A novel forecasting model for wind speed assessment using sentinel family satellites images and machine learning method

Nezhad, Meysam Majidi; Heydari, Azim; Pirshayan, Elmira; Groppi, Daniele; Garcia, Davide Astiaso

doi:10.1016/j.renene.2021.08.013

Cited by 31 publications

(16 citation statements)

References 61 publications

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“…As a matter of fact, existing techniques and methods are incapable of solving analytical challenges relating to EO-based satellite data. Fortunately, machine learning methods are growing at a remarkable rate due to the dramatic growth of technology that can fully cover EO-based satellite data for GESs area (Majidi Nezhad et al, 2021). These methods can be very effective in the context of multisource data with a wide range of dimensions.…”

Section: Discussionmentioning

confidence: 99%

Green Energy Sources Assessment Using Sentinel-1 Satellite Remote Sensing

et al. 2021

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Due to the growing use of Green Energy Sources (GESs), the activities of mapping, monitoring, measurement, and detection of various GESs have become crucial. Assessing and measuring GESs are very complex since different environmental conditions occur. This importance is even greater when researchers face a shortage of measuring instruments and tools in many parts of the world. GES assessment is a challenging task that requires accurate and continuous measurement methods. Currently, traditional methods are very time-consuming and require spending money and human sources. So, the use of accurate and fast measurement methods and tools assessing measuring GESs potential are seriously recommended, which can greatly help the growth of the use of GESs, especially to cover and focus large areas. Satellite remote sensing is used to observe the environment in many fields and new and fast applications. Satellites remote sensing technologies and techniques for GESs assessing are fast, accurate, and can help to reduce costs and decision-making risks of GESs converters installations projects and provide suitable products to the public end-users. These could also be used to identify regions of interest for energy converter installations and to accurately identify new areas with interesting potentials. In this case, researchers can dramatically reduce the possibility of significant error in assessment methods. There is a lack of in-situ measuring tools mainly due to their high economic costs in the interested areas; an accurate analysis was carried out to assess the GESs energy potential. Since there are only limited options for further expanding the measurement over large areas, the use of satellites makes it easier to overcome in-situ limitations. Actually, to use and develop it as much as possible, a correct interdisciplinary understanding is needed. Satellite remote sensing technology for identifying suitable areas for GESs power plants could be a powerful tool that is constantly increasing in its new and fast applications but requires good planning to apply it in various GESs converters installations projects. In this article, a comprehensive review on wind, wave, biomass, geothermal sources assessment using Sentinel-1 (S-1) Synthetic Aperture Radar (SAR) satellite estimation has been summarized along with the different techniques available to measure GESs using satellites. In the paper, several of the successful estimation techniques were introduced in each section and compared for the understanding of limitations and strengths of different methods of GESs availability evaluation.

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Section: Discussionmentioning

confidence: 99%

Green Energy Sources Assessment Using Sentinel-1 Satellite Remote Sensing

et al. 2021

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“…The accuracy of reanalysis data is commonly evaluated by comparison with measured data using statistical analysis (Kardakaris et al, 2021; Majidi Nezhad et al, 2021a). The evaluation of the reanalysis data is initial step in wind resource assessment.…”

Section: Methodsmentioning

confidence: 99%

“…Offshore wind power generation is becoming an attractive option in wind power industry with four times more growth in installed capacity than onshore wind in the last decade (IRENA, 2021). Offshore wind has many advantages over onshore wind including higher wind speeds, consistent patterns, uniformity for wider areas and lesser environmental impact (Majidi Nezhad et al, 2021a). Several of the typical drawbacks associated with onshore wind power generation can be avoided in case of offshore wind farms, such as land occupancy and noise issues (Lima et al, 2015; Majidi Nezhad et al, 2021a).…”

Section: Introductionmentioning

confidence: 99%

“…Offshore wind has many advantages over onshore wind including higher wind speeds, consistent patterns, uniformity for wider areas and lesser environmental impact (Majidi Nezhad et al, 2021a). Several of the typical drawbacks associated with onshore wind power generation can be avoided in case of offshore wind farms, such as land occupancy and noise issues (Lima et al, 2015; Majidi Nezhad et al, 2021a). The Levelized Cost of Electricity (LCOE) for offshore wind farms has reduced by 48% from 16.2 to 8.4 US¢/kWh in the last decade (IRENA, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…28125°), elevation levels of 10 and 100 m and 137 pressure levels from 1979 to date (Kardakaris et al, 2021; Olauson, 2018). The use of satellite and reanalysis data has been reported for wind resource assessment in previous studies (Gil Ruiz et al, 2021; Kistler et al, 2001; Kokkos et al, 2021; Majidi Nezhad et al, 2021a; Nezhad et al, 2021b, 2021c). The quality and accuracy of reanalysis data is important to evaluate before its use which is checked against measured data.…”

Section: Introductionmentioning

confidence: 99%

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Offshore wind resource assessment using reanalysis data

et al. 2022

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The growth rate of offshore wind is increasing due to technological advancement and reduction in cost. An approach using mast measured data at coastline and reanalysis data is proposed for offshore wind resource assessment, especially for developing countries. The evaluation of fifth generation European Reanalysis (ERA5) data was performed against measured data using statistical analysis. ERA5 data slightly underestimates wind speed and wind direction with percentage bias of less than 1%. Wind resource assessment of region in Exclusive Economic Zone (EEZ) of Pakistan was performed in terms of wind speed and Wind Power Density (WPD). The range of monthly mean wind speed and WPD in the region was 4.03–8.67 m/second and 73–515 W/m2 respectively. Most-probable wind speed and dominating wind direction on corners and center of the region were found using probability distributions and wind rose diagrams respectively. Most-probable wind speed ranges 4.41–7.64 m/second and dominating wind direction is southwest.

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A Review on Wind Power Forecasting Regarding Impacts on the System Operation, Technical Challenges, and Applications

et al. 2022

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Wind energy generation is a fast developing efficient renewable source widely used for modern power generation. [1] Countries and energy companies have increased their interest in electricity generation from wind energy in the last decades, thanks to its natural, cost-free, and environmentally friendly features. [2] Wind power plants can generate electrical energy at any time of the day and are distributed energy sources for systems that need permanent energy. [3] Nonetheless, due to the disordered nature of the earth's atmosphere, there is a major uncertainty in the electrical power produced by the wind, which causes complexities in the utilization and management of wind energy sources. [4] The changes in weather conditions depending on time and location also create uncertainty in managing the supply-demand balance controlled by the grid operators. [5] In cases where the electrical energy produced by wind power plants is insufficient, auxiliary energy sources provide operational support to the electric grid. [6] Ensuring the supply-demand balance in the electricity grid is also an important condition for the electrical power quality and energy supply in the transmission system, and wind power plant operators care about the follow-up of wind power in terms of economy, operation, and planning. [7] For this, the presence of wind power forecasting (WPF) is an essential factor in the optimization of wind power plants. [8] For consumers to use electrical energy uninterruptedly, efficiently, and economically, wind power plant operators need to estimate the generated electrical energy smoothly. [9] The smooth estimation of electrical power generated by wind turbines increases the operational efficiency for system maintenance, planning, investment, and energy traders. [10,11] It is a precious procedure for electrical grids to provide a respectable commercial yield on the electrical energy market. [12] The capability of advanced WPF provides the contributions like balancing the power system and mitigation of penalties, scheduling the maintenance of wind power plants, investment regarding site location, and technoeconomic and socioeconomic benefits. [13,14] In this way, it is possible to reduce the energy cost and obtain high revenue in the energy market as a result of the contributions obtained for wind power generation systems. [15]

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A novel forecasting model for wind speed assessment using sentinel family satellites images and machine learning method

Cited by 31 publications

References 61 publications

Green Energy Sources Assessment Using Sentinel-1 Satellite Remote Sensing

Green Energy Sources Assessment Using Sentinel-1 Satellite Remote Sensing

Offshore wind resource assessment using reanalysis data

A Review on Wind Power Forecasting Regarding Impacts on the System Operation, Technical Challenges, and Applications

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