Expanded Implementation of Solar Photovoltaics: Forecasting and Risk Assessment
<p class="Default">This research is a forecast of solar photovoltaics (PV) implementation made for a period through to 2030. The leading factors of PV development that were included into the forecast model are the price for PV modules, the efficiency of silicon solar panels, the pric...
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doaj-dbcb3ccb45e44f98bd0643335a97328e2020-11-25T03:52:08ZengEconJournalsInternational Journal of Energy Economics and Policy2146-45532018-09-01851131183468Expanded Implementation of Solar Photovoltaics: Forecasting and Risk AssessmentBura Ahmetzhanov0Kashamida Tazhibekova1Aigerim Shametova2Abay Urazbekov3Karaganda State Technical UniversityKaraganda State Technical UniversityKaraganda State Technical UniversityKaraganda State Technical University<p class="Default">This research is a forecast of solar photovoltaics (PV) implementation made for a period through to 2030. The leading factors of PV development that were included into the forecast model are the price for PV modules, the efficiency of silicon solar panels, the price of lithium-ion batteries, the price of lithium and the silicon PV module manufacture. The model is based on the calculations made for the coefficients of correlation between the installed capacity and economic factors. The ARIMA forecasting method was applied to generate forecasts for each factor and installed capacity riding on specific factor’s back. The calculated coefficients show a strong correlation between the installed capacity and the above listed factors. According to the generated forecasts, the efficiency factor will reach an abstract limit of 30% by 2030. Investments in photovoltaics will increase up to 70%; this is 10% higher than current level.</p><p><strong>Keywords</strong>: Photovoltaics (PV), Forecasting, Risk Assessment of PV Implementation, PV power, Correlation Coefficients</p><p><strong>JEL Classifications: </strong>A11; B41; C01<strong></strong></p>https://www.econjournals.com/index.php/ijeep/article/view/6766 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Bura Ahmetzhanov Kashamida Tazhibekova Aigerim Shametova Abay Urazbekov |
spellingShingle |
Bura Ahmetzhanov Kashamida Tazhibekova Aigerim Shametova Abay Urazbekov Expanded Implementation of Solar Photovoltaics: Forecasting and Risk Assessment International Journal of Energy Economics and Policy |
author_facet |
Bura Ahmetzhanov Kashamida Tazhibekova Aigerim Shametova Abay Urazbekov |
author_sort |
Bura Ahmetzhanov |
title |
Expanded Implementation of Solar Photovoltaics: Forecasting and Risk Assessment |
title_short |
Expanded Implementation of Solar Photovoltaics: Forecasting and Risk Assessment |
title_full |
Expanded Implementation of Solar Photovoltaics: Forecasting and Risk Assessment |
title_fullStr |
Expanded Implementation of Solar Photovoltaics: Forecasting and Risk Assessment |
title_full_unstemmed |
Expanded Implementation of Solar Photovoltaics: Forecasting and Risk Assessment |
title_sort |
expanded implementation of solar photovoltaics: forecasting and risk assessment |
publisher |
EconJournals |
series |
International Journal of Energy Economics and Policy |
issn |
2146-4553 |
publishDate |
2018-09-01 |
description |
<p class="Default">This research is a forecast of solar photovoltaics (PV) implementation made for a period through to 2030. The leading factors of PV development that were included into the forecast model are the price for PV modules, the efficiency of silicon solar panels, the price of lithium-ion batteries, the price of lithium and the silicon PV module manufacture. The model is based on the calculations made for the coefficients of correlation between the installed capacity and economic factors. The ARIMA forecasting method was applied to generate forecasts for each factor and installed capacity riding on specific factor’s back. The calculated coefficients show a strong correlation between the installed capacity and the above listed factors. According to the generated forecasts, the efficiency factor will reach an abstract limit of 30% by 2030. Investments in photovoltaics will increase up to 70%; this is 10% higher than current level.</p><p><strong>Keywords</strong>: Photovoltaics (PV), Forecasting, Risk Assessment of PV Implementation, PV power, Correlation Coefficients</p><p><strong>JEL Classifications: </strong>A11; B41; C01<strong></strong></p> |
url |
https://www.econjournals.com/index.php/ijeep/article/view/6766 |
work_keys_str_mv |
AT buraahmetzhanov expandedimplementationofsolarphotovoltaicsforecastingandriskassessment AT kashamidatazhibekova expandedimplementationofsolarphotovoltaicsforecastingandriskassessment AT aigerimshametova expandedimplementationofsolarphotovoltaicsforecastingandriskassessment AT abayurazbekov expandedimplementationofsolarphotovoltaicsforecastingandriskassessment |
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