DocumentCode :
648374
Title :
Options based reserve procurement strategy for wind generators — Using binomial trees
Author :
Venkatesh, B.
fYear :
2013
fDate :
21-25 July 2013
Firstpage :
1
Lastpage :
1
Abstract :
Summary form only given. Wind and Solar PV are the most mature forms of renewable energy and are integral to our clean energy strategy. Their intermittency poses technical and economic challenges. Technical challenges are load balancing, frequency regulation, etc. Economic challenges include providing least costing load balancing (reserves) services to these intermittent generators. This paper considers a future electricity market situation wherein wind generators are required forecast and bid to supply energy. The future electricity market treats wind generators similar to conventional generators penalizing for underproduction and pays poorly for overproduction. An intra-day (<;24 hours) secondary market is proposed in this paper where a wind generator and a reserve provider can bilaterally trade in reserves. Reserves are traded in the market by purchasing options to buy reserves at predetermined strike prices by paying premiums. These reserves include call and put options to address underproduction and overproduction. A binomial tree approach for estimating possible deviation from the forecast value is used. A new optimization formulation is proposed that uses binomial tree option pricing technique to determine optimal values of strike prices and premiums for call and put options. Two examples illustrate the benefits of the proposed idea.
Keywords :
binomial distribution; power markets; pricing; procurement; renewable energy sources; wind power plants; binomial tree option pricing technique; clean energy strategy; electricity market; options based reserve procurement strategy; renewable energy; secondary market; wind generators; Computers; Economics; Electricity supply industry; Generators; Load management; Procurement; Wind forecasting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location :
Vancouver, BC
ISSN :
1944-9925
Type :
conf
DOI :
10.1109/PESMG.2013.6672953
Filename :
6672953
Link To Document :
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