الفهرس 
AcknowledgementOnly 14 pages are availabe for public view
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Abstract
present thesis introduces some novel approaches capable solving large size power systems networks reliability lems using normal size computers. These techniques are
ged to cope with networks with different criteria of ess. They also enable the network reliability to be essed in terms of load point indices and system al indices.The thesis presents three approaches which
applied in, the field of large-scale power system evaluation.
first approach is based on : tearing the network apart distinguishing certain branches, henceforth called -
branches, then solving the torn
rately. The torn networks are then reconnected and the ginal system reliability is evaluated.
recursive technique is used to include the effect of the tearing links upon the two joined nodes ilities and, in turn on the whole network nodes ilities. By this means the system nodes reliabilities
obtained according to loss of load probability
t=_rion der to establish the accuracy of the new technique,
results obtained have been compared with other
i able techniques. Excellent agreement is achieved with Ctto the loss of load probability at every load
over a wide range of network configurations.
novelty of the new approach lies in its ability to dle various levels of network contingencies in an Y. fast and exhaustive manner. Moreover this novel roach provides a very powerful tool in handling the -lem of planning.
proposed technique has been extended to take into cent the capacity constraints in power networks. rzducing the capacity constraint to each link has been eE ’:igated upon the load point reliability in various Lability test systems in this second approach. The ation of the capacity constraint has introduced an ent technique to handle the large and complex ric network reliability problems. Each load point :.:es have been calculated to give an insight into the of each link on the reliability of each node the actual network. The effect of joining the torn works with the tearing branches has been revealed by nina the change in the network capacity matrix,