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Vijay, Vivek
- Solar Photovoltaic Power Generation Forecasting Models and Techniques
Abstract Views :158 |
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Authors
Affiliations
1 Indian Institute of Technology Jodhpur, IN
2 Department of Electrical Engineering Faculty of Engineering, D.E.I. Dayalbagh, Agra, U.P.-282 005, IN
3 ERED, Central Power Research Institute, Bangalore - 560080, IN
1 Indian Institute of Technology Jodhpur, IN
2 Department of Electrical Engineering Faculty of Engineering, D.E.I. Dayalbagh, Agra, U.P.-282 005, IN
3 ERED, Central Power Research Institute, Bangalore - 560080, IN
Source
Power Research, Vol 10, No 1 (2014), Pagination: 165-174Abstract
The various forms of solar energy - solar heat, solar photovoltaic, solar thermal electricity, and solar fuels offer a clean, climate-friendly, very abundant and in-exhaustive energy resource to mankind. Solar power is the conversion of sun light into electricity, directly using photovoltaic (PV). The forecasting of energy Demands have become concerns for facility managers, and predicting energy generation plays a critical role in power-system management, scheduling, and dispatch operations. A reliable energy supply forecast helps to prevent unexpected loads and provides vital information for decisions made on energy generation and purchase. However, study of energy generation prediction by the photovoltaic (PV) system has been limited over the years, especially concerning short-term predictions. This study will helps in providing the details on different type of models and techniques of solar power forecasting.Keywords
Solar forecasting; Forecasting models; Forecasting techniques.
- Analysis of Solar Power Variability Due to Seasonal Variation and its Forecasting for Jodhpur Region Using Artificial Neural Network
Abstract Views :203 |
PDF Views:0
Authors
Affiliations
1 Indian Institute of Technology Jodhpur, Rajasthan, Old Residency Road, Ratanada, Jodhpur - 342 011, IN
2 Dayalbagh Educational Institute, Electrical Department Faculty of engineering, Dayalbagh Agra-282005, IN
3 ERED, Central Power Research Institute, Bangalore - 560 080, IN
1 Indian Institute of Technology Jodhpur, Rajasthan, Old Residency Road, Ratanada, Jodhpur - 342 011, IN
2 Dayalbagh Educational Institute, Electrical Department Faculty of engineering, Dayalbagh Agra-282005, IN
3 ERED, Central Power Research Institute, Bangalore - 560 080, IN
Source
Power Research, Vol 9, No 3 (2013), Pagination: 423-430Abstract
In 21st century solar power variability is an important issue due to grid integration. In these days grid integration is very popular because of heavy load. So solar power, wind power and conventional power are basic sources of grid integration. Solar power is playing a key role in grid integration. The main objective of this paper is to analyse solar power variability due to seasonal variation in Jodhpur. Jodhpur is known as sun-city for an average 320 sunny days in a year. Average solar insolation available in Jodhpur city is 5.7-6.0 kWh/m2 per day. This is second highest insolation in the world. In this paper, the Solar power variability analysis is carried out based on the data collected from a typical 43 kW amorphous silicon solar photovoltaic system installed in Jodhpur. Mansoon, winter and summer seasons are used for analysis of variation in Photovoltaic Generation due to change of solar insolation. Output of solar photovoltaic system depends on solar insolation and in this paper we have analysed the variation in solar power according to rainy, winter and summer seasons and used artificial neural network to predict the power output from PV system. The paper showed that proposed ANN model is more accurate and study of variability in solar power can help in plant operation, power scheduling and dispatchability.Keywords
No Keywords- Analysis of Solar Power Variability Due to Seasonal Variation and its Forecasting for Jodhpur Region Using Artificial Neural Network
Abstract Views :194 |
PDF Views:0
Authors
Affiliations
1 Indian Institute of Technology Jodhpur, Rajasthan, Old Residency Road, Ratanada, Jodhpur - 342 011, IN
2 Dayalbagh Educational Institute, Electrical Department Faculty of engineering, Dayalbagh Agra-282005, IN
3 ERED, Central Power Research Institute, Bangalore - 560 080, IN
1 Indian Institute of Technology Jodhpur, Rajasthan, Old Residency Road, Ratanada, Jodhpur - 342 011, IN
2 Dayalbagh Educational Institute, Electrical Department Faculty of engineering, Dayalbagh Agra-282005, IN
3 ERED, Central Power Research Institute, Bangalore - 560 080, IN
Source
Power Research, Vol 9, No 3 (2013), Pagination: 423-430Abstract
In 21st century solar power variability is an important issue due to grid integration. In these days grid integration is very popular because of heavy load. So solar power, wind power and conventional power are basic sources of grid integration. Solar power is playing a key role in grid integration. The main objective of this paper is to analyse solar power variability due to seasonal variation in Jodhpur. Jodhpur is known as sun-city for an average 320 sunny days in a year. Average solar insolation available in Jodhpur city is 5.7-6.0 kWh/m2 per day. This is second highest insolation in the world. In this paper, the Solar power variability analysis is carried out based on the data collected from a typical 43 kW amorphous silicon solar photovoltaic system installed in Jodhpur. Mansoon, winter and summer seasons are used for analysis of variation in Photovoltaic Generation due to change of solar insolation. Output of solar photovoltaic system depends on solar insolation and in this paper we have analysed the variation in solar power according to rainy, winter and summer seasons and used artificial neural network to predict the power output from PV system. The paper showed that proposed ANN model is more accurate and study of variability in solar power can help in plant operation, power scheduling and dispatchability.Keywords
No Keywords- Combined Effect of Deterministic and Stochastic Variables on Comparative Performance Analysis of 110 kW A-Si PV and C-Si PV based Rooftop Grid Tied Solar Photovoltaic Systems in Jodhpur
Abstract Views :182 |
PDF Views:0
Authors
Affiliations
1 Indian Institute of Technology Jodhpur, Old Residency Road, Jodhpur - 342 011, Rajathan, IN
2 Dayalbagh Educational Institute, Dayalbagh, Agra – 282005, Uttar Predesh, IN
3 Central Power Research Institute, Bangalore - 560 080, IN
1 Indian Institute of Technology Jodhpur, Old Residency Road, Jodhpur - 342 011, Rajathan, IN
2 Dayalbagh Educational Institute, Dayalbagh, Agra – 282005, Uttar Predesh, IN
3 Central Power Research Institute, Bangalore - 560 080, IN