Abstract
Optimal Capacitor Placement (OCP) determines the locations, the size and the control settings of these capacitors during each load level of a three-phase distribution system. That will reduce peak power and energy losses and minimise the investment costs and installation of the capacitor banks. The optimal solution is obtained by testing various combinations of capacitor banks and candidate nodes and the distribution system and calculating the resultant savings. The capacitor placement problem is a combinational optimisation problem having an objective function composed of energy losses and capacitor bank installation costs subject to the load constraints, network constraints and operational constraints at different load levels. OCP seeks to maximise the net savings resulting from the reduction in power and energy losses less the total costs of capacitors. An Artificial Intelligence (A.I.) based Genetic Algorithm (G.A.) has been used to solve the OCP problem. The proposed method allows the modelling of loads of different power factors for other portions of the power distribution system. The solution algorithm has been implemented and tested on a ten bus power distribution system, and the simulation results of the proposed algorithm are well executed.
Highlights
The mechanical title storage of electrical energy; indicated that the project deals with the concept of transformation and storage of points from one form to another form such as automatic to the electrical state of energies
The mechanical input devices produced the energy with the help of giving some external kinetic energies
The primary concept of this procedure was the generation of a hand-powered input mechanism
Summary
The mechanical title storage of electrical energy; indicated that the project deals with the concept of transformation and storage of points from one form to another form such as automatic to the electrical state of energies. Described in windup products such as windup radio and windup torch, which stores mechanical energy in a spring and, when it is released, will power an electrical generator [Kermit, 1989]. The battery storage system was inefficient since its storage capacity was not constant. The primary purposes of the project were improving the energy storage system for much more time, reducing
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