Capacitor placement in distribution systems using artificial intelligent techniques

This paper undertakes the problem of optimal capacitor placement in a distribution system. The problem is how to optimally determine the locations to install capacitors, the types and sizes of capacitors to be installed and, during each load level, the control settings of these capacitors in order that a desired objective function is minimized while the load constraints, network constraints and operational constraints (e.g. voltage profile) at different load levels are satisfied. The problem is formulated as a combinatorial optimization problem with a nondifferentiable objective function. Four solution mythologies based on simulating annealing (SA), genetic algorithms (GA), tabu search (TS), and hybrid GA-SA algorithms are presented. The solution methodologies are preceded by a sensitivity analysis to select the candidate capacitor installation locations. The effect of nonlinear loads on the optimal solution is studied. The solution algorithms have been implemented into and tested on a 69-bus power system.