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.