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     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2012(Vol.4, Issue:05)
Article Information:

Stochastic Electric Power Generation Unit Commitment in Deregulated Power Market Environment

F. Gharehdaghi, H. Jamali, M. Deysi and A. Khalili
Corresponding Author:  F. Gharehdaghi 
Submitted: 2011 September, 14
Accepted: 2011 October, 15
Published: 2012 March, 01
Abstract:
Utilities participating in deregulated markets observe increasing uncertainty in load (i.e., demand for electric power) and prices for fuel and electricity on spot and contract markets. This study proposes a new formulation of the unit commitment problem of electric power generators in a restructured electricity market. Under these conditions, an electric power generation company will have the option to buy or sell from a power pool in addition to producing electricity on its own. The unit commitment problem is expressed as a stochastic optimization problem in which the objective is to maximize expected profits and the decisions are required to meet the standard operating constraints. Under the assumption of competitive market and price taking, it is depicted that the unit commitment schedule for a collection of N generation units can be solved by considering each unit separately. The volatility of the spot market price of electricity is represented by a stochastic model. This paper uses probabilistic dynamic programming to solve the stochastic optimization problem pertaining to unit commitment. It is shown that for a market of 150 units the proposed unit commitment can be accurately solved in a reasonable time by using the normal, Edgeworth, or Monte Carlo approximation methods.

Key words:  Dynamic voltage compensator, reactive compensation, voltage and energy enhancement, wind energy conversion system, , ,
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Cite this Reference:
F. Gharehdaghi, H. Jamali, M. Deysi and A. Khalili, . Stochastic Electric Power Generation Unit Commitment in Deregulated Power Market Environment. Research Journal of Applied Sciences, Engineering and Technology, (05): 439-445.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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