Cost Allocation of SPS Service Using Cooperative Game Theory

Power systems planning and operations are usually defined by N-1 criterion. This means that in an event of a single contingency, no remaining connected transmission elements will be thermally overloaded, no bus voltage will be outside of acceptable limits, no system interface limit is violated, and system stability is maintained.

Special Protection Systems or SPS are widely utilized for increasing power transfer in transmission systems at the same time respecting security constraints [1]. SPS applications usually are generation rejection schemes (GRS), line/transformer transfer tripping and load shedding. GRS are designed to mitigate overloading of a transmission line or lines after an N-1 contingency near the vicinity of a generating plant or are employed to arrest increasing dynamic oscillation which may lead to unstable system conditions. Without the GRS, generation output is curtailed to satisfy the N-1 security criterion. With the GRS, the output of the generation is increased thereby increasing power transfer. Further, GRS also mitigates or delays the possibility of transmission expansion or investment due to transmission capacity constraints.

In a locational marginal pricing based electricity market, curtailment of generation (without GRS), specifically of a cheap generation due to the security N-1 criterion can be considered as transmission congestion. Transmission capacity limitations impede the generation output thereby decreasing the profit opportunity of the generation company (GenCo).  If a GRS is installed for this GenCo, the output of the GenCo is increased and thus there is a clear benefit for the GenCo in terms of profit. When transfer capability is limited, without GRS, the profit of a transmission owner (TO) is decreased due to less power wheeling charges. With the GRS, wheeling charges increase as a consequence of the added power transfer. This premise is the same with the electricity system and market administrator, called independent system operator (ISO), since the ISO charges for cost-based services including scheduling, system control and dispatch.  For the demand side, when generation output is curtailed due to congestion, without GRS, the resulting nodal prices at the demand’s location maybe higher than when a GRS is in place to increase generation output from a cheap generation.

GRS installations have embedded cost and actual service cost [3]. Since electricity market participants have various benefits in having a GRS installation, the cost of the SPS/GRS service must be allocated among the participants. Cooperative game theory [4-5] can be utilized in allocating fair cost on the beneficiaries of the SPS service.

The PJM 5 bus test system [6], shown Figure 1, is to be utilized as an example for the application of cooperative game theory in sharing the SPS service cost among power system organizations.

Figure 1. PJM 5 bus test system.

References:

[1]     W. Fu, S. Zhao, J. D. McCalley, V. Vittal, N. Abi-Samra, “Risk Assessment for Special Protection Systems,” IEEE Transactions on Power Systems, vol. 17, no. 1, pp. 63-72. February 2002. Available: home.eng.iastate.edu/~JDM/WebJournalPapers/RiskAssessentSPS.pdf

[2]     Ancillary Services Presentation. Available: http://www.nyiso.com/public/webdocs/services/market_training/workshops_courses/nymoc/Ancillary_Services.pdf

[3]     J. K. Earle, “Functional unbundling of special protection systems as a required interconnected operating service in a deregulated environment,” MSEE Thesis, University of New Brunswick, 1997. Available: dspace.hil.unb.ca:8080/handle/1882/42522

[4]     H. Singh, “Introduction to Game Theory and Its Application in Electric Power Markets,” IEEE Computer Applications in Power, IEEE Computer Application in Power, vol.12, no.2, pp. 18-20, 22, Oct.1999.

[5]     J. Mepokee, D. Enke, B. Chowdhury, “Cost allocation for transmission investment using agent-based game theory,” International Conference on Probabilistic Methods Applied to Power Systems, Iowa State University, Ames, Iowa, September 12-16, 2004.

[6]     L. Fangxing, B. Rui, "Small Test Systems for Power System Economic Studies," Proceedings of the 2010 IEEE PES General Meeting, Minneapolis, MN, July 25-29, 2010.