Assessment of solar and wind energy potentials for three free economic and industrial zones of Iran

Mohammadi, Kasra; Mostafaeipour, Ali; Sabzpooshani, Majid

doi:10.1016/j.energy.2014.02.024

Cited by 60 publications

(25 citation statements)

References 30 publications

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“…Weibull distribution function is given by (Curry et al 2012;Mohammadi and Mostafaeipour 2013b;Pryor et al 2005;Mohammadi et al 2014): where v, k and c are wind speed (m/s), shape factor (dimensionless) and scale factor (m/s), respectively. k resemble the potential of wind energy in the location and show how peaked the wind distribution is.…”

Section: Weibull Distribution Functionmentioning

confidence: 99%

RETRACTED ARTICLE: Application of extreme learning machine for estimation of wind speed distribution

et al. 2015

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the same Weibull parameters. The survey results reveal that applying ELM approach is eventuated in attaining further precision for estimation of both Weibull parameters compared to other methods evaluated. Mean absolute percentage error, mean absolute bias error and root mean square error for k are 8.4600 %, 0.1783 and 0.2371, while for c are 0.2143 %, 0.0118 and 0.0192 m/s, respectively. In conclusion, it is conclusively found that application of ELM is particularly promising as an alternative method to estimate Weibull k and c factors.

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Section: Weibull Distribution Functionmentioning

confidence: 99%

RETRACTED ARTICLE: Application of extreme learning machine for estimation of wind speed distribution

et al. 2015

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“…Another study has focused on three free economic and industrial zones of Iran, called Chabahar, Kish and Salafchegan. It also demonstrates a tremendous result, showing that all three regions have great potential solar and wind energy throughout the year suitable for utilizing different types of solar energy systems (Mohammadi et al, 2014). Some researchers have focused on special cities.…”

Section: Introductionmentioning

confidence: 99%

Renewable Energy Sources in Iran: Policy and Regulation

Safari¹,

Safari²

2017

JPL

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According to the Fifth Five Year Development Plan, in Iran, renewable resources, under the green horizon scenarios, must provide 5,000 MW of electricity. Among different types of renewable source of energy, there is no shortage of information in Iran, which is located near to zero line (earth's equator), with about 300 clear sunny days in a year, about setting policies promoting solar energy. Taking into account the availability and benefits of solar energy for Iran, this paper has focused on solar energy.Recent statistics show that, if the current development plans proceed, the capacity of the installed renewable energy systems would reach 2.8GW by 2030. This requires more than 2800 million US dollar investment in 20 years, i.e., 2010 to 2030. Despite the advantages of using solar energy, such as reducing greenhouse gases, it is important to note that solar power is 2.5 to 5 times as expensive as electricity from existing conventional power sources, such as coal and other sources. In order to encourage people to use solar power, there is a need to change our laws and establish an integrated energy regulation, involving tax policy mechanisms to support the deployment of solar energy in Iran. As Iran is dependent upon its fossil fuels, the transition from fossil fuels to renewable, which is a worldwide goal to reduce GHG or CO2 emissions, requires the adoption of a comprehensive policy and integrated regulation nationwide, taking a multidisciplinary approach. This paper exemplifies and considers the 2005 Energy Policy Act and Investment Tax Credit (ICT) for residential energy property, illustrating how solar-energy-regulation could contribute to the sustained development of solar energy. The main purpose is to help the development of sustainable solar energy regulation in Iran.

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“…Let the yearly transposition factor at the yearly fixed optimal tilt angle (β Yopt ) be denoted as Tf 1 ( 1 ) where; …”

Section: Comparison Of the Yearly Fixed And Seasonally Adjusted Optimmentioning

confidence: 99%

“…However, daily and monthly adjustment of tilt-angles is troublesome in practical application due to frequent adjustment and complex structure of frames which support solar panels. In this wise, seasonal adjustment of tilt-angle proves to be simpler and easier to be implemented in practice [1]. In particular, in Nigeria, as well as in PVSyst simulation software [9][10][11][12][13], two seasons are identified, namely; winter and summer.…”

Section: Introductionmentioning

confidence: 99%

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Determination of Optimal Tilt Angle for Biannual Seasonally Adjusted Flat-Plate Photovoltaic Modules Based on Perez Transposition Model

Ekanem¹

2017

AJSEA

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Determination of optimal tilt angle for seasonally adjusted flat-plate photovoltaic (PV) modules based on Perez transposition model is presented. Particularly, two seasons are considered, namely winter and summer. As such, two optimal tilt angles are obtained which requires that the tilt angle the of flat plate PV module will be adjusted twice in a year. The method is based on yearly global radiation incident on a horizontal plane as downloaded from NASA website. Furthermore, PVSyst software that uses transposition model is used to generate the yearly global radiation incident on a tilted plane for various tilt angles, from 0° to 46°. The location used in the study is at longitude of 7.860761, latitude of 5.011474 and elevation of 67.506 m. The results show that the winter season optimal tilt angle is 25.46° the summer season optimal tilt angle is 0° and the yearly fixed optimal tilt angle is 7.16°. The annual transposition factor for the seasonally adjusted tilt angle is 1.05 whereas annual transposition factor for the year fixed tilt angle 1.01. The result amounts to 3.6% improvement is solar radiation capture due to the seasonal adjustment of the tilt angle when compare to the yearly fixed tilt angle.

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Assessment of solar and wind energy potentials for three free economic and industrial zones of Iran

Cited by 60 publications

References 30 publications

RETRACTED ARTICLE: Application of extreme learning machine for estimation of wind speed distribution

RETRACTED ARTICLE: Application of extreme learning machine for estimation of wind speed distribution

Renewable Energy Sources in Iran: Policy and Regulation

Determination of Optimal Tilt Angle for Biannual Seasonally Adjusted Flat-Plate Photovoltaic Modules Based on Perez Transposition Model

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