Solar power potential mapping in India using remote sensing inputs and environmental parameters

a b s t r a c tSolar potential of western Himalayan Indian state of Himachal Pradesh is assessed using Artificial Neural Network (ANN) based global solar radiation (GSR) prediction model. J48 algorithm in Waikato Environment for Knowledge Analysis (WEKA)is used for the selection of input parameters for ANN model for predicting GSR. Most relevant input parameters are found to be temperature, altitude and sunshine hours whereas latitude, longitude, clearness index and extraterrestrial radiation are found to be least influencing variables. The usefulness of J48 algorithm in variable selection is checked by developing five ANN models: ANN-1, ANN-2, ANN-3, ANN-4 and ANN-5. The maximum mean absolute percentage error (MAPE) for ANN-1, ANN-2, ANN-3, ANN-4 and ANN-5 are found to be 16.91%, 16.89%, 16.38%, 6.89% and 9.04% respectively. ANN-5 model is used to develop the solar maps of Himachal Pradesh. The estimated GSR varies from 3.59 to 5.38 kWh/m 2 /day indicating good solar potential for solar energy applications. A correlation is developed between NASA satellite data and ground measured GSR data to find values close to ground measured GSR for different locations. The correlation coefficient is found to be 0.97. Models developed can be used to assess solar potential of any location worldwide.

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“…The H.P. cities [33]. The annual GSR is used to assess the district wise solar energy potential of HP as shown in Table 4.…”

Section: Annual and Monthly Global Solar Radiation Mapsmentioning

confidence: 99%

Solar energy potential assessment of western Himalayan Indian state of Himachal Pradesh using J48 algorithm of WEKA in ANN based prediction model

Yadav

Chandel

2015

Renewable Energy

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“…On the other hand, many papers aimed at improving the prediction of the performance of a PV energy capture system have been published [14,[18][19][20][21][22][23]. From an adequate analysis of direct solar measurements and the predicted response of the PV systems it is possible to calculate the energy obtainable for a given location [24,25].…”

Section: Journal Of Solar Energymentioning

confidence: 99%

A Simple and Inexpensive Method for Evaluating the Photovoltaic Potential: Its Validation in Buenos Aires and Antarctica

Cabezas

Hawryluk

Franco

et al. 2016

Journal of Solar Energy

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The use of renewable energies requires a precise and detailed quantification of the resource available. Because of the cost of solar stations or limited availability of skilled human resources, in most emerging countries, this assessment is made only on a few points scattered over large areas. We report here a simple and inexpensive method to evaluate the photovoltaic (PV) potential for a specific geographic region and a given PV capture technology. The system allows for a direct evaluation of the energy actually obtainable by scaling the measurement array of photovoltaic cells. The proposed measurement system can be installed as a stand-alone unit, or as part of a measurement network, connected to a more sophisticated central hub. The measurement station consists of said PV array (or similar PV array), a resistor, and a portable data logger. The system is calibrated with a device composed of a small array of PV cells, a resistor load bank, and two multimeters. Due to its low cost, this system can be replicated as many times as required with minimal investment. This would make it possible to evaluate the available photovoltaic potential of large regions with accurate and detailed data. Measurements carried out in Buenos Aires and in Antarctica confirm the consistency of the method.

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“…India is a good place for illustrating site adaptation due to its challenging climatic conditions associated to the monsoon and to the atmospheric aerosol loads. India is showing a high growth in large-scale deployment of solar power plants and in consequence is setting up over 50 new meteorological stations for measuring the direct, global and diffuse solar radiation [22,23]. The solar resources expected in India are generally high and particularly Rajasthan and Gujarat regions are believed to receive the maximum direct normal irradiance in the country [24].…”

Section: Introductionmentioning

confidence: 99%

Correcting satellite derived DNI with systematic and seasonal deviations: Application to India

Polo

Martín²,

Vindel

2015

Renewable Energy

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a b s t r a c tA simple method for correcting satellite-derived direct normal irradiance, with important deviations to the experimental data, is presented in this work and illustrated for the particular case of Rajasthan (India). Northwest India is expected to have a high level of solar radiation and it is an interesting area for solar concentrating power systems. However uncertainty in direct normal irradiance estimations from satellite may affect negatively to the bankability of solar plants. Direct normal irradiance have been estimated for a site in Rajasthan from satellite information for the period 2003 to 2011, and ground measurements during 2011 have been used to analyze the uncertainties and to develop a simple correction method. The original satellite estimations showed important deviations from the experimental values and high bias. A systematic underestimation of direct irradiance has been observed during the dryer seasons that could be attributed to an overestimation of the aerosol optical depth input to the model. These observations have allowed the design of a correction methodology. Unbiased new estimations of direct normal irradiance have been generated with this methodology with important reduction in the deviations and with an agreement in the distribution functions compared to the distribution function of the ground data.

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Solar power potential mapping in India using remote sensing inputs and environmental parameters

Cited by 113 publications

References 24 publications

Solar energy potential assessment of western Himalayan Indian state of Himachal Pradesh using J48 algorithm of WEKA in ANN based prediction model

Solar energy potential assessment of western Himalayan Indian state of Himachal Pradesh using J48 algorithm of WEKA in ANN based prediction model

A Simple and Inexpensive Method for Evaluating the Photovoltaic Potential: Its Validation in Buenos Aires and Antarctica

Correcting satellite derived DNI with systematic and seasonal deviations: Application to India

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