DocumentCode :
1725513
Title :
Systematical determination of load flow cases for power system planning
Author :
Rechberger, G. ; Renner, H. ; Gaun, A.
Author_Institution :
Inst. of Electr. Power Syst., Univ. of Technol., Graz, Austria
fYear :
2009
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents a novel method to determine a minimum number of representative load flow cases with load and generation data in a meshed transmission grid, which cover all critical power line loading situations in a given time frame. Measured active and reactive line loading data obtained from SCADA are the basic data input for this method. In order to find the optimum number of load flow cases a heuristic search algorithm in combination with a genetic optimization algorithm is used. The comparison of the required load flow cases with conventional load situations e.g. peak load or peak generation show, that conventional load flow cases do not cover all critical power line loading situations. Load flow cases determined with the presented method give an objective and representative picture of the expected situations and can be used for power system planning in the view of increasing demand and new generation capacity installations.
Keywords :
SCADA systems; genetic algorithms; load flow; power cables; power grids; power system planning; SCADA; generation capacity installations; genetic optimization algorithm; heuristic search algorithm; load flow; meshed transmission grid; power line loading situations; power system planning; reactive line loading data; Electric variables measurement; Fluid flow measurement; Heuristic algorithms; Load flow; Power generation; Power measurement; Power system measurements; Power system planning; Reactive power; Time measurement; genetic algorithm; load flow case optimization; power flow measurement; power system planning; set of load flow cases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
PowerTech, 2009 IEEE Bucharest
Conference_Location :
Bucharest
Print_ISBN :
978-1-4244-2234-0
Electronic_ISBN :
978-1-4244-2235-7
Type :
conf
DOI :
10.1109/PTC.2009.5282217
Filename :
5282217
Link To Document :
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