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Solar Radiation Forecasting for Moderate Climatic Zone
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The challenge with solar energy prediction is that the solar radiation is intermittent and uncontrollable. Energy forecasting can be used to mitigate some of the challenges that arise from the uncertainty in the resource. Weather data was sourced from India Meteorological Department for Bangalore and Chennai location. This paper provides statistical approach to predict the solar power in future. Analysis was done for different predictive models; Multiple Regression Model is used as we have multiple inputs. The results indicate the prediction of solar radiation has better accuracy during higher irradiation period rather than lower irradiation period.
Keywords
Irradiation, Multiple Regression, Solar Forecasting, Solar Radiation.
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- Sanders S, Barrick C, Maier F, Rasheed K. Solar radiation prediction improvement using weather forecasts. 16th IEEE International Conference on Machine Learning and Applications (ICMLA); 2017. https://doi.org/10.1109/ICMLA.2017.0-112
- Orjuela A, Hernandez CJ, Rivero C. Very short term forecasting in global solar irradiance using linear and nonlinear models. IEEE Workshop on Power Electronics and Power Quality Applications (PEPQA); 2017. https://doi.org/10.1109/PEPQA.2017.7981691
- Hassan M, Ali M, Ali A, Kumar J. Forecasting dayahead solar radiation using machine learning approach. 4th Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE); 2017. https://doi.org/10.1109/APWConCSE.2017.00050. PMid:28515669. PMCid:PMC5409806
- Abuella M, Chowdhury B. Solar power probabilistic forecasting by using multiple linear regression analysis. SoutheastCon; 2015. https://doi.org/10.1109/ SECON.2015.7132869
- Haupt S, Kosovic B, Jensen T, Cowie J, Jimenez P, Wiener G. Comparing and integrating solar forecasting techniques. IEEE 43rd Photovoltaic Specialists Conference (PVSC); 2016. https://doi.org/10.1109/PVSC.2016.7749751
- Snegirev D, Eroshenko S, Khalyasmaa A, Dubailova V, Stepanova A. Day ahead solar power plant forecasting accuracy improvement on the hourly basis. IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus); 2019. https://doi.org/10.1109/EIConRus.2019.8657024
- Hussain S, Alili A. Day ahead hourly forecast of solar irradiance for Abu Dhabi, UAE. IEEE Smart Energy Grid Engineering (SEGE); 2016. https://doi.org/10.1109/SEGE.2016.7589502
- Serttas F, Hocaoglu F, Akarslan E. Short term solar power generation forecasting: A novel approach. 2018 International Conference on Photovoltaic Science and Technologies(PVCon); 2018. https://doi.org/10.1109/PVCon.2018.8523919
- Vijay V, Singh VP, Bhatt DM, Chaturvedi. Generalised neural network methodology for short term solar power forecasting”, 13th International Conference on Environment and Electrical Engineering (EEEIC); 2013.
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