolinger 2007). ...
... In the early days of grid-connected wind generators, the grid rules required that wind turbines go offline when any grid event was in progress. Now, with penetration of wind energy approaching 10% in some regions of the United States, more than 8% nationally in Germany, and more than 20% of the average generation in Denmark, the rules are being changed (Wiser and Bolinger 2007). Grid rules on both continents are requiring more support and fault-ride-through protection from the wind generation component. ...
A 20% Wind Energy Scenario would support expansion of domestic manufacturing and related employment. Production of several key materials for wind turbines would require substantial but achievable growth. Stakeholders and decision makers need to know whether the effort to achieve a generation mix with 20% wind energy by 2030 might be constrained by raw materials availability, manufacturing capability, or labor availability. This chapter examines the adequacy of these critical resources.
... To meet the growing demand for wind energy, U.S. manufacturers have expanded their capacity to produce and assemble the essential components. Despite this growth, U.S. components continue to represent a relatively small share of total turbine and tower materials, and U.S. manufacturers are struggling to keep pace with rising demand (Wiser & Bolinger 2007). ...
... By early 2007, global wind power capacity exceeded 74 GW, and U.S. wind power capacity totaled 11.6 GW. This domestic wind power has been installed across 35 states and delivers roughly 0.8% of the electricity consumed in the nation (Wiser and Bolinger 2007). ...
... In the early days of grid-connected wind generators, the grid rules required that wind turbines go offline when any grid event was in progress. Now, with penetration of wind energy approaching 10% in some regions of the United States, more than 8% nationally in Germany, and more than 20% of the average generation in Denmark, the rules are being changed (Wiser and Bolinger 2007). Grid rules on both continents are requiring more support and fault-ride-through protection from the wind generation component. ...
... Cost estimates for wind capacity are not very accurate and, at any rate, vary from project to project due to differences in scale, land cost and construction costs. In the United States, Bolinger and Wiser (2007) argue that the cost per kilowatt of wind installed in the U.S. in 2007 varied from $1240 to $2600, with a mean of $1710. The average estimate from Bolinger and Wiser (2007), coming from projects proposed in 2006 (but at the time were still not executed), is that each kilowatt cost $1920. ...
... In the United States, Bolinger and Wiser (2007) argue that the cost per kilowatt of wind installed in the U.S. in 2007 varied from $1240 to $2600, with a mean of $1710. The average estimate from Bolinger and Wiser (2007), coming from projects proposed in 2006 (but at the time were still not executed), is that each kilowatt cost $1920. ...
... Oswald et al. (2006) reported the following capacity factors: United Kingdom 28.4%, Spain 26.6%, Denmark 24.1% and Germany 17.8%. Bolinger and Wiser (2007) reported capacity factors around 30% on average for the United States, although the range is broad-for example, between 18% and 48% for projects built in 2006. And International Energy Association (2012), which surveys wind capacity and generation in 21 countries reports that in 2011 202,976 MW of nominal capacity generated 375,700 GWh-an average capacity factor of 21.1%. ...
... , | ( (9) k : parameter bentuk x : parameter skala Tujuan utama diskritisasi ini adalah mendiskritisasi distribusi tenaga angin yang bersifat kontinyu menjadi lima poin diskrit distribusi tenaga angin, dengan probabilitas pada masingmasing poin. Untuk langkah awal, dapat didefinisikan sebagai berikut: ...
... 5 poin diskrit tersebut dapat dilihat pada tabel 4. 5 poin diskrit tersebut kemudian akan digunakan sebagai 5 skenario pada studi kasus. US Department of Energy[9], biaya operasi dan perawatan dari pembangkit tenaga angin disepakati sebesar 30$/MWh. Berdasarkan Sandia National Laboratory[10], biaya operasi dan perawatan sistem penyimpan energi sebesar 40$/MWh.IV. ...
... In the current scenario, wind power is a dependable and proven technology that can provide electricity at a cost competitive with coal and alternative energy such as nuclear, which has been deployed during the last 18 years since 2005 [122]. Although there seems to be a lack of intensive wind energy appraisal in entire the Himalayan region, an assessment of the western Himalayan region of India showed beneficial potential for large-scale wind energy extraction systems [123]. ...
Greenhouse aquaponics (GA) can serve as a sustainable food production method, potentially improving food and nutrition security in resource-constrained and hostile climatic zones such as Nepal's Himalayan region. Energy concerns, however, are one of the major barriers to GA adoption in this region. There is a lack of comprehensive energy demand analysis for GA operations. Therefore, in this study, an energy model for GA based on a quasi-static energy balancing technique was developed to estimate energy demand for the Himalayan region. The 2 study was conducted in 19 districts with varied GA dimensions, and a linear-model was fitted to predict yearly energy consumption. Thereafter, relations to estimate the capacity of PV systems for supplying the required energy were devised. Eventually, this study proposes potential energy management strategies to reduce dependency on a single energy source, reduce energy loss, and enhance resilience to energy concerns. Findings suggest, heating the GA is a major energy concern, accounting up to 85% of the overall energy requirement. Thermal evaluation reveals that conduction and convection losses are the most significant, contributing up to 29.5% of total energy consumption. Moreover, this study testifies the effectiveness of thermal energy storage devices in achieving significant energy savings. The proposed energy management strategies can serve as a decision-making tool for optimizing the design and operation of GA. Furthermore, this research serves as a blueprint for addressing aquaponics related energy challenges worldwide, especially in areas with similar climatic conditions, such as the Hindu Kush Himalaya (HKH) region.
... More recently, the inclusion of renewable energy generation sources, such as wind and solar, that are greatly associated with uncertainties, increase the complexity and competition in the electricity market, and the importance of adequately managing available resources [1,2]. A second challenge, associated with power systems decision problems, is related to responding to the market needs quickly and adequately in an unpredictable environment [3,4]. The third challenge is to determine an adequate computational environment for analyzing these power systems, considering Distributed Energy Resources (DER) [5][6][7][8][9]. ...
Modern electric power systems consist of large-scale, highly complex interconnected systems projected to match the intense demand growth for electrical energy. This involves the decision of generation, transmission, and distribution of resources at different time horizons. They also face challenges in incorporating new forms of generation, distributed generations, which are located close to consumer centers, and new loads such as electric vehicles. Traditionally, the nonlinear Newton–Raphson optimization method is used to support operational decisions in such systems, known as Optimal Power Flow (OPF). Although OPF is one of the most practically important and well-researched sub-fields of constrained nonlinear optimization and has a rich history of research, it faces the convergence difficulties associated with all problems represented using non-linear power flow constraints. The proposal is to present an approach in a software component in cloud Application Programming Interface (API) format, with alternative modeling of the electrical optimization problem as a non-linear objective function and representing electric network constraints modeled through both current and voltage Kirchhoff linear equations. This representation overcomes the non-linearity of the OPF problem considering Distributed Energy Resources (DER). The robustness, scalability, and availability of the method are tested on the IEEE-34 bus system with several modifications to accommodate the DER testing under conditions and in radial or meshed distribution systems under different load scenarios.
... In 2006, smart meter projects in Sweden, Italy, the Nether-lands, Victoria (Australia), the United Kingdom, Northern Ireland, Ontario (Canada), California (USA) and The Italian utility ENEL introduced smart meters already in 2001 in their "Telegestore project [36]. In 2007, the first 105-m wind tower installed in the US [37]. In 2008, Tesla Motors started less than 2500 EV production [38]. ...
The development of smart energy systems is a crucial enabler of the transition towards a decarbonized renewable energy (RE)-based society with universal energy access as it provides flexibility to integrate variable RE sources. This paper analyzes the development of new RE-based smart energy systems while introducing energy technologies and effective methods for energy systems development, recent progress of energy systems by using RE, practical government measures in pioneer countries for energy systems, development with quantitative data for these countries, and PEST (political, economic, socio-cultural and technological) analysis. Our findings show that the development of smart energy systems requires appropriate policies and that thorough collaboration between all national executive agents like national and local governments and citizens in this regard is crucial. Smart energy system development needs to be tailored to local conditions, and due consideration must be given new technologies and methods for development, correct policies, investment, collaboration national/local and their citizens, societal support , and citizens acceptance.
... In 2006, smart meter projects in Sweden, Italy, the Nether-lands, Victoria (Australia), the United Kingdom, Northern Ireland, Ontario (Canada), California (USA) and The Italian utility ENEL introduced smart meters already in 2001 in their "Telegestore project [36]. In 2007, the first 105-m wind tower installed in the US [37]. In 2008, Tesla Motors started less than 2500 EV production [38]. ...
The development of smart energy systems is a crucial enabler of the transition towards a decarbonized renewable energy (RE)-based society with universal energy access as it provides the flexibility to integrate variable RE sources. This paper analyzes the development of new RE-based smart energy systems while introducing energy technologies and effective methods for energy systems development, recent progress of energy systems by using RE, practical government measures in pioneer countries for energy systems, development with quantitative data for these countries, and PEST (political, economic, socio-cultural and technological) analysis. Our findings are that smart energy systems require appropriate policies and that thorough collaboration between all national executive agents like national and local governments and citizens is crucial. Smart energy system development needs to be tailored to local conditions, and due consideration must be given new technologies and methods for development, correct policies, investment, collaboration national/local and their citizens, societal support, and citizens acceptance.
... The peak load demand of 283 MW was picked as the max load condition to execute NSGA-II in the proposed case study. According to [11], the total operation cost of the wind turbine ( ) was taken as 30 $/MWh and incorporated both the operation and maintenance cost. ...
Herein, we determine the optimal configuration (location and size) of a static Var compensator (SVC) considering the intermittent nature of wind power in the transmission system. A probabilistic load flow (PLF) integrated using a five-point estimation method was used to model the wind power uncertainties by discretizing wind power distribution into five discrete points. Consolidating the PLF using a multi-objective non-dominated sorting genetic algorithm (NSGA-II), the location and size of an SVC can be optimally allocated considering wind power uncertainties. This method aims to minimise system operation cost, power loss reduction, and voltage profile enhancement. To demonstrate the viability of the applied method, we validated it using the IEEE 30 bus system. Simulation outcomes demonstrate the viability of the applied method in minimizing different objective functions under the unpredictable nature of wind power.
... j is the cost of ESS in scenario i($/h);C opw, i is the operation cost of wind power generator including (maintenance and operation cost) which is 30 ($/Mwh) according to [28] and [29]; C ops, i is the operation cost of energy storage system in scenario i which is considered to be 40 ($/Mwh) [30]; a j ($/Mw 2 h),b j ($/Mwh) and c j ($/h) are the fuel cost coefficients of generator j; γ j (kg/h), ϕ j (kg/Mwh) and θ j (kg/Mw 2 h) are the carbon emission coefficients of generator j; N w is the number of wind farms; NESSis the total number of energy storage systems; P i G , j is the power of generator j in scenario i; P i w , j is the power of wind farmj in scenario i; P i ESS , j is the power rating of the ESS j in scenario i and t i is the duration time. Only the peak load is studied. ...
Wind power integration with high penetration in a power system is indispensable. However, wind power integration, especially with high level, raises the power system instability problems due to its natural variability and unpredictability, which increases system uncertainties. Thus, uncertainties and correlations amongst wind farms should be considered in a power system operation and planning. One of the best solutions for facilitating the wind power integration is the installation of an energy storage system (ESS). However, the location and sizing of ESSs should be optimally planned to achieve maximum benefits such as minimising total cost, time shifting, reliability and power quality enhancement, minimising power loss, improving the power factor and providing environmental support. In this paper, a new probabilistic discretising method is derived and developed to discretise the continuous joint power distribution of correlated wind farms. Combining the new probabilistic discretising method with a multi-objective hybrid particle swarm optimisation (MOPSO) and non-dominated sorting genetic algorithm (NSGAII), a new hybrid probabilistic optimisation algorithm is proposed. The proposed hybrid algorithm aims to search for the best location and size of energy storage system (ESSs) and considers the power uncertainties of multi-correlated wind farms. The objective functions to be minimised include a system's total expected cost restricted by investment budget, total expected voltage deviation and total expected carbon emission. IEEE 30-bus and IEEE 57-bus systems are adopted to perform the case studies using the proposed hybrid probabilistic optimisation algorithm. The simulation results demonstrate the effectiveness of the proposed hybrid method in solving the optimal allocation problem of ESSs and considering the uncertainties of wind farms’ output power and the correlation amongst them.
... Com o desenvolvimento de novas tecnologias, o custo da eletricidade a partir da geração de energia eólica caiu mais de 80% durante os últimos 20 anos (WISE; BOLINGER, 2007). E, comparado com os custos de tecnologias convencionais tem se tornado muito atrativa, além de não haver a necessidade de lidar com equipamentos para controle de emissão de poluentes. ...
Electric energy generation is expect to undergo important changes at the XXI century. The cost of wind energy electricity generation has dropped more than 80% lately due to the development of new conversion technologies. Energy generation through WECS (wind energy conversion systems) is expected to supply a considerable amount of electricity. In this context, wind turbines equipped with permanent magnet synchronous generators (PMSG) present relevant advantages over other types of electric generators. However, PMSGs must be connected to full-scale power electronic converters that provide a suitable interface to the power grid. These converters allow a WECS to be operated at its maximum power at each time instant. Furthermore, modern power converters guarantee high power quality, high conversion efficiency levels, reliability and flexibility. This work proposes a novel high performance/power factor PMSG current control technique. The proposed control technique is based on the current self-control applied to three-phase rectifiers and improves it by including a reactive power compensation for the PMSG. A three-phase PWM rectifier is employed to achieve robustness and low conduction losses. The analysis of such a rectifier in a WECS is presented along with the proposal of an appropriate space vector modulation scheme. The analyzed WECS is theoretically modeled and tested through computer simulations and the proposed current control technique is experimentally verified in a 6.5 kVA lab-prototype.
... Commonly, the useful life of a wind turbine is about 25 years, this does not depend on its size. We also report the capital cost, and the maintenance and operating cost for each turbine, these are taken from [32,33]. Based on the Table 1, places with wind speeds below 10 km/h do not have the chance to generate electrical power from wind speeds since these are lower than the minimum cut-in wind speed across all Wind Turbine Generators (WTGs). ...
In this paper, we propose a Four-Dimensional Variational (4D-Var) data assimilation framework for wind energy potential estimation. The framework is defined as follows: we choose a numerical model which can provide forecasts of wind speeds then, an ensemble of model realizations is employed to build control spaces at observation steps via a modified Cholesky decomposition. These control spaces are utilized to estimate initial analysis increments and to avoid the intrinsic use of adjoint models in the 4D-Var context. The initial analysis increments are mapped back onto the model domain from which we obtain an estimate of the initial analysis ensemble. This ensemble is propagated in time to approximate the optimal analysis trajectory. Wind components are post-processed to get wind speeds and to estimate wind energy capacities. A matrix-free analysis step is derived from avoiding the direct inversion of covariance matrices during assimilation cycles. Numerical simulations are employed to illustrate how our proposed framework can be employed in operational scenarios. A catalogue of twelve Wind Turbine Generators (WTGs) is utilized during the experiments. The results reveal that our proposed framework can properly estimate wind energy potential capacities for all wind turbines within reasonable accuracies (in terms of Root-Mean-Square-Error) and even more, these estimations are better than those of traditional 4D-Var ensemble-based methods. Moreover, large variability (variance of standard deviations) of errors are evidenced in forecasts of wind turbines with the largest rate-capacity while homogeneous variability can be seen in wind turbines with the lowest rate-capacity.
... Over the last decade, Texas has emerged as the leading state in the development of U.S. wind energy capacity, expanding at a greater rate than any other state (Wiser and Bollinger 2008). Texas is home to seven of the nation's top ten largest wind farms, and has a total installed capacity of 10,135 MWnearly a quarter of national capacity 22 (AWEA, 2011;Brannstrom et al., 2011) (see Figure 19). ...
... Texas currently accounts for one-third of the nation's installed wind power. Wind farms are ideally situated along wind corridors in rural agricultural areas (Wiser and Bolinger 2008), which puts them in direct conflict with migrating and wintering birds. The High Plains of Texas support over 80% of the midcontinent population of sandhill cranes (Grus canadensis, hereafter cranes) every winter. ...
Wind energy is essential for a shift to carbon-emission free energy, however there has been very little research investigating the disturbance caused by wind farms on the landscape. Texas is a leading state in wind power capacity, and the High Plains of Texas support over 80% of the midcontinent population of sandhill cranes (Grus canadensis) every winter. Historically, cranes used saline lakes for fresh water and predator protection, but recent hydrological changes due to agricultural practices have reduced the availability of the lakes for wintering birds. Playa wetlands currently represent the main source of water and roosting habitat in the High Plains. We examined crane occupancy of playa wetlands in 4 counties of Texas during the fall and winters of 2009-10 and 2010-11. In addition to recording presence/no presence, we recorded multiple variables and used information theory and AICc to develop models which best explained crane occupancy. Using occupancy modeling methods to survey playas in Texas resulted in no combination of variables explaining crane presence or absence in playas, most likely because cranes likely move between playas freely on their winter habitat. As playas are a vital part of their winter ecology, sandhill crane use and movement between them should be further examined to better describe crane use of their winter landscape and better plan and manage for large scale habitat alterations, such as the large increase in the number of wind turbines across the High Plains.
... Source: NREL 2009. Bolinger , 2007. 7 More than 150 U.S. facilities now manufacture wind turbine equipment-many in the Midwest (Figure 2.3) . ...
This paper outlined a recommended pathway toward a dramatic increase in clean energy in the Midwest.
... According to Kenway and Martin [8], changing the blade geometry and structural sizes while maintaining a fixed cost and compatibility with the remainder of turbine system can improve the power output of a wind turbine. Besides, reduced cost of producing wind power can be achieved in different ways, for example, site selection, site layout design, predictive maintenance, and optimal control system design [9]. The installation layout of turbines plays an important role in the design of a wind farm. ...
Installation layout of wind turbines plays a prominent role in the design of every wind farm. Thus, the wind farm layout optimization problem is proposed to maximize the total power output with the minimum cost. In this research, Kahrizak region in Tehran province of Iran is selected as a windy region and its real wind speed data are gleaned. Three different scenarios are also considered, with various number of generations and populations for GA parameters, effective distances, and longitude and latitude distances of turbines from each other. Among these scenarios, the best result is obtained for the one in which the longitudinal distance between turbines is greater than the latitudinal distance. By observing the wind rose of Kahrizak region, it is observed that the dominant wind direction of the region is toward the east and south–east. Therefore, by increasing the longitudinal distance of the turbines from each other, the efficiency can be improved and the turbine layout becomes more realistic. In this case, the efficiency rate and normalized cost of turbines are 89.5% and 37.4, respectively, and also 56 turbines are needed. The amounts of efficiency and power output are very convenient for real wind speed data of a region.
... Though wind energy is said to be most economical and is fully competitive with conventional power generation, it still suffers from the higher cost of operation and maintenance [2]. The key areas of wind energy in which reduction of cost can be achieved include, site selection, layout design, predictive maintenance etc. [3][4][5][6]. On the other hand, maximizing the power output of a wind turbine for a given wind speed between a cut in and cut out wind speeds through effective control strategies can also fetch benefits [7,8]. ...
The wind being a most promising renewable energy, has become a strong contender for fossil fuels. Optimizing the blade pitch angle of a wind turbine is important to obtain the maximum power output, as the other variables are considered to be uncontrollable. In this paper an effort has been made to compare performances of three different optimization algorithms namely Particle swarm optimization (PSO), Artificial bee colony (ABC) and cuckoo search (CS) for optimizing the blade pitch angle and hence optimize the power output of a 1.5 MW capacity, pitch regulated, three-bladed horizontal axis wind turbine operating at a large wind farm in central dry zone of Karnataka. The objective function development is done using Artificial Neural Network. The CS algorithm is found to be faster and more efficient as compared to ABC and PSO for the problem under consideration.
... Hala ere, 2003tik kostuak gora egin du, batez ere altzairua, aluminioa eta kobrea bezalako materialen garestitzeagatik. 3. irudian ikus daitezke azken urteetako joera hauek Estatu Batuetako haize turbinen kasuan [5]. Hala ere, EWEAk (Europako Haize Energia Batzordeak) eginiko txosten batek aditzera eman du etorkizun hurbilean berriro nagusituko dela beheranzko joera [6]. ...
... Thus, administrative signals or regulated rates of return have become, by far, the most important drivers for RE investments (International Energy Agency, 2014). Further, uncertainty relating to regulatory frameworks is an inhibiting factor for private RE investments (Barradale, 2010), evidenced by investment downturns as a consequence of changing regulations in Germany (Agnolucci, 2006), Denmark (Meyer and Koefoed, 2003) and the US (Wiser and Bolinger, 2006). Hitchens et al. (2006) highlight that both regulation and market have become key drivers for private investments. ...
In line with the global trend towards socially responsible products, socially responsible investments have gained increasing relevance worldwide. The effect of individuals’ concerns about the environmental sustainability of their consumption patterns has not only received increased attention from market participants but also from academics. Existing literature which focuses specifically on investments in renewable energies points out that individuals’ attitudes are good predictors or moderators of ecologically friendly investment behavior. This study aims to investigate those factors which influence retail investors’ attitudes towards investments in renewable energies. The results are based on an online-survey of participants in Germany and reveal that individuals’ social norms, their confidence in NGOs, and their evaluation of the relevant regulatory framework significantly influence their attitudes towards investments in renewable energies. Based on a multiple linear regression, it was found that the conceptual model used explains 49% of individuals’ attitudes. The results further reveal that German retail investors can be separated into two groups, namely “Supporters” and “Skeptics”, based on their attitudes towards investments in renewable energies. This study provides important practical implications for the investment community and proposals for future research.
... The time period analyzed is the beginning of 1981 until the end of 2008 a period that spans the emergence of a commercial market for wind power to the most recent data available. The geographic extent of the project was selected as the six countries with the highest installed wind power capacity: Germany, the U.S., Spain, India, China, and Denmark (Wiser and Bolinger, 2008). These six markets account for 75% of cumulative world installed capacity and, with the exception of the past few years, have accounted for close to 90% of the world market for new wind power turbines. ...
... 24 There most detailed information relative to the learning curve for WPG is related to the turbine cost which account for 3=4 of the total. Wiser and Bolinger (2007) found a 2.4% yearly cost reduction for the US over the 1982-2004 period and a slight increase since then. According to English study SDC (2005), the price of wind turbines fell by 3.7% per year over the 1990-2004 period. ...
For two decades now, the capacity factor of wind power measuring the average energy delivered has been assumed in the 30-35% range of the name plate capacity. Yet, the mean realized value for Europe over the last five years is below 21%; accordingly private cost is two-third higher and the reduction of carbon emissions is 40% less than previously expected. We document this discrepancy and offer rationalizations that emphasize the long term variations of wind speeds, the behavior of the wind power industry, political interference and the mode of finance. We conclude with the consequences of the capacity factor miscalculation and some policy recommendations.
... The long-term drive to develop larger turbines stems from a desire to take advantage of wind shear by placing rotors in the higher, more energetic winds at a greater elevation above ground (wind speed increases with height above the ground). This is a major reason that the capacity factor of wind turbines has increased over time, as documented by Wiser and Bolinger [1]. ...
Wind turbines have evolved rapidly over the past 20 years and the turbines have grown in size from 100 kW in the early 1980s to over 2.5 MW today. The evolution of wind technology is expected to continue over the next decades resulting in a continued improvement in reliability and energy capture with a modest decrease in cost. The improvements in blade design and materials, innovative rotors, drive systems, towers, and controls are expected to enable this continued improvement in the cost effectiveness of wind technology.
... In contrast to turbine costs, operational and maintenance costs appear to be declining as new turbine technologies gradually reduce or eliminate previously experienced problems. O&M costs are generally considered to rate at less than US$ 0.01 per kWh for turbines manufactured after 2006 (Wiser & Bolinger 2007). In the case of an MPR installation, they would consist of land rent (to Government of Belize), insurance, servicing, repairs, parts and administration. ...
... The need of modernising the power grid infrastructure around world is both a consequence of the limited investment made in recent decades, and the result of new needs arising in the safe integration of public services renewable scale feeding transmission system, DERs feeding into the distribution system or the home. In fact, The legacy of power generation and transmission concept are converts to massive distributed energy incorporating a large number of variables and small renewable energy resources (DER), as the wind production (Wiser and Bolinger, 2008) -solar (Albany, 2005) facilities with all their stimulating effects the smart grid. MetaPV (Van Loon et al., 2010) is a project that has demonstrated the benefits of supply electric photovoltaic (PV) on a large scale, pointing the way to the city powered by renewable energy sources. ...
Communications infrastructure is a basic part for the success of smart grid. Optimisation of energy consumption in the future intelligent energy networks (smart grids) will be based on the integrated near real-time between the different elements of grid network communications. Through a communication infrastructure, a smart grid can improve the reliability of power, eliminate power outages, and optimise energy consumption. The network gets smarter by improving detection, so the most important element that makes the smart grid is wireless sensor networks. Among them, one of the most important applications is a sensor data collection. This paper discusses some of communications research challenges and opportunities in the areas of smart grid and smart meters. In particular, we focus on some of the main communications challenges to achieve interoperability and future proof, smart grid/metering networks. We describe the basic taxonomy and propose to break the network data collection of wireless sensors.
... Maine's Climate Future fossil fuel-based sources (Wiser and Bolinger 2007). Energy costs average $0.03-$0.06/ ...
Earth’s atmosphere is experiencing unprecedented changes that are modifying global climate. Discussions continue around the world, the nation, and in Maine on how to reduce and eventually eliminate emissions of carbon dioxide (CO2), other greenhouse gases, and other pollutants to the atmosphere, land, and oceans. These efforts are vitally important and urgent. However, even if a coordinated response succeeds in eliminating excess greenhouse gas emissions by the end of the century, something that appears highly unlikely today, climate change will continue, because the elevated levels of CO2 can persist in the atmosphere for thousands of years to come.
In late 2007, Governor Baldacci asked the University of Maine and its ClimateChange Institute to lead a wide-ranging analysis of the state’s future in the context of changing climate during the 21st century. The assignment involved making use of existing knowledge and understanding of climate change; the terrestrial, freshwater, and marine ecosystems that characterize our environment; and the socioeconomic characteristics of the state. The project involved no financial support for new research or data collection, but participating scientists contributed their time and expertise to initiate a process that could lead to systematic planning and thoughtful decisions for the future. Based on considerable prior research, this report serves as a preliminary step designed to frame future detailed analyses focused on Maine by teams that will likely continue for years.
... ͉ L i t e r a t u r e R e v i e w Growing acceptance and public sentiment toward renewable energy indicate that development of wind farms in the United States is likely to continue. Annual wind capacity in the U.S. grew by 46% in 2007, adding 5,329 MW of generation capacity and $9 billion of investment (Wiser and Bolinger, 2008). Two distinct approaches to determining the market and social consequences of new wind projects have developed: post-development hedonic pricing models of real estate values and consumer sentiment surveys. ...
This study examines the announcement affect of a proposed wind farm
development on an 11,000-acre ranch in Northern Colorado on
surrounding rural housing prices. This study analyzes 2,910 single-
family home transactions in two rural census tracts adjacent to the
proposed wind farm prior to, and after the wind farm announcement.
The results account for the timing of the announcement in March 2007,
which coincided with the beginning of national and regional housing
price declines, and still shows insignificant and minimal impacts to
surrounding home values and sales, adjusted for the economic recession,
after the announcement.
... For example, during the time period of our data collection , and even today, the wind energy sector faced significant uncertainty due to technical, economic, and political circumstances (Vasi, 2011). Renewable energy's abil- ity to economically compete with fossil fuel-based sources remained questionable as illustrated by the sector's dependence on the U.S. federal production tax credit during this time period (Wiser and Bolinger, 2008). Indeed, as illustrated in Table I of our orig- inal sample, only 14 of 25 firms are still operating as of 2015. ...
On the basis of a qualitative study of 25 renewable energy firms, we theorize why and how individuals engage in environmental entrepreneurship, inductively defined as: the use of both commercial and ecological logics to address environmental degradation through the creation of financially profitable organizations, products, services, and markets. Our findings suggest that environmental entrepreneurs: (1) are motivated by identities based in both commercial and ecological logics,(2) prioritize commercial and/or ecological venture goals dependent on the strength and priority of coupling between these two identity types, and (3) approach stakeholders in a broadly inclusive, exclusive, or co-created manner based on identity coupling and goals. These findings contribute to literature streams on hybrid organizing, entrepreneurial identity, and entrepreneurship’s potential for resolving environmental degradation.
Exploring environmental entrepreneurship: Identity coupling, venture goals, and stakeholder incentives (PDF Download Available). Available from: https://www.researchgate.net/publication/295088464_Exploring_environmental_entrepreneurship_Identity_coupling_venture_goals_and_stakeholder_incentives [accessed May 4, 2016].
... Some projections indicate that the global energy demand will almost triple by 2020 [1]. An inadequate wind farm layout design would may not lead to the expected wind power capture, and increased maintenance costs [2,3]. The design of a layout of standalone wind farm and a study of optimal sizing of interconnected wind farm has been addressed in many literatures. ...
Optimal sizing of wind turbines on a given area interconnected with electric utility, EU involve several complex optimization problems. Multi-objective functions based on PSO technique for optimal sizing are presented. Firstly, the objective function, to find the optimal number of wind turbines to produce desired annual energy. Secondly, finding the optimal number of EU’s feeders to minimize the cost of kilowatt hour generated. A capacity outage probability table is implemented to find the loss of load expectation. Moreover, the involved Wake Loss Model is based on Jensen model, and the Economic Model is based on the annual cost of the system concept. Furthermore, the inherent numerical example which is related to the industrial case is presented.
... U.S. Department of Energy (DOE) [69] gives a similar estimate of $0.004-0.006/kWh in 2004 for new wind turbine projects in the Class 4 resource areas (at a Class 4 site, the wind speed is between 5.6 and 6.0 m/s at 10 m height [70]). But, according to a later report by DOE [71] in 2006, the actual O&M costs range from $0.008 to $0.018/kWh, depending on the wind farm size. Most recently, Asmus [72]'s study presents even higher O&M costs. ...
The global wind power industry involves operations in highly stochastic environments and thus faces challenges in enhancing reliability and reducing maintenance costs. Earlier studies related to wind energy facility reliability and maintenance focused more on qualitative aspects, discussing the unique influencing factors in wind power operations and their effects on system performance. With operational experience accumulated for more than a decade, the most recent focus has shifted to a more structured approach using analytical and/or simulation methods. In this chapter, we provide a comprehensive account of the existing research regarding wind energy facility reliability and maintenance. We group the relevant studies into three major categories. The first category addresses the degradation and failure pattern of wind turbines, aiming at optimizing the operations and maintenance. The second and third categories discuss the reliability issues in a broader sense, focusing on reliability assessment at the wind farm level and at the overall power system level, respectively.
... The O&M cost of sole SUT in UHI in the first operation year is therefore estimated to be 1.12 M yuan. The cost just accounts for about 33% of the average O&M cost estimated to be 3.36 M yuan (0.48 M€), according to the conservative average O&M cost of approximately 10.7 €/MW h over the lifetimes of Chinese wind projects [47], which is comparable to the maximum costs observed in recent years for US wind farms well into their operational lifetimes [48]. This is because that compared to wind farm, the air current inside the SUT is steady and successive, and therefore the SUT turbine blades are not readier to be fatigue and the SUT turbines are not readier to be out of order. ...
Due to rapid urbanization, dense haze is formed in some Chinese cities where urban heat island (UHI) effect is aggravated. The urban haze problem has become a touchy issue significantly affecting humans living and working in the cities. Solar updraft tower (SUT) is a device that can drive warm air up to high altitude under the effect of natural buoyancy. In this paper, high SUTs are proposed to be used to drive the UHI warm air containing haze up to higher altitude and help the haze disperse to farther distance, thus lowering the concentration of haze effectively. This proposal can effectively alleviate the urban haze problem and simultaneously produce clean electric power in Chinese cities. The performance analyses and cost analyses of sole SUT for power generation in a UHI are conducted. The number of 1 and 1.5 km high SUTs only for impelling air up in UHIs of several main Chinese cities are estimated, respectively.
In this paper we develop an integrated model to identify optimal subsidy schedules for clean energy technologies that maximize social benefits less subsidy costs. The model uses historical cost, adoption, and emissions data and accounts for both environmental and technological progress benefits of the subsidy. An alternative analytical model is also presented to analyze key technological features affecting subsidy design. We focus on three important factors in determining the social benefits of subsidizing the use of clean energy technology: the price (or cost) sensitivity of adoption, induced cost reductions through learning, and environmental benefits. We quantify how distinct profiles of these three factors result in qualitatively different optimal subsidy plans for utility wind and residential solar power in 13 electricity grid regions in the US. Results show that optimal subsidy schedules for utility wind depend on the region, starting at $20–60/MWh, and are roughly constant over time. In contrast, optimal residential solar subsidies either decline over time (starting from $8–70/MWh) or are not desirable (subsidy of zero). The results imply that the optimal subsidy for utility wind is justified mainly through the direct environmental benefits, unlike residential solar PV in which the subsidy is primarily justified by indirect technological progress benefits.
While extant research on sustainability transitions discusses how innovations are nurtured in protective market spaces before causing change in established industries, we know less about how characteristics of these protective market spaces, policy, and resource endowments impact incumbents’ sustainability transition pathways for a new technology. We distinguish between incumbents’ choice to embrace innovation by contracting for wind power or direct ownership of windfarms. We contribute to recent calls in the literature to open the “black box” surrounding the heterogeneity in incumbents’ responses to sustainability transitions. In a sample of 801 windfarm transactions over a 14-year-time period (2004–2017), we find that characteristics of protective market spaces affect incumbents’ response: incumbents facing less experienced niche actors (windfarm developers) and acquiring greater capacities of the innovation (wind power) are more likely to own a windfarm than contract for wind power. Moreover, if the innovation has greater physical distance from incumbents’ operations, ownership is the incumbent's likely response to innovation. As policies for the innovation persists, incumbents are more likely to own a windfarm than contract for wind power. However, that relationship is weakened for firms more established in existing technologies. We contribute to the literature by demonstrating that market characteristics and policy impact heterogeneity in incumbents’ sustainability transitions.
This paper presents a preventive maintenance policy for wind turbines considering three effects of wind speed: accelerating hazard rate, restricting maintenance implementation, and affecting downtime cost. The effect on the hazard rate is described by a proportional hazards model. The restriction on maintenance actions results in the elongation of maintenance duration. The downtime cost is evaluated based on the power output curve model. Three failure types (i.e., catastrophic failure, critical failure, and minor failure) and multiple maintenance actions (i.e., preventive and corrective replacements, preventive and corrective general repairs, and minimal repair) are integrated into the policy. The objective is to determine the optimal maintenance policy that minimizes the long‐run average cost rate. The optimization problem is formulated and solved in the semi‐Markov decision process (SMDP) framework. A practical example is provided to illustrate the proposed method. The comparison with other policies shows the superiority of the proposed policy as well as the significance of the three effects of wind speed in maintenance decision‐making.
Outsourcing maintenance is an economical way for wind farm owners to address sophisticated and expensive maintenance operations of wind turbines. This paper proposes three options for the post-warranty maintenance contract of wind turbines from the perspective of service providers. Option 1 involves corrective maintenance only. In option 2, the first preventive maintenance is performed at a certain time point and after that periodic maintenance is carried out. Option 3 initiates with a preventive replacement and performs periodic maintenance subsequently. An availability target is set over the contract period and failing to satisfy the target incurs a penalty from the service provider. The objective is to determine the optimal preventive maintenance programs of option 2 and option 3 that minimize the contract servicing cost. Numerical examples are provided to illustrate the proposed policies. The results show that option 2 and option 3 are more effective than option 1 and their effectiveness grows when warranty and contract coverages increase.
Dynamic measurements are undertaken on a utility scale wind turbine (900 kW rated power, 55 m hub height, and a 53.6 m rotor diameter) located at Oak Creek Energy Systems near Mojave, California, USA. The acceleration response to wind and other ambient sources is recorded by as many as 81 channels at locations along the height of the tower, on the foundation, and on the surface of the surrounding soil. This extensive dataset is accessible for further studies at https://www.designsafe-ci.org/data/browser/public/nees.public//NEES-2008-0661.groups. In this paper, modal parameters (natural frequencies, damping ratios, and mode shapes) are estimated with the Multiple-Reference Natural Excitation technique combined with the Eigensystem Realization Algorithm based on 19 h of data while the turbine is parked and 1.5 h when it is operating under normal conditions. Structural characteristics are identified from the parked and operational state recordings. These dynamic test series provides a unique opportunity to observe variability in modal parameters of the turbine and is the first to be published for a megawatt scale turbine. The experimentally observed properties are compared to results from a beam-column model, the most common approach for simulating global turbine dynamics. Agreement between the experimentally identified and numerically predicted modal parameters confirms that this modeling approach is representative of modern wind turbine dynamics and provides a basis for seismic response evaluations.
Monitoring a large number of units whose health conditions follow complex dynamic evolution is a challenging problem in many healthcare and engineering applications. For instance, a unit may represent a patient in healthcare application or a machine in manufacturing process. Challenges mainly arise from 1) insufficient data collections that result in limited measurements for each unit to build an accurate personalized model in the prognostic modeling stage, and 2) limited capacity to further collect surveillance measurement of the units in the monitoring stage. In this study, we develop a selective sensing method that integrates prognostic models, collaborative learning, and sensing resource allocation to efficiently and economically monitor a large number of units by exploiting the similarity between them. We showcase the effectiveness of the proposed method using two real-world applications; one on depression monitoring and another with cognitive degradation monitoring for Alzheimer's disease. Comparing with existing benchmark methods such as ranking and selection method, our fully integrated prognosis-driven selective sensing method enables more accurate and faster identification of high-risk individuals.
Vertical Axis Wind Turbines (VAWTs) with fixed pitch blades have a limited power capture performance envelope as the Tip Speed Ratio (TSR) changes. Circulation Control (CC) has been proposed and simulated to possibly increase power capture of a VAWT using constant CC jet momentum, but a practical method of minimizing CC usage has yet to be explored. In addition, VAWTs are typically limited in power capture performance either by a maximum peak at a small set of TSR or wide operating TSR at fractions of the peak performance based on the design solidity. Both the reduced jet usage and solidity limitation were addressed by developing a method of dynamically using CC to perform a virtual solidity change. The developed method described within this work used CC to change blade aerodynamics to specifically match a maximum performing static solidity or wake shape at a given TSR. Simulation results using an existing aerodynamics model indicated a significant reduction in the re-quired CC jet momentum compared to a constant CC system along with control over power capture for a CC-VAWT.
This paper proposes an integrated product-service model to ensure the system availability by concurrently allocating reliability, redundancy, and spare parts for a variable fleet. In literature reliability and inventory allocation models are often developed based on a static installed base. The decision becomes really challenging during the new product introduction as the demand for spare parts is nonstationary due to the fleet expansion. Under the system availability criteria, our objective is to minimize the fleet costs associated with design, manufacturing, and after-sales support. We tackle this reliability-inventory allocation problem in two steps. First, to accommodate the fleet growth effects, the nonstationary spare parts demand stream is modeled as a sum of randomly delayed renewal processes. When component failure time is exponential, the mean and variance of the lead-time inventory demand are explicitly derived. Second, we propose an adaptive base stock policy against the time-varying parts demand rate. A bisection search combined with meta-heuristics is used to find the optimal solution. Numerical examples show that spare parts inventory results in a lower fleet cost under short-term performance-based contracts while reliability-redundancy is preferred for long-term service programs.
A growing number of manufacturing firms are striving to achieve eco-friendly operations through onsite wind or solar generation. This paper proposes a zero-carbon power supply model to guide the integration of onsite renewable energy into manufacturing facilities. We intend to address two fundamental questions: (1) Is it cost-effective to deploy onsite wind turbines and solar photovoltaics (PVs) systems to achieve net-zero carbon environmental performance? (2) Is the renewable generation system able to meet the electricity demand despite the power intermittency? To answer these questions, we formulate a stochastic optimization model to minimize the levelized cost of onsite renewable energy. The goal is achieved by optimizing the sizing of wind and solar generating units. The proposed energy solution is tested in ten cities around the world under diverse climatic conditions. While PV is still expensive, we conclude that manufacturers could realize zero-carbon emissions at affordable cost provided the local wind speed is above 5 m/s.
The kinetic energy of wind is harvested using wind turbines to generate electricity. Among various renewable energy sources, wind energy is the second most technologically advanced renewable energy source; hydropower is the first. Although there is a significant potential for converting wind energy to electricity, a number of issues must be addressed before it can be used to its full potential. Wind blows in every corner of the earth; however, it does not blow constantly. In addition, it must maintain a certain speed to be effective for running a wind turbine and generating electricity. In this chapter, various aspects of wind energy including types of wind turbines, onshore and offshore wind farms, the cost of wind energy, and steps necessary for installing a wind turbine are discussed.
Wind energy is a rapidly growing field of renewable energy, and as such, intensive scientific and societal interest has been already attracted. Research on wind turbine structures has been mostly focused on the structural analysis, design and/or assessment of wind turbines mainly against normal (environmental) exposures while, so far, only marginal attention has been spent on considering extreme natural hazards that threat the reliability of the lifetime-oriented wind turbine's performance. Especially, recent installations of numerous wind turbines in earthquake prone areas worldwide (e.g., China, USA, India, Southern Europe and East Asia) highlight the necessity for thorough consideration of the seismic implications on these energy harnessing systems. Along these lines, this state-of-the-art paper presents a comparative survey of the published research relevant to the seismic analysis, design and assessment of wind turbines. Based on numerical simulation, either deterministic or probabilistic approaches are reviewed, because they have been adopted to investigate the sensitivity of wind turbines' structural capacity and reliability in earthquake-induced loading. The relevance of seismic hazard for wind turbines is further enlightened by available experimental studies, being also comprehensively reported through this paper. The main contribution of the study presented herein is to identify the key factors for wind turbines' seismic performance, while important milestones for ongoing and future advancement are emphasized. Copyright
This chapter examines availability, markets, and the technical potential of renewable energy (RE) resources in meeting energy demand in a redefined energy economy. These new energy challenges include energy security, environmental integrity, climate change, and economic prosperity. It looks at how far renewables have come during the past decades and their potential to provide a larger portion of energy needs in the future. It also examines the current status of renewables capacity as well as technology investment; it includes trends by country and by technology as well as the impact of the global economic situation. Market and technology trends for resources such as hydropower, wind, solar, geothermal, and bioenergy; it also provides market projections are also outlined.
Data centers operating cost are dominated by their power consumption. Renewable energy sources can reduce the operating costs when correctly selected. Nevertheless, this is a non trivial task because it should consider different energy sources (wind, solar), storage alternatives (batteries, grid-tie), workload, historical weather patterns, incentives, and service agreement penalties. These are the basic factors, but the model should be extensive to consider other factors like power gating support.
This paper introduces ReRack, an extensible simulation infrastructure that can be used to evaluate the energy cost of a data center using renewable energy sources. ReRack is composed of two main components, a simulation and an optimization component. The simulation component explores the cost effectiveness of renewable energy generation. It requires a model that can simulate both the data center power usage and the location-dependent variability of the power generation source (solar and wind). The ReRack optimization component finds the best ratio of renewable energy sources for a given location and workload.
Green energy (GE) refers to energy sources that have no undesired consequences such as carbon emissions from fossil fuels or hazardous waste from nuclear energy. Alternative energy sources are renewable and are thought to be "free" energy sources. These include biomass energy, wind energy, solar energy, geothermal energy, and hydroelectric energy sources. GE supply is viewed as an option for satisfying the increased energy demand with the prospect of carbon accountability. However, geographical areas have diverse GE resources and different levels of energy consumptions. Territory design is defined as the problem of grouping geographic areas into larger geographic clusters called territories in such a way that the grouping is acceptable according to the planning criteria. The aim of this study is to group geographic areas in such a way that energy requirement in a geographic cluster matches the available GE potential in the same cluster. In this way, investments may be supported through region specific policies.
This chapter compares wind-power development in Germany and the United States by focusing on the share of each country's total electricity generation or consumption that is produced from wind. More specifically, it examines the differences between the two countries in the extent to which they have developed wind power successfully based on two contrasting theoretical perspectives, one dealing with socioeconomic structures and political institutions, and the other on the interaction between problem and political streams. It also discusses three phases in wind-power development in the two countries: US leadership (1978–1993); Germany's rise into a growing leadership role (1993–2004); and the beginning of catch-up by the United States (2004–present). Finally, it explains how certain combinations of structures and processes drove the turning points between these phases, along with the implications for theories of environmental outcomes and for multiple-streams theory.
This chapter addresses the question how policy frameworks can be designed to improve the flow of private capital into renewable energy technologies and energy efficiency. It argues that significant growth in clean energy investment over past decades has been fostered by favorable policy frameworks. Yet, policy also posed risks for renewable energy investors. The chapter argues that because risk and return are important drivers of investment decisions, policy-makers need to reduce risk and provide adequate returns for renewable energy. Creating a level playing field, and helping the market to value positive externalities of renewables, is also important. At the same time, perceptions matter, and policy needs to take cognitive factors into account, i.e., risk perceptions and return expectations among market actors. The chapter concludes that investor preferences should however not replace strategic choices made by policy-makers themselves.
Recently, harmonization of renewable energy policies has drawn growing attention as an important issue. To find the most effective combination, this paper identifies simultaneous interactions in an endogenous technological-change system and analyzes empirically the static and dynamic impacts of renewable energy policies in solar PV and wind power. The empirical results indicate that policy outcomes create a virtuous cycle in the technological change system through market oppurntunity, learning-by-searching, and learning-by-doing. According to the results, the static impact of technology-push and tariff incentive policies are effective on invention, while renwables obligation and CO2 tax appear to encourage cost reduction in the technologies. When the dynamic impacts of policy are considered, tariff incentives appears to outperform a renewables obligation policy with very small margin.We also found that the dynamic impact of CO2 tax varies with the level of technological development maturity.
Biofuels are by now a well-established component of the liquid fuels market and will continue to grow in importance for both economic and environmental reasons. To date, all commercial approaches to biofuels involve photosynthetic capture of solar radiation and conversion to reduced carbon; however, the low efficiency inherent to photosynthetic systems presents significant challenges to scaling. In 2009, the US Department of Energy (DOE) Advanced Research Projects Agency-Energy (ARPA-E) created the Electrofuels program to explore the potential of nonphotosynthetic autotrophic organisms for the conversion of durable forms of energy to energy-dense, infrastructure-compatible liquid fuels. The Electrofuels approach expands the boundaries of traditional biofuels and could offer dramatically higher conversion efficiencies while providing significant reductions in requirements for both arable land and water relative to photosynthetic approaches. The projects funded under the Electrofuels program tap the enormous and largely unexplored diversity of the natural world, and may offer routes to advanced biofuels that are significantly more efficient, scalable and feedstock-flexible than routes based on photosynthesis. Here, we describe the rationale for the creation of the Electrofuels program, and outline the challenges and opportunities afforded by chemolithoautotrophic approaches to liquid fuels.
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