DocumentCode :
1260269
Title :
Fuel Resource Scheduling, Part III: The Short-Term Problem
Author :
Kumar, A.B.Ranjit ; Vemuri, S. ; Gibbs, L.A. ; Hackett, D.F. ; Eisenhauer, J.T.
Author_Institution :
Harris Controls and Composition Division, Melbourne, FL
Issue :
7
fYear :
1984
fDate :
7/1/1984 12:00:00 AM
Firstpage :
25
Lastpage :
26
Abstract :
The paper presents a method for optimum scheduling of fuels over a few days, subject to fuel supply limits, spanning different time periods, and unit operating constraints. Constraints over mixed and shared fuels, are also considered. Results for a 17 unit/17 contract test system over a two day study period are presented and discussed. Scheduling fuel resources, in the short term, to satisfy fuel supply and consumption constraints is a nontrivial task for planning and operating engineers of an electric utility. The complexity of the problem increases when one has to consider the fuel constraints over different time periods (hour, day, combination of days, etc.) simultaneously. When the (linear) fuel constraints are coupled with the linear and nonlinear operating constraints of the system the complexity of the scheduling problem becomes a mathematical challenge for the operation researchers and is beyond the reach of intuitive methods. The current techniques for planning the operation of generating units in a power system subject to operating and fuel supply constraints share the following common features. 1) Daily (or study period) fuel supply limits are either too broad to be constraining or so narrow that they can be specified as fixed amounts that must be consumed. Either daily limits or study period limits (but not both) can be specified in a given study. 2) All hourly fuel supply constraints are translated as hourly constraints on the capacity of individual units. 3) Price of the fuel to be used by a unit is known apriori.
Keywords :
Approximation methods; Biological system modeling; Constraint optimization; Contracts; Couplings; Dynamic scheduling; Fuels; Piecewise linear approximation; Power generation; Power industry; Power system planning; Resource management; Spinning; System testing; Time factors;
fLanguage :
English
Journal_Title :
Power Engineering Review, IEEE
Publisher :
ieee
ISSN :
0272-1724
Type :
jour
DOI :
10.1109/MPER.1984.5525862
Filename :
5525862
Link To Document :
بازگشت