In recent years, power systems have been pushed to operate above their limits due to the increase in the demand for energy supply and its usage. This increase is accompanied by various kinds of obstructions in power transmission systems. A power system is said to be secured when it is free from danger or risk. Power systems security deals with the ability of the system to withstand any contingencies without any consequences. Contingencies are potentially harmful disturbances which occur during the steady state operation of a power system. Load flow constitutes the most important study in a power system for planning, operation, and expansion. Contingency selection is performed by calculating two kinds of performance indices; an active performance index (PIP) and reactive power performance index (PIV) for a single transmission line outage. In this paper, with the help of the Newton Raphson method, the PIP and PIV were calculated with DIgSILENT Power Factory simulation software and contingency ranking was performed. Based on the load flow results and performance indexes, the Ethiopian Electric Power (EEP) North-West region network is recommended for an upgrade or the reactive power or series compensators should be constructed on the riskiest lines and substations.

For reasons of reliability, stability, safety and economy, controlling and monitoring the response of structures during the time of use, either permanently or temporally, is of increasing importance. Experimental methods enable in-situ measuring deformations of any kind of structures and enable drawing conclusions over the actual state of the structures. However, to obtain reliable knowledge of the real internal conditions like the strength of materials and the actual stress-state, as well as of their changes over time, caused by ageing, fatigue and environmental influences, always an inverse problem must be solved. That requires special mathematical algorithms. Especially for time-depending material response it might be quite important to know the material parameters at any time and furthermore the internal stress-state also. Therefore, a method will be presented to solve the inverse problem of parameter identification with reference to linear visco-elastic materials.