الفهرس 
Introduction to power systemOnly 14 pages are availabe for public view
 |  | from | 163 |  |  |
| | | from | 163 | | |
Abstract
Distributed generation (DG) has been gaining increasing importance in the last decade due to economic and technical reasons. There are many issues to be considered for the interconnection of DGs to the distribution network such as the sizing and siting of the DG units. The problem of the optimal sizing and siting of DG has taken top priority as they affect the distribution system operation especially the power losses and the voltage profile.
This dissertation focuses on developing a software program to perform an unbalanced power flow analysis of radial distribution systems. The algorithm that utilizes the backward forward sweep method is implemented in MATLAB and tested on the IEEE 37 nodes feeder. The distributed generator is modeled as PV (voltage controlled) node with the ability to be converted to PQ (constant power factor) node in case of the reactive power limits violation. The voltage profile and the feeder currents obtained from the developed software are compared with the previous results to validate the developed software.
This thesis also discusses the impact of distributed generation penetration on the distribution system operation. The optimal size and location of the DG unit are obtained from the perspective of the active power losses at different positive sequence voltages with the consideration of the feeder branches thermal capacity limits. The branch currents variation with varying DG penetration is studied. Also a comparison is done between one DG placed at the optimal location and two DGs placed at well selected nodes.
Moreover, a heuristic approach to determine the optimal size and location of DG under predetermined power loss or voltage regulation is suggested. The results obtained from this approach strongly support the results obtained from the developed power flow software. The proposed DG optimization techniques in this thesis significantly reduce the search efforts for the optimal solution attainment.