Estimation of Energy Yield From Wind Farms Using Artificial Neural Networks

This paper uses the data from seven wind farms at Muppandal, Tamil Nadu, India, collected for three years from April 2002 to March 2005 for the estimation of energy yield from wind farms. The model is developed with the help of neural network methodology, and it involves three input variables—wind speed, relative humidity, and generation hours—and one output variable, which give the energy output from wind farms. The modeling is done using MATLAB software. The most appropriate neural network configuration after trial and error is found to be 3-5-1 (3 input layer neurons, 5 hidden layer neurons, 1 output layer neuron). The mean square error for the estimated values with respect to the measured data is $7.6 times 10^{-3}$. The results demonstrate that this work is an efficient energy yield estimation tool for wind farms.      

Adequacy evaluation of wind power generation systems

This paper attempts to assess the adequacy of wind power generation systems using the data collected from seven wind farms in Muppandal, Tamilnadu (India) with a total capacity of 37 MW. A Monte Carlo model simulation is incorporated in the algorithm to obtain the hourly power output of wind farms, which also takes into account the unavailability of wind turbines. A typical load demand profile is used to examine the chronological hourly wind power generation for each month. The reliability index of LOLE (loss of load expectation) is used to estimate the reliable contribution of wind farm power generation.     

Contents

In India, grid connected wind power generation has gained a high level of attention and acceptability as compared to other renewable technologies available in the country. Wind energy installation in the country is around 1340 MW as of March 2001 and around 6.75 billion units of electricity have been fed to the state grids so far. India had undertaken one of the world's largest efforts for wind resource assessment, a program that covers 25 states comprising about 900 stations. The study has indicated a gross wind potential of around 45000 MW and the technical potential is currently estimated at 13000 MW. A notable feature of the Indian wind energy program has been the interest evinced by private investors/developers in setting up commercial wind power projects. A capacity of 1250 MW of commercial wind power projects has so far been installed, mainly in Tamil Nadu, Maharashtra, Gujarat, Andhra Pradesh, and Karnataka. The largest installation of wind turbines in the country so far is in the Muppandal and Perungudi area near Kanyakumari in Tamil Nadu with an aggregate installed capacity of about 500 MW. This represents one of the largest concentrations of wind farm capacity at any particular location. State-of-the-art technology is now available in India for manufacturing wind turbines of capacity up to 750 kW. Presently about 12 manufacturers are engaged in the production of wind electric generators. The annual production capacity of the domestic wind turbine industry is around 500 MW at present.     

Analysis of impacts of wind integration in the Tamil Nadu grid

As the share of wind in power systems increases, it is important to assess the impact on the grid. This paper combines analysis of load and generation characteristics, generation adequacy and base and peak load variations to assess the future role of wind generation. A simulation of Tamil Nadu in India, with a high penetration of wind power (27% by installed capacity), shows a capacity credit of 22% of the installed wind capacity. For seasonal wind regimes like India, neither the capacity factor, nor the capacity credit reflects the monthly variation in the wind generation. A new approach based on the annual load duration curve has been proposed for generation expansion planning with higher penetration of wind. The potential savings in base and peak capacity required with increasing wind power have been quantified. A future scenario for Tamil Nadu for 2021 has been illustrated. It was found that 5500 MW of wind power can save 3200 MU of peak energy required or an average peak capacity of 2400 and 1100 MW of base capacity. This analysis would be useful to assess the future impacts of increasing wind capacity in grids.     

Strategic structure matrix: A framework for explaining the impact of superstructure organizations on the diffusion of wind energy infrastructure

Increasing the use of renewables in the global energy mix has become a top priority for policy makers. In this paper, we use a diffusion theory based approach to analyze the impact of government initiatives on the development of wind energy infrastructure focusing on the specific case of wind energy diffusion in India. We propose a new framework—the strategic structure matrix—as a way to characterize the strategic focus and analyze the effectiveness of different initiatives to increase wind power diffusion. We apply the matrix to explain the different pace and paths of wind energy growth observed in five Indian states: Tamil Nadu, Gujarat, Maharashtra, Andhra Pradesh, and Karnataka. Our findings suggest the importance of a comprehensive approach that includes multiple strategies across initiatives, local regulatory measures, and supply-side incentives.     

Estimation of wind power availability in Tamil Nadu

Eleven years' daily wind speed data at 21 locations in the state of Tamil Nadu, India were analysed to assess the available wind power potential using Weibull distribution under two different methods. The mean wind speed varied from 1.0 to 5.0 m/s dividing the state into four regions. Judged by mean and standard deviation of available wind power, six locations have been identified as possible sites for a wind energy system.     

Performance,reliability and failure analysis of wind farm in a developing Country

In this paper, an analysis of the performance, failure and reliability, as well as a spare parts analysis have been conducted for a wind farm, which has 15 wind turbine generators (WTGs), each of 225 kW capacity. This wind farm is located at Muppandal, Tamil Nadu, South India. The average value of performance parameters such as technical availability, real availability and capacity factor for the wind farm were 94%, 82.88% and 24.9% respectively during the years 2000–2004. This paper also deals with Pareto analysis to find out the reduction in problems, when one problem is tackled partly and completely. The Weibull technique was also used for the reliability analysis. The reliability factor in the initial period after one year seems to be good as the wind farm has a lower failure rate of 0.000019. As a supplemental activity, spare parts optimization was also carried out for a few vital components of this wind farm and the results are presented. The failure and its financial implications are also analyzed in this paper.     

Optimizing transmission from distant wind farms

We explore the optimal size of the transmission line from distant wind farms, modeling the tradeoff between transmission cost and benefit from delivered wind power. We also examine the benefit of connecting a second wind farm, requiring additional transmission, in order to increase output smoothness. Since a wind farm has a low capacity factor, the transmission line would not be heavily loaded, on average; depending on the time profile of generation, for wind farms with capacity factor of 29–34%, profit is maximized for a line that is about 3/4 of the nameplate capacity of the wind farm. Although wind generation is inexpensive at a good site, transmitting wind power over 1600 km (about the distance from Wyoming to Los Angeles) doubles the delivered cost of power. As the price for power rises, the optimal capacity of transmission increases. Connecting wind farms lowers delivered cost when the wind farms are close, despite the high correlation of output over time. Imposing a penalty for failing to deliver minimum contracted supply leads to connecting more distant wind farms.     

A review on reliability assessment for wind power

The application of wind energy in electric power systems is growing rapidly due to enhanced public concerns to adverse environmental impacts and escalation in energy costs associated with the use of conventional energy sources. Electric power from wind energy is quite different from that of conventional resources. The fundamental difference is that the wind power is intermittent and uncertain. Therefore, it affects the reliability of power system in a different manner from that of the conventional generators. This paper, from available literatures, presents the model of wind farms and the methods of wind speed parameters assessment. Two main categories of methods for evaluating the wind power reliability contribution, i.e., the analytical method and the Monte Carlo simulation method have been reviewed. This paper also summarizes factors affecting the reliability of wind power system, such as wake effect, correlation of output power for different windturbines, effect of windturbine parameters, penetration and environment. An example has been used to illustrate how these factors affect the reliability of wind power system. Finally, mainstream reliability indices for evaluating reliability are introduced. Among these reliability indices, some are recently developed, such as wind generation interrupted energy benefit (WGIEB), wind generation interruption cost benefit (WGICB), Equivalent Capacity Rate (ECR), load carrying capacity benefit ratio (LCCBR).     

CRITICAL ANALYSIS OF WIND FARMS FOR SUSTAINABLE GENERATION

A critical analysis on wind farms has been carried out to improve the performance and reliability of wind energy system. The effect of its improvement has been studied with the Optimal Renewable Energy Mathematical (OREM) model which is developed for sustainable generation in India. The performance and reliability of the wind turbine generators have been evaluated in a demonstration windfarm (6 MW) in India. The windfarm is situated in Kayathar, a village in the south of Tamil Nadu State. The average technical availability, real availability and capacity factor have been analysed from 1991 to 1995 and they are found to be 92%, 54% and 19% respectively. Fault analysis for grid failures has been done using pareto analysis. The analysis indicates that when grid drop failures are reduced by 50%, the overall reduction in the frequency of faults would be 35.2%, which is significant. The reliability analysis has also been done for the wind turbine generator. The failure rate is high to an extent of 6.7×10⁻⁵ h⁻¹ in the case of a yaw control defect and the factor of reliability is found to be 0.5 at 10 000 h. The OREM model developed reveals that when the reliability factor of wind energy system is improved from 0.5 to 0.9 then the utilisation of wind energy would be increased by 82%.     

The role of energy storage in accessing remote wind resources in the Midwest

Replacing current generation with wind energy would help reduce the emissions associated with fossil fuel electricity generation. However, integrating wind into the electricity grid is not without cost. Wind power output is highly variable and average capacity factors from wind farms are often much lower than conventional generators. Further, the best wind resources with highest capacity factors are often located far away from load centers and accessing them therefore requires transmission investments. Energy storage capacity could be an alternative to some of the required transmission investment, thereby reducing capital costs for accessing remote wind farms. This work focuses on the trade-offs between energy storage and transmission. In a case study of a 200 MW wind farm in North Dakota to deliver power to Illinois, we estimate the size of transmission and energy storage capacity that yields the lowest average cost of generating and delivering electricity ($/MW h) from this farm. We find that transmission costs must be at least $600/MW-km and energy storage must cost at most $100/kW h in order for this application of energy storage to be economical.     

Electricity generation from the first wind farm situated at Ras Ghareb, Egypt

Egypt is one of the Red Sea and Mediterranean countries having windy enough areas, in particular along the coasts. The coastal location Ras Ghareb on the Red Sea has been investigated in order to know the wind power density available for electricity generation. To account for the wind potential variations with height, a new simple estimating procedure was introduced. This study has explicitly demonstrated the presence of high wind power density nearly 900 kW/m² per year at 100 m of altitude for this region. Indeed, the seasonal wind powers available are comparable to and sometimes higher than the power density in many European cities for wind electricity applications like Vindeby (Denmark) and also America.New technical analysis for wind turbine characteristics have been made using three types of commercial wind turbines possessing the same rotor diameter and rated power to choice the best wind machine suitable for Ras Ghareb station. As per the decreasing the cut-in wind speed for the wind turbine used, the availability factor increases for a given generator. That it could produce more energy output throughout the year for the location.The aim of this research, was to predict the electrical energy production with the cost analysis of a wind farm 150 MW total power installed at Ras Ghareb area using 100 wind turbines model (Repower MD 77) with 1.5 MW rated power. Additionally, this paper developed the methodology for estimating the price of each kWh electricity from the wind farms. Results show that this wind park will produce maximum energy of 716 GWh/year. The expected specific cost equal to 1.5 € cent/kWh is still less than and very competitive price with that produced from the wind farms in Great Britain and Germany and at the international markets of wind power. The important result derived from this study encourages several wind parks with hundreds of megawatts can be constructed at Ras Ghareb region.     

An onsite demonstration and validation of LiDAR technology for wind energy resource assessment

The investigation of wind resource at higher heights is very crucial in planning wind power project. Normally, this involves the installation of a high and costly meteorological mast with a cup anemometer and wind vanes. This investigation uses the new ground-based remote-sensing technique Light Detection and Ranging (LiDAR) to investigate the wind resource at higher heights. This paper describes the LiDAR technology principle and examines the potential of LiDAR measurement to estimate the wind resource at higher heights by conducting a measurement campaign at Tamil Nadu, India. The wind statistics were determined using the 10?min average time-series wind data monitored by ZephIR LiDAR. These include the Weibull parameters, daily mean wind speed, wind power density, wind energy density, vertical wind speed profile and capacity factor. The investigation reveals that the vertical wind speed profile measured from the LiDAR system has approximate closer values to the standard meteorological measurement.     

Prioritization of potential locations for harnessing wind energy to produce hydrogen in Afghanistan

Due to the devastating ecological effects and constrained reserves of fossil fuels, renewable energies are now globally accepted as viable alternative sources of energy. Among renewable energy sources, wind energy has become globally popular, primarily because wind farms can be rapidly built and easily maintained at a relatively low cost. Wind-powered hydrogen production is an effective solution for storing the excess energy output of wind farms. The hydrogen produced in this way can be used not only in fuel cells but also in cooling, oil, gas, and petrochemical fields. As a country devastated by war and instability, Afghanistan has major energy generation challenges and a substantially large power supply deficiency. However, there are good wind energy potentials in several parts of this country. There are also several hydrogen-consuming fields in Afghanistan that can benefit from hydrogen production from wind energy. This paper endeavored to distinguish the appropriate areas in Afghanistan for harvesting wind energy for hydrogen production using multi-criteria decision-making techniques. Eleven criteria were utilized to prioritize 20 Afghan provinces with wind energy potential. The Step-wise Weight Assessment Ratio Analysis (SWARA) was utilized to weight the criteria and Evaluation based on Distance from Average Solution (EDAS) were utilized to prioritize the provinces. Then, ARAS, TOPSIS, and VIKOR methods were used to validate the resultants. For criteria weighting with SWARA, “wind speed”, “wind power density” and “area of windy regions” with weights of 0.1423, 0.1356, and 0.1221 were introduced as the most significant criteria for this ranking. In all the rankings, Herat, Farah, and Jowzjan were identified as the top three most suitable provinces for wind power generation. The power output and hydrogen output to be achieved in Herat province using a 900-kW turbine were estimated to 2558.4 MW per year and 41.4 tons per year, respectively.     

Societal acceptance of wind farms: Analysis of four common themes across Australian case studies

Australia's renewable energy target (RET) seeks to provide 20 per cent of Australia's electricity generation from renewable energy sources by 2020. As wind power is relatively advanced, it was anticipated that wind power will contribute a major component of the early target. However, high levels of societal resistance to wind farms, combined with new regulatory policies, indicate the RET may not be dominated by wind power. This research involved an examination of seven case studies around wind farm deployment. Qualitative interviews were the primary data for the case studies and analysed using methods informed by grounded theory. Despite the diversity of stakeholder views, the qualitative analysis identified strong community support for wind farms but four common themes emerged that influence this societal acceptance of wind farms in Australia: trust, distributional justice, procedural justice and place attachment. Without addressing these factors through integration into policy development and engagement approaches, wind energy is unlikely to provide the early and majority of new renewable energy. Similar international experiences are incorporated in the discussion of the Australian wind industry's societal acceptance.     

Growth and future trends of wind energy in India

In India, the wind power generation has gained a high level of attention and acceptability compared to other renewable energy technologies. New technological developments in wind power design have contributed for the significant advances in wind energy penetration and to get optimum power from available wind. The yearly percentage increase in wind energy installation is highest for India and now ranks fourth in the world with an installed capacity of 6018 MW. This paper reviews the development of wind energy in India and five potential Indian states. The future growth pattern and time period to achieve the technical wind potential are predicted and analysed.     

The value of energy storage in optimal non-firm wind capacity connection to power systems

Wind is a variable and uncontrollable source of power with a low capacity factor. Using energy storage facilities with a non-firm connection strategy is the key to maximum integration of distant wind farms into a transmission-constrained power system. In this paper, we explore the application of energy storage in optimal allocation of wind capacity to a power system from distant wind sites. Energy storage decreases transmission connection requirements, smoothes the wind farm output and decreases the wind energy curtailments in a non-firm wind capacity allocation strategy. Specifically, we examine the use of compressed air energy storage (CAES) technology to supplement wind farms and downsize the transmission connection requirements. Benders decomposition approach is applied to decompose this computationally challenging and large-scale mixed-integer linear programming (MILP) into smaller problems. The simulation results show that using energy storage systems can decrease the variation of wind farms output as well as the total cost, including investment and operation costs, and increase the wind energy penetration into the power system.     

Reliably model of microwind power energy output under real conditions in France suburban area

Micro-wind turbine are now specially designed for rural or urban environment and one of the main advantages of such turbine is that it can be propelled by a wind speed as low as 3 m/s. However, due to terrain roughness in urban environments wind flow is reduced compared to open spaces reducing power output and increasing payback time on capital investment. Well mounting turbines in urban areas may provide the perfect opportunity for onsite generation from wind power. In this paper, we investigate the performance of a micro-wind turbine in a complex urban area and show that due to long time period and very subtile onsite measurements the ideal position for the wind turbine can be determined. Well measured data, wind speed, power output at this particular location are approximated by the Weibull function. The considered model is tested and validated at an urban landscape location in Metz City, France, where an anemometry is positioned at adjacent to the turbine and the instrumentation is positioned specific to its surrounding location and, record wind turbine data thanks to real time wireless communications. Technical data including wind speed and output power were analyzed and reported allowing to provide an reliable estimation of the wind energy potential in an urban location.     

Offshore wind energy policy for India—Key factors to be considered

Indian Economy is growing at a healthy pace during the last few years. To sustain this growth, power sector needs to build additional generation capacity. However, continued dependence on fossil fuels to power the growth of electricity generation capacity, is hardly sustainable. Renewable Energy source forms a miniscule portion (25 GW,∼12%) of India's overall power generation today (202 GW). The share of wind energy (17 GW) is 67% of the total renewable energy basket. But the contribution from offshore wind farms is non-existent, as all the wind energy generated in India is only through onshore wind farms. India needs a policy framework to encourage the development of offshore wind farms. Several European countries have effective offshore wind energy policies that have helped them to accelerate the growth of their offshore wind energy sector. This paper does an exhaustive literature survey, to identify 21 building blocks of a successful offshore wind energy policy initiative adopted by select European countries, which have been classified under 5 broad categories—Government support, Fiscal and quota based incentives, Availability of local expertise, Capital for investments and Building an enabling ecosystem, which can be leveraged by India to articulate its own offshore wind energy policy.     

Optimal integration of wind farms to isolated wind-Diesel energy system

Wind farms installed on isolated systems are subject to significant restrictions, affecting their expected energy yield and, hence, the feasibility of investments. As wind power penetrations increase in isolated power systems, it is very important to understand how variations in wind plant outputs affect the operation of the isolated system on a day to day basis and what the associated added costs are. In this paper, a wind-Diesel coordination generation scheduling (WCGS) software is developed for appropriate assessment of the added cost to cover the unpredictable wind generator output variations. The developed WCGS software is also a useful tool for the system planner to predict the energy cost and the fuel saving from the expected new wind-Diesel systems. Several technique constraints are applied to determine the optimal proportion of wind generator capacity that can be integrated into the existing system. A simple benefit cost ratio (BCR) is used in this study to evaluate the investment effectiveness of the installation of wind farms for an isolated hybrid system. Numerical experiments are included to understand the wind generator output variations in system operating cost analysis and to assess the impact and economic benefits of the installation of wind farms.