Abstract

http://ssrn.com/abstract=2054073
 
 

Citations (1)



 
 

Footnotes (3)



 


 



The Optimal Share of Variable Renewables


Lion Hirth


Vattenfall Europe AG

April 2012

USAEE Working Paper No. 2054073

Abstract:     
The variability of wind and solar power crucially affects their social value. This paper determines the welfare-optimal market share of wind and solar power under different technology, price, and policy assumptions, focussing on the impact of variability. A numerical electricity market model with high temporal resolution is used to represent variability realistically, and empirical data are used to capture crucial correlations over time and across space. Results indicate that variability significantly limits the role that wind and solar power should play in a cost-optimal energy system. The optimal share of wind power in North- Western Europe is estimated to be 7-10% in the medium term and around 25% in the long term. If wind speeds were constant, the optimal deployment rate would be up to twice as high. Solar power is too expensive to be deployed efficiently, even at very optimistic assumptions regarding cost development.

Number of Pages in PDF File: 25

Keywords: wind power, solar power, variable renewables, cost-benefit analysis, numerical optimization

JEL Classification: C61, C63, Q42, Q48, D41

working papers series


Download This Paper

Date posted: May 8, 2012  

Suggested Citation

Hirth, Lion, The Optimal Share of Variable Renewables (April 2012). USAEE Working Paper No. 2054073. Available at SSRN: http://ssrn.com/abstract=2054073 or http://dx.doi.org/10.2139/ssrn.2054073

Contact Information

Lion Hirth (Contact Author)
Vattenfall Europe AG ( email )
Chausseestrasse 23
Berlin, 10115
Germany
Feedback to SSRN


Paper statistics
Abstract Views: 562
Downloads: 181
Download Rank: 96,889
Citations:  1
Footnotes:  3

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo6 in 0.250 seconds