A Nodal Transmission Pricing Model based on Newly Developed Expressions of Real and Reactive Power Marginal Prices in Competitive Electricity Markets

In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.

• Ashish Saini
• A.K. Saxena

• Deregulation
• electricity markets
• nodal pricing
• social welfare function
• short run marginal cost.

[1] Thilo Krause, Evaluation of Transmission Pricing methods for
Liberalized Markets-A Literature Survey, Internal Report, Z├╝rich,
EEH_PSL_2003_001: EEH Power Systems Laboratory, 2003.
[2] F.C. Schweppe, M.C., Caramanis, R.D. Tabors & R.E. Bohn, Spot
Pricing of Electricity, Boston, MA: Kluwer, 1988.
[3] M.L. Baughman & S.N. Siddiqi, "Real time pricing of reactive power:
theory and case study results", IEEE Trans. Power Systems, vol. 6, pp.
23-29, 1991.
[4] Y.Z. Li and A.K. David, "Wheeling rates of reactive flow under
marginal cost theory", IEEE Trans. Power Systems, vol. 10, No. 3, 1993.
[5] A.A. El-Keib, & X. Ma, "Calculating short-run marginal costs of active
and reactive power production", IEEE Trans. Power Systems, vol. 12,
pp. 559-565, 1997.
[6] D. Chattopadhyay, K. Bhattacharaya & J. Parikh, "Optimal Reactive
Power Planning and its Spot-Pricing: Integrated Approach", IEEE Trans.
Power Systems, vol. 10, pp. 2014-2019, 1995.
[7] S. Hao & A. Papalexopoulos, "Reactive power pricing and
management", IEEE Trans. Power Systems, vol. 12, pp. 95-104, 1997.
[8] Y. Dai , Y.X. Ni, C.M. Shen, F.S. Wen, Z.X. Han & Felix F. Wu, "A
study of reactive power marginal price in electricity market", Electric
Power Systems Research, vol. 57, pp. 41-48, 2001.
[9] Ashish Saini, D.K. Chaturvedi & A.K. Saxena, "Optimal Power Flow
Solution: A GA-Fuzzy System Approach", International Journal of
Emerging Electric Power Systems, vol. 5, Issue 2, Article 1, 2006.
[10] D. Galiana Francisco & Mark Phelan, "Allocation of Transactions
Losses to Bilateral Contracts in a Competitive Environment", IEEE
Trans. Power Systems, vol. 15, pp. 143-150, 2000.
[11] J.W. Lamont & R. Fu, "Cost analysis of reactive power support", IEEE
Trans. Power Systems, vol. 14, pp. 890-898, 1999.
[12] J.Y. Choi, S. Rim, & J. Park, "Optimal real time pricing of real and
reactive powers", IEEE Trans. Power Systems, vol. 13, pp. 1226-1231,
1998.
[13] Ashish Saini, D.K. Chaturvedi & A.K. Saxena, "Congestion
Management Methods based on GA-Fuzzy OPF under Deregulated
Environment", International Conference on Power Systems, Bangalore,
12-14th Dec., 2007.