DocumentCode
2989422
Title
Optimal capacitor placement using deterministic and genetic algorithms
Author
Delfanti, M. ; Granelli, G.P. ; Marannino, P. ; Montagna, M.
Author_Institution
Dipt. di Ingegneria Elettrica, Pavia Univ., Italy
fYear
1999
fDate
36342
Firstpage
331
Lastpage
336
Abstract
A procedure for solving the power capacitor placement problem is presented. The objective is to determine the minimum investment required to satisfy suitable reactive constraints. Due to the discrete nature of reactive compensation devices, optimal capacitor placement leads to a nonlinear programming problem with mixed (discrete and continuous) variables. It is solved with an iterative algorithm based on successive linearizations of the original nonlinear model. The mixed integer linear programming problem to be solved at each iteration of the procedure is tackled by applying both a deterministic method (branch and bound) and genetic algorithm techniques. A hybrid procedure, aiming to exploit the best features of both algorithms is also considered. The proposed procedures are tested and compared with reference to a small CIGRE system and two actual networks derived from the Italian transmission and distribution system
Keywords
compensation; deterministic algorithms; genetic algorithms; linear programming; power capacitors; power system planning; reactive power; Italy; deterministic algorithms; genetic algorithms; iterative algorithm; mixed integer linear programming problem; nonlinear programming problem; power capacitor placement optimisation; power system planning; reactive constraints; successive linearization; Capacitors; Genetic algorithms; IEEE members; Investments; Iterative algorithms; Linear programming; Mixed integer linear programming; Power system planning; Reactive power; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Industry Computer Applications, 1999. PICA '99. Proceedings of the 21st 1999 IEEE International Conference
Conference_Location
Santa Clara, CA
Print_ISBN
0-7803-5478-8
Type
conf
DOI
10.1109/PICA.1999.779515
Filename
779515
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