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|dc.description.abstract||Distribution system is one from which the power is distributed to various users through feeders, distributors and service mains. Feeders are conductors of large current carrying capacity, carrying the current in bulk to the feeding points. Conductor is often the biggest contributor to distribution system losses. Economic conductor sizing is therefore of major importance. If a conductor is loaded up to or near its thermal rating, the losses will be increased. Therefore, line conductors are loaded below their thermal limit. The power loss is significantly high in distribution systems because of lower voltages and higher currents, when compared to that in high voltage transmission systems. Studies have indicated that as much as 13% of total power generated is consumed as I2R losses in distribution level. Reduction of total loss in distribution systems is very essential to improve the overall efficiency of power delivery. In this thesis work, an attempt has been made for selecting optimal size of branch conductor of radial distribution feeders based on PSO (Particle Swarm Optimization). The capital investment in laying distribution network lines accounts for a considerable fraction of total capital, investment. The problem is posed as an optimization problem with an objective to minimize the overall cost of annual energy losses and depreciation on the cost of conductors. The conductor, which is determined by this method will maintain acceptable voltage levels of the radial distribution system. Besides, it gives maximum saving in the capital cost of conducting material and cost of energy losses. The proposed method also shows that only proper selection of optimum branch conductors reduces losses instead of using uniform conductors. The effectiveness of the proposed method is demonstrated through an example.||en|
|dc.subject||Radial Distribution Network||en|
|dc.title||An Efficient Method for Selection of Optimal Conductors in Planning of Radial Distribution Network||en|
|Appears in Collections:||Masters Theses@EIED|
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