Published January 2010 | Version v1
Journal article

The effect of contingency analysis on the nodal prices in the day-ahead market

  • 1. Fox School of Business and Management, Temple University, Philadelphia, PA 19122 (United States)
  • 2. 1416 Berkshire Dr. Bensalem, PA 19020 (United States)
  • 3. National Science Foundation, 4201 Wilson Boulevard, Arlington, VA 22230 (United States)
  • 4. Cacak College of Engineering, Univeristity of Kragujevac, Svetog Save 65, 32000 Cacak (Serbia)
  • 5. College of Engineering, Northeastern University, Boston, MA (United States)

Description

We look at the effect of modeling branch-outage contingencies on locational marginal prices. To model contingencies in the day-ahead auction, we formulate a two-stage stochastic program. Rather than follow the current practice of including a list of possible contingencies that must be satisfied, we incorporate a larger set of contingencies in the model and allow contingencies to result in load reductions/outages at a cost. The model can be used and interpreted in two ways. One is to look at the tradeoff between reliability and outage costs. Another is to consider the load losses resulting from a contingency to be consumer offers of load reductions in response to line outages as part of the day-ahead auction. In analyzing the model structure, we find that the prices in the model closer in definition to those currently used in the day-ahead auction do not maximize expected surplus because the day-ahead auction produces prices that assume shortages will never occur. This raises issues with the design of auctions with important stochastic elements in the market. We present results for a 68-node grid with 86 branches (lines and transformers) to illustrate how prices and expected values change as the costs of outages are varied. (author)

Availability note (English)

Available from Available from: http://dx.doi.org/10.1016/j.enpol.2009.08.065

Additional details

Identifiers

Publishing Information

Journal Title
Energy Policy
Journal Volume
38
Journal Issue
1
Journal Page Range
p. 141-150
ISSN
0301-4215
CODEN
ENPYAC

INIS

Country of Publication
United Kingdom
Country of Input or Organization
United Kingdom
INIS RN
41026842
Subject category
S29: ENERGY PLANNING, POLICY AND ECONOMY;
Descriptors DEI
COST; ELECTRICITY; MARKET; OUTAGES; PRICES; RELIABILITY; SHORTAGES; SIMULATION; STOCHASTIC PROCESSES

Optional Information

Notes
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