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...

Full description

Bibliographic Details
Main Authors: Bura Ahmetzhanov, Kashamida Tazhibekova, Aigerim Shametova, Abay Urazbekov
Format: Article
Language:English
Published: EconJournals 2018-09-01
Series:International Journal of Energy Economics and Policy
Online Access:https://www.econjournals.com/index.php/ijeep/article/view/6766
id doaj-dbcb3ccb45e44f98bd0643335a97328e
record_format Article
spelling 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
_version_ 1724484125550706688