A computational tool for evaluating the economics of solar and wind microgeneration of electricity
J. Kelleher and
J.V. Ringwood
Energy, 2009, vol. 34, issue 4, 401-409
Abstract:
This paper presents a method, implemented as a freely available computer programme, which is used to estimate the economics of renewable microgeneration of electricity from wind and solar energy sources. A variety of commercial small wind turbines and photovoltaic (PV) panels are considered and combined with raw energy data gathered from a variety of locations. Both residential and holiday home user profiles are available and options are selectable concerning feed-in tariffs (if available), government incentive schemes and the cost of capital borrowing. The configuration of the generation setup, which can consist of wind, PV and combination of wind/PV, is fully selectable by the user, with a range of appropriate default data provided. A numerical example, based on Irish data, is presented, which suggests that payback periods for solar and wind microgeneration systems can vary greatly (2.5–500 years), depending on the location, installation and economic variables.
Keywords: Microgeneration; Wind power; Solar power; Payback period; Economics (search for similar items in EconPapers)
JEL-codes: C65 (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544208002867
Full text for ScienceDirect subscribers only
Related works:
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:eee:energy:v:34:y:2009:i:4:p:401-409
DOI: 10.1016/j.energy.2008.10.009
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().