NDLI: A risk-constrained optimal bidding strategy for a generation company by IWAPSO

Content Provider	IEEE Xplore Digital Library
Author	Boonchuay, C. Ongsakul, W.
Copyright Year	2009
Description	Author affiliation: Energy Field of Study, Asian Institute of Technology (AIT), P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand (Boonchuay, C.; Ongsakul, W.)
Abstract	In this paper, an optimal bidding strategy for a generation company by the inertia weight approach particle swarm optimization (IWAPSO) is proposed. The expected profit maximization and risk (profit variance) minimization are combined into the objective function of the optimization problem. Nonconvex operating cost functions of thermal generation units and minimum up/down time constraints are formulated to find the optimal bid prices for multi-hourly trading in a uniform price spot market. The rivals' behavior is approximated through the Monte Carlo (MC) simulation. The proposed method based on the IWAPSO and MC simulation can provide the efficient set of bid prices which is the best combinations between expected profit and risk. The mean-standard deviation ratio (MSR) index is used to select the optimal risky bid prices. The proposed approach is a profitable tool for a producer who needs to compromise between expected profit and risk in spot market. Moreover, this approach can be applied to different market models.
Starting Page	1
Ending Page	6
File Size	127322
Page Count	6
File Format	PDF
ISBN	9781424422340
DOI	10.1109/PTC.2009.5281876
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-28
Publisher Place	Romania
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Power generation Particle swarm optimization Cost function Time factors Monte Carlo methods Risk management Cooling Production Electricity supply industry Aggregates optimal risky scenario Bidding strategy particle swarm optimization Monte Carlo simulation spot market uniform price risk assessment
Content Type	Text
Resource Type	Article

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