The effects of wind generation capacity on electricity prices and generation costs: a Monte Carlo analysis
Lynch and
John Curtis
Applied Economics, 2016, vol. 48, issue 2, 133-151
Abstract:
We use Monte Carlo analysis to examine the potential of increased renewable generation to provide a hedge against variability in energy prices and costs. Fuel costs, electricity demand and wind generation are allowed to vary and a unit commitment and economic dispatch algorithm is employed to produce cost-minimizing generation schedules under different levels of installed wind capacity. Increased wind capacity reduces the mean and the variance of production costs but only the variance of electricity prices. Wind generators see their market revenues increase while consumer payments and fossil generator profits do not considerably vary as wind capacity increases. Risk aversion is captured by considering the conditional value-at-risk for both consumers and producers. The optimal level of wind generation increases as risk aversion increases due to the potential of wind to act as a hedge against very high electricity prices in high fuel price scenarios.
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2015.1076145 (text/html)
Access to full text is restricted to subscribers.
Related works:
Working Paper: The Effects of Wind Generation Capacity on Electricity Prices and Generation Costs: a Monte Carlo Analysis (2014) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:applec:v:48:y:2016:i:2:p:133-151
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/00036846.2015.1076145
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().