Bidding information to generate bidding strategies for LaGrangian relaxation-based auctions

LaGrangian relaxation (LR) is used as an auction method for bidding in a deregulated environment. Identical or similar units can prevent LR from finding the optimal solution when only one of the units should be committed. If many units are similar, LR may have trouble selecting some subset of them for the optimal solution. A unique feasible solution may thus not be found. This leads to inequity among the unit(s) not selected and may result in less revenue for one or more competitors. Because the dispatcher has to use heuristic selection, there is no 'fair' solution to these problems. This paper focuses on how to change unit data to obtain an advantage while using LR as an auction method. The authors suggest alternative strategies based on previously published problems with selection by unit commitment and subsequent dispatch by economics. Sensitivity analysis results demonstrate the method for finding the percentage difference between units to affect the solution. (C) 1999 Elsevier Science S.A. All rights reserved.