Investment risk prediction method of renewable energy market under the background of carbon neutralisation
by Chunxia Liu
International Journal of Global Energy Issues (IJGEI), Vol. 45, No. 4/5, 2023

Abstract: To improve the accuracy of market investment risk prediction and reduce the time consumption of investment risk prediction, this paper proposes a renewable energy market investment risk prediction method under the background of carbon neutralisation. Firstly, based on the background of carbon neutrality, the earned value management theory is used to quantitatively describe the investment risk of renewable energy market. Secondly, aiming at carbon neutralisation, the system dynamics method is used to design the investment risk prediction function of renewable energy market. Finally, the residual test is used to verify the investment risk prediction results of the energy market, so as to realise the investment risk prediction of the renewable energy market. The results show that the accuracy of market investment risk prediction of this method is 96.5%, and the time of investment risk prediction is only 8.6 s. It can accurately predict the investment risk of renewable energy market.

Online publication date: Thu, 06-Jul-2023

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Global Energy Issues (IJGEI):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com