Forecast study of the supply curve of solar and wind technologies in Argentina,Brazil, Chile and Mexico

This paper forecasts the supply curve of non-conventional renewable technologies such as wind and solar generating stations in Argentina, Brazil, Chile and Mexico using technological and economic parameters. It also estimates the additional investment costs in solar and wind generation for reaching the renewable energy target in each of these countries. To assess the power supply profile from 1 axis tracking PV and horizontal axis wind turbine (three blade) stations, two different scenarios are developed for 2014 and 2025. Scenario 1 estimates the PV and wind annual electricity yield by using polycrystalline silicon (cSi poly) as semiconductor material for PV cells and a Vestas 90–3.0 MW turbine for the wind for 2014.Scenario 2 assumes a more efficient technology, such as CPV. In fact, the model employs 45% efficiency triple junction cells using ∼3500 m2 for each 1 MW installed capacity in 2025. Moreover, this scenario also assumes a more powerful type of turbine, i.e. Vestas 112–3.075 MW. The biggest potential for wind power is found to be in Argentina, followed by Brazil, Mexico and Chile. In addition, a 550 MW installed capacity CPV power station, using triple junction cells could generate up to 4 TWh in Chile in 2025.     

Airborne wind energy: Optimal locations and variability

This paper explores the global wind power potential of Airborne Wind Energy (AWE), a relatively new branch of renewable energy that utilizes airborne tethered devices to generate electricity from the wind. Unlike wind turbines mounted on towers, AWE systems can be automatically raised and lowered to the height of maximum wind speeds, thereby providing a more temporally consistent power production. Most locations on Earth have significant power production potential above the height of conventional turbines. The ideal candidates for AWE farms, however, are where temporally consistent and high wind speeds are found at the lowest possible altitudes, to minimize the drag induced by the tether. A criterion is introduced to identify and characterize regions with wind speeds in excess of 10 m s⁻¹ occurring at least 15% of the time in each month for heights below 3000 m AGL. These features exhibit a jet-like profile with remarkable temporal constancy in many locations and are termed here “wind speed maxima” to distinguish them from diurnally varying low-level jets. Their properties are investigated using global, 40 km-resolution, hourly reanalyses from the National Center for Atmospheric Research's Climate Four Dimensional Data Assimilation, performed over the 1985–2005 period. These wind speed maxima are more ubiquitous than previously thought and can have extraordinarily high wind power densities (up to 15,000 W m⁻²). Three notable examples are the U.S. Great Plains, the oceanic regions near the descending branches of the Hadley cells, and the Somali jet offshore of the horn of Africa. If an intermediate number of AWE systems per unit of land area could be deployed at all locations exhibiting wind speed maxima, without accounting for possible climatic feedbacks or landuse conflicts, then several terawatts of electric power (1 TW = 10¹² W) could be generated, more than enough to provide electricity to all of humanity.     

Wind shear coefficients and energy yield for Dhahran, Saudi Arabia

This study presents calculated values of wind shear coefficients (WSE) using measured values of wind speed at 20, 30, and 40 m above ground level (AGL), for Dhahran, Saudi Arabia. The study also includes the air density estimated using measured air temperature and surface pressure and effect of wind shear coefficient on energy yield from a wind farm of 60 MW installed capacity developed using 40 wind turbines of 1500 kW size. The data used in the determination of wind shear coefficient covered a period of almost 5 years between 4 October 1995 and 30 November 2000.The study suggests a value of 0.189 of wind shear coefficient for the calculation of wind speed at different heights if measured values are known at one height. No regular seasonal trend was observed in the values of wind shear coefficients. In case of diurnal variation, higher values were observed during nighttime and early hours of the day and comparatively smaller values during day light hours. The air density, calculated using measured temperature and pressure was found to be 1.18 kg/m³. The energy yield obtained using RetScreen software, showed that the actual wind shear coefficient presented in this paper produced around 11–12% more energy compared to that obtained using 1/7 power law. Accordingly, 2–3% higher plant capacity factors were achieved using actual site-dependent wind shear coefficient instead of 1/7th wind power law exponent for the calculation of wind speed at hub-height.     

Feasibility study of harnessing wind energy for turbine installation in province of Yazd in Iran

This paper analyses the wind speed of some major cities in province of Yazd which is located in central part of Iran. Also, the feasibility study of implementing wind turbines to take advantage of wind power is reviewed and then the subject of wind speed and wind potential at different stations is considered. This paper utilized wind speed data over a period of almost 13 years between 1992 and 2005 from 11 stations, to assess the wind power potential at these sites. In this paper, the hourly measured wind speed data at 10 m, 20 m and 40 m height for Yazd province have been statically analyzed to determine the potential of wind power generation. Extrapolation of the 10 m data, using the Power Law, has been used to determine the wind data at heights of 20 m and 40 m. The results showed that most of the stations have annual average wind speed of less than 4.5 m/s which is considered as unacceptable for installation of the wind turbines. City of Herat has higher wind energy potential with annual wind speed average of 5.05 m/s and 6.86 m/s, respectively, at height of 10 m and 40 m above ground level (AGL). This site is a good candidate for remote area wind energy applications. But some more information is required, because the collected data for Herat is only for 2004. Cities of Aghda with 3.96 m/s, Gariz with 3.95 m/s, and Maybod with 3.83 m/s annual wind speed average at height of 10 m above ground level are also able to harness wind by installing small wind turbines. The Tabas and Bafgh sites wind speed data indicated that the two sites have lower annual wind speed averages between 1.56 m/s and 2.22 m/s at 10 m height. The monthly and annual wind speeds at different heights have been studied to ensure optimum selection of wind turbine installation for different stations in Yazd.     

Potential wind power generation in the State of Kuwait

The wind characteristics of six locations in the State of Kuwait have been assessed. The annual average wind speed for the considered sites ranged from 3.7 to 5.5 m/s and a mean wind power density from 80 to 167 W/m² at standard height of 10 m. The Weibull parameters and power density of each station have been determined using Weibull distribution. The wind data at heights 15, 20, 25 and 30 m were obtained by extrapolation of the 10 m data using the Power-Law. The potential wind energy at different heights was estimated using Weibull parameters. Maximum power density is found at 30 m height which varies between 130 and 275 W/m² with 70% increase from the standard height indicating fairly potential wind energy especially in the northern part of the country. The highest potential wind power was found during the summer season which is the peak demand season of electricity in Kuwait.     

Wind energy potential estimation and micrositting on Izmir Institute of Technology Campus, Turkey

The aim of this study was to predict the wind energy content over the campus area of Izmir Institute of Technology. The wind data were collected at 10 and 30 m mast heights for a period of 16 months. Mean wind speeds were 7.03 and 8.14 m/s at 10 and 30 m mast heights, respectively. The ‘WAsP’ and ‘WindPRO’ softwares were used for the wind statistics and energy calculations. Suitable sites were selected according to the created wind power and energy maps. Wind turbines with nominal powers between 600 and 1500 kW were established for annual energy production calculations and best fitted ones were used for the micrositting.     

Wind power analysis and site matching of wind turbine generators in Kingdom of Bahrain

In this paper, the hourly measured wind speed data for years 2003–2005 at 10 m, 30 m and 60 m height for Kingdom of Bahrain have been statically analyzed to determine the potential of wind power generation. Extrapolation of the 10 m data, using the Power Law, has been used to determine the wind data at heights of 30 m and 60 m. Weibull distribution parameters have been estimated and compared annually and on monthly bases using two methods; the graphical method and the another method, designated in this paper as approximated method, which depends on the standard deviation and average wind speed. The maximum power density for 10 m, 30 m and 60 m heights were found to be 164.33 W/m², 624.17 W/m² and 1171.18 W/m² in February, respectively while the minimum power density were 65.33 W/m², 244.33 W/m² and 454.53 W/m² in October, respectively. The average annual wind power density was found to be 114.54 W/m² for 10 m height, 433.29 W/m² for 30 m height and 816.70 W/m² for 60 m height. Weibull probability function, using Weibull parameters estimated from the approximated method, has shown to provide more accurate prediction of average wind speed and average power density than the graphical method. In addition, the site matching of wind turbine generators at 30 m and 60 m heights has been investigated by estimating the capacity factors of various commercially available wind turbines generators. The monthly and annual variation of capacity factors have been studied to ensure optimum selection of wind turbine generators.     

Empowering the electric grid: Can SMES coupled to wind turbines improve grid stability?

The transition to a low carbon energy portfolio necessitates a reduction in the demand of fossil-fuel and an increase in renewable energy generation and penetration. Wind energy in particular is ubiquitous, yet the stochastic nature of wind energy hinders its wide-spread adoption into the electric grid. Numerous techniques (improved wind forecasting, improved wind turbine design and improved power electronics) have been proposed to increase the penetration of wind energy, yet only a few have addressed the challenges of wind intermittency, grid stability and flexibility simultaneously. The problem of excess wind energy results in wind curtailment and has plagued large scale wind integration. NREL's HOMER software is used to show that a strong negative correlation exists between the cycles to failure of a storage device and the excess wind energy on the system. A 1 MJ magnesium-diboride superconducting magnetic energy storage (SMES) system is designed to alleviate momentary interruptions (lasting from a few milli-seconds to a few minutes) in wind turbines. The simulation results establish the efficacy of SMES coupled with wind turbines improve output power quality and show that a 1 MJ SMES alleviated momentary interruptions for ∼50 s in 3 MW wind turbines. These studies suggest that SMES when coupled to wind turbines could be ideal storage devices that improve wind power quality and electric grid stability.     

The potential of electricity generation on the east coast of Red Sea in Egypt

Wind characteristics have been analyzed based on long-term measured data of monthly mean wind speed of seven meteorological stations along the east coast of Red Sea in Egypt. It was found that the windiest stations (Region A) namely (Zafarana, Abu Darag, Hurghada and Ras Benas) have annual mean wind speeds (7.3, 7.2, 6.4 and 5.5 m/s) at 10 m height, respectively.Numerical estimations using measured wind speeds and frequencies to calculate the two Weibull parameters were carried out and two methods were applied.The methodical analysis for the corrected monthly wind power density at a height of 10 m above ground level, over roughness class 0 (water), for each station was done. The recommended correlation equation was also stated for Red Sea zone in Egypt. Also the corrected annual wind power density at the heights (50–70) m was obtained for all stations. Moreover, calculations show that the four stations in (Region A) have a huge energy potential available (430–1000 W/m²) at 70 m height, while Quseir and Suez stations (Region B) have good wind power density (170–190 W/m²) at 50 m height.A technical and economic assessment has been made of electricity generation from two turbines machines having capacity of (1000 and 600 kW) considered in Regions A & B, respectively, using WASP program. The yearly energy output, capacity factor and the electrical energy cost of kWh produced by the two different turbines in each region were estimated. The production costs of four stations in Region A was found to be less than 2€ cent/kWh and compared with retail tariff.     

Wind resource assessment of the Jordanian southern region

Wind data in terms of annual, seasonal and diurnal variations at Queira, which is located in the southern part of Jordan was studied and analyzed. For this purpose, long-term wind speed data for a period of 12 years (1990–2001) was used. The analysis showed that the seasonal and diurnal pattern of wind speed matches the electricity load pattern of the location. Higher winds of the order of 6 m/s and more were observed during both the summer months of the year (May–August) and peak hours (1100–1500) of the day. The wind duration availability is discussed as the number of hours during which the wind remained in certain wind speed intervals. The possibility of electricity generation from wind power at Queira was carried out using three different wind energy systems of sizes 100, 22 kW rated power, and a wind farm consisting of 25 small wind turbines; each of 4 kW rated power with hub heights of 20, 30, and 40 m. The energy production analysis showed higher production from the wind farm with a 20 m hub height than the production from the other two wind turbines. Similarly, the cost analysis showed that the lowest generation costs of 1 kWh were obtained for the wind farm compared to the other two wind turbines. The possibility of water pumping using the wind farm was also investigated. The results showed that water pumping using wind turbines is an appropriate alternative for the photovoltaic water pumping in the region.     

Wind energy analysis based on turbine and developed site power curves: A case-study of Darling City

The observed wind at a given site varies continuously as a function of time and season, increasing hub heights, topography of the terrain, prevailing weather condition etc. The quality of wind resource is one of the important site factors to be considered when assessing the wind potential of any location for any energy project. In this study, two wind energy analysis techniques are presented: the use of direct technique where the electrical power outputs of the wind turbines at a time t are estimated using the turbine power curve(s) and the use of statistical-based technique where the power outputs are estimated based on the developed site power curve(s). The wind resource assessment at Darling site is conducted using a 5-min time series weather data collected on a 10 m height over a period of 24 months. Because of the non-linearity of the site's wind speed and its corresponding power output, the wind resources are modeled and the developed site power curve(s) are used to estimate the long term energy outputs of the wind turbines for changing weather conditions. Three wind turbines rating of 1.3 MW, 1.3 MW and 1.0 MW were selected for the energy generation based on the gauged wind resource(s) at 50, 60 and 70 m heights, respectively. The energy outputs at 50 m height using the 1.3 MW WT were compared to the energy outputs at 60 m to determine the standard height for utility scale energy generation at this site. An additional energy generation of 190.71 MWh was available by deploying the same rated turbine at a 60 m height. Furthermore, comparisons were made between the use of turbine and site power curve for wind energy analysis at the considered heights. The results show that the analysis of the energy outputs of the WTs based on the site power curve is an accurate technique for wind energy analysis as compared to the turbine power curve. Conclusions are drawn on the suitability of this site for utility scale generation based on the wind resources evaluation at different heights.     

Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)

Wind energy has become a major competitor of traditional fossil fuel energy, particularly with the successful operation of multi-megawatt sized wind turbines. However, wind with reasonable speed is not adequately sustainable everywhere to build an economical wind farm. The potential site has to be thoroughly investigated at least with respect to wind speed profile and air density. Wind speed increases with height, thus an increase of the height of turbine rotor leads to more generated power. Therefore, it is imperative to have a precise knowledge of wind speed profiles in order to assess the potential for a wind farm site. This paper proposes a clustering algorithm based neuro-fuzzy method to find wind speed profile up to height of 100 m based on knowledge of wind speed at heights 10, 20, 30, 40 m. The model estimated wind speed at 40 m based on measured data at 10, 20, and 30 m has 3% mean absolute percent error when compared with measured wind speed at height 40 m. This close agreement between estimated and measured wind speed at 40 m indicates the viability of the proposed method. The comparison with the 1/7th law and experimental wind shear method further proofs the suitability of the proposed method for generating wind speed profile based on knowledge of wind speed at lower heights.     

Wind energy resource assessment for five locations in Saudi Arabia

The analysis of recently collected wind data at five sites in Saudi Arabia namely, Dhulum, Arar, Yanbu, Gassim and Dhahran is presented. The five sites represent different geographically and climatologically conditions. The data collected over a period spanned between 1995 and 2002 with different collection periods for each site. Daily, monthly and frequency profiles of the wind speed at the sites showed that Dhulum and Arar sites have higher wind energy potential with annual wind speed average of 5.7 and 5.4 m/s and speeds higher than 5 m/s for 60 and 47% of the time, respectively. The two sites are candidates for remote area wind energy applications. The costal site's, i.e. Yanbu and Dhahran wind speed data indicated that the two sites have lower annual wind speed averages and wind blows at speed higher than 5 m/s during afternoon hours. That makes the two sites candidates for grid connected wind systems for electrical load peak shaving. The data of Gassim site showed that the site has the lowest wind energy potential compared to the others. The annual energy produced by a Nordex N43 wind machine is estimated to be 1080, 990, 730, 454 and 833 MWh for Dhulum, Arar, Yanbu, Gassim and Dhahran, respectively. The analysis showed that the estimated annual energy produced by the machine based on 10 min averaged data is 2.5% higher than the estimated energy based on 30 min averaged data.     

Electrochemical modelling of ammonia synthesis in molten salt medium for renewable fuel production using wind power

Ammonia is one of the most abundantly used chemicals in the world, and it is a potential hydrogen carrier for possible solutions of hydrogen storage and transportation. The conventional method of ammonia production is energy-intensive that requires high pressure and it is dominantly dependent on fossil fuels for hydrogen and nitrogen production. With the electrochemical synthesis option, ammonia can be produced at atmospheric pressures and lower temperature levels. Hydrogen production via water electrolysis using renewable energy can further reduce carbon emissions. In this work, ammonia production via an electrochemical process in a molten salt medium is modelled through electrochemical impedance spectroscopy using several equivalent circuit models. Then, afterwards, for a case study in Qatar to produce renewable ammonia, wind data are used to predict the annual ammonia production rates where the wind turbine rated power is 6 MW. The electrochemical modelling results show that two main parameters emerged as the most influential on the modelling of the low frequencies region; the capacitance of the electrolyte, and the capacitance of the electrode. Furthermore, it is found that the Warburg diffusion limit showed little to negligible effect on the shape in the low-frequency region. The best performing model in terms of the goodness of fit is model 11 with a value of 4.75 × 10⁻⁷, which was modelled by 9 circuit elements (resistors, inductor, capacitors and Gerischer elements) and 12 adjustable parameters. Moreover, Models 11 and 12 reached a goodness of fit in the order of 10⁻⁷. Some models included a larger number of variables but offered poorer fit or insignificant improvement, which does not provide justification for the additional elements.     

Combining wave energy with wind and solar: Short-term forecasting

While wind and solar have been the leading sources of renewable energy up to now, waves are increasingly being recognized as a viable source of power for coastal regions. This study analyzes integrating wave energy into the grid, in conjunction with wind and solar. The Pacific Northwest in the United States has a favorable mix of all three sources. Load and wind power series are obtained from government databases. Solar power is calculated from 12 sites over five states. Wave energy is calculated using buoy data, simulations of the ECMWF model, and power matrices for three types of wave energy converters. At the short horizons required for planning, the properties of the load and renewable energy are dissimilar. The load exhibits cycles at 24 h and seven days, seasonality and long-term trending. Solar power is dominated by the diurnal cycle and by seasonality, but also exhibits nonlinear variability due to cloud cover, atmospheric turbidity and precipitation. Wind power is dominated by large ramp events–irregular transitions between states of high and low power. Wave energy exhibits seasonal cycles and is generally smoother, although there are still some large transitions, particularly during winter months. Forecasting experiments are run over horizons of 1–4 h for the load and all three types of renewable energy. Waves are found to be more predictable than wind and solar. The forecast error at 1 h for the simulated wave farms is in the range of 5–7 percent, while the forecast errors for solar and wind are 17 and 22 percent. Geographic dispersal increases forecast accuracy. At the 1 h horizon, the forecast error for large-scale wave farms is 39–49 percent lower than at individual buoys. Grid integration costs are quantified by calculating balancing reserves. Waves show the lowest reserve costs, less than half wind and solar.     

Electricity generation and wind potential assessment at Hurghada, Egypt

A technical and economic assessment has been made of the generation of electricity using wind turbines at one of the most promising wind sites in Egypt: Hurghada. In this paper, we used wind data recorded over 23 years for this site. The WASP program was used to calculate the values of wind speed frequency for the station, their seasonally values have been estimated and compared with measured data.Weibull parameters and the power law coefficient (n) for all seasons at different heights (10–70 m) has been estimated and used to describe the distribution and behavior of seasonal wind speed and their frequencies at Hurghada. The monthly and annual values of wind potential at a height of 70 m were obtained by extrapolation of the 10 m data from the results of our previous article [Ahmed Shata AS, Hanitsch R. The potential of electricity generation on the east coast of Red Sea in Egypt. Renew Energy 2006;31:1597–615] using the power law.Also, the monthly plant load factor (PLF) has been estimated, which is used to determine the expected annual energy output of a wind energy conversion system (WECS).Variation of annual capacity factor with rated wind speed for 10 different wind turbines has been studied. The lower the rated speed for the WECS of the same height, the higher will be the capacity factor values. The expected electrical energy cost of kWh produced by the wind turbine (Repower MM82) with a capacity of 2 MW considered for Hurghada station was found to be less than 1.5 € cent/kWh.     

Data efficient measure-correlate-predict approaches to wind resource assessment for small-scale wind energy

The feasibility of predicting the long-term wind resource at 22 UK sites using a measure-correlate-predict (MCP) approach based on just three months onsite wind speed measurements has been investigated. Three regression based techniques were compared in terms of their ability to predict the wind resource at a target site based on measurements at a nearby reference site. The accuracy of the predicted parameters of mean wind speed, mean wind power density, standard deviation of wind speeds and the Weibull shape factor was assessed, and their associated error distributions were investigated, using long-term measurements recorded over a period of 10 years. For each site, 120 wind resource predictions covering the entire data period were obtained using a sliding window approach to account for inter-annual and seasonal variations. Both the magnitude and sign of the prediction errors were found to be strongly dependent on the season used for onsite measurements. Averaged across 22 sites and all seasons, the best performing MCP approach resulted in mean absolute and percentage errors in the mean wind speed of 0.21 ms⁻¹ and 4.8% respectively, and in the mean wind power density of 11 Wm⁻² and 14%. The average errors were reduced to 3.6% in the mean wind speed and 10% in the mean wind power density when using the optimum season for onsite wind measurements. These values were shown to be a large improvement on the predictions obtained using an established semi-empirical model based on boundary layer scaling. The results indicate that the MCP approaches applied to very short onsite measurement periods have the potential to be a valuable addition to the wind resource assessment toolkit for small-scale wind developers.     

Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function

The wind resource is a crucial step in planning a wind energy project and detailed knowledge of the wind characteristic at a site is needed to estimate the performance of a wind energy project. In this paper, with the help of 2-parameter Weibull distribution, the assessment of wind energy potentiality at Kudat and Labuan in 2006-2008 was carried out. “WRPLOT” software has been used to show the wind direction and resultant of the wind speed direction. The monthly and yearly highest mean wind speeds were 4.76 m/s at Kudat and 3.39 m/s at Labuan respectively. The annual highest values of the Weibull shape parameter (k) and scale parameter (c) were 1.86 and 3.81 m/s respectively. The maximum wind power density was found to be 67.40 W/m² at Kudat for the year 2008. The maximum wind energy density was found to be 590.40 kWh/m²/year at Kudat in 2008. The highest most probable wind speed and wind speed carrying maximum energy were estimated 2.44 m/s at Labuan in 2007 and 6.02 m/s at Kudat in 2007. The maximum deviation, at wind speed more than 2 m/s, between observed and Weibull frequency distribution was about 5%. The most probable wind directions (blowing from) were 190° and 269° at Kudat and Labuan through the study years. From this study, it is concluded that these sites are unsuitable for the large-scale wind energy generation. However, small-scale wind energy can be generated at the turbine height of 100 m.     

Evaluation of electricity generation and energy cost of wind energy conversion systems (WECSs) in Central Turkey

The negative effects of non-renewable fossil fuels have forced scientists to draw attention to clean energy sources which are both environmentally more suitable and renewable. Although Turkey enjoys fairly high wind energy potential, an investigation and exploitation of this source is still below the desired level. In this study which is a preliminary study on wind energy cost in Central Anatolian-Turkey, the wind energy production using time-series approach and the economic evaluation of various wind energy conversion systems (WECSs) enjoying the 2.5, 5, 10, 20, 30, 50, 100 and 150 kW rated power size using the levelised cost of electricity (LCOE) method for the seven different locations in Central Turkey were estimated. In addition, effects of escalation ratio of operation and maintenance cost and annual mean speed on LCOE are taken into account. The wind speed data for a period between 2000 and 2006 years were taken from Turkish State Meteorological Service (TSMS). According to the result of the calculations, it is shown that the WECS of capacity 150 kW produce the energy output 120,978 kWh per year in the Case-A (Pinarbasi) for hub height 30 m and also the LCOE varies in the range of 0.29–30.0 $/kWh for all WECS considered.     

Wind energy assessment and wind farm simulation in Triunfo – Pernambuco,Brazil

This paper presents a wind energy assessment and a wind farm simulation in the city of Triunfo in the state of Pernambuco in the northeast region of Brazil. The wind data were obtained from the SONDA (Sistema de Organização Nacional de Dados Ambientais) project’s meteor station (wind speed, wind direction and temperature) at both heights of 50 m during a period of time of 30 months. The Triunfo wind characterization and wind power potential assessment study shows an average wind speed (V) of 11.27 m/s (predominant Southeast wind direction), an average wind power density (P/A_T) of 1.672 W/m² and Weibull parameters shape (K) and scale (A) respectively equal to 2.0 and 12.7 m/s. Those values demonstrate an important wind potential in this region for future wind farm prospection. The wind farm (TRI) was simulated by using 850 kW wind turbines given a total of 20 MW installed. The simulated results show(s) an AEP (annual energy produced) of 111.4 GWh, a capacity factor (C_f) of 62% and a total of 5.462 h of operation by year (full load hours). The economical simulated results show(s) a Pay-back of 3 years Internal Rate of Return (IRR) of 47% and Net Present Value (NPV) of 85.506 k€ (both in a period of time of 20 years).