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Impact of Market Uncertainty on Congestion Revenue Right Valuation
Authors:Haibin Sun  Shi-Jie Deng  A P Sakis Meliopoulos
Affiliation:1PhD Student, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332. E-mail: hsun@isye.gatech.edu
2Assistant Professor, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332. E-mail: deng@isye.gatech.edu
3Professor, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332. E-mail: sakis.meliopoulos@ece.gatech.edu
Abstract:Congestion revenue rights (CRRs) are property rights that entitle and/or obligate their holders to receive specified (possibly negative) congestion revenues. They provide price certainty for transmission customers who need to purchase open access transmission service. Auctions and bilateral transactions allocate CRRs to market participants who value the transmission rights the most. If valued correctly, CRRs would yield market signals required in valuing congested transmission facilities and inducing capital investment in the transmission sector. Financial transmission rights (FTRs) and flowgate rights (FGRs) are two specific forms of CRRs. This paper presents a simulation based approach for valuing FTRs and FGRs. Using the proposed approach, we derive the probabilistic characteristics of FTR and FGR values under market uncertainties resulting from fluctuating system loads, varying fuel prices, and other system contingencies such as unplanned transmission circuit and generator outages. A theoretical framework consisting of a multilateral-transaction model, a nonconforming electric load model, and CRR valuation models under different market structures incorporating market aforementioned uncertainties is proposed. A Monte Carlo simulation procedure is employed to obtain the distributions of FTR and FGR values. Numerical implementation of the proposed approach is illustrated on a sample test system.
Keywords:Financial management  Monte Carlo method  Revenues  Probability distribution  
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