Overhead Transmissions Lines (OTL) are outdoor systems, which can easily be affected by weather fluctuation. In the worst-case scenario, temperature variation, horizontal wind and vertical ice-loading make the value of sag, tension and conductor (cable) length to vary between low to high extremes. The temperature and cable length variations have an effect on the resistance of the OTL. This variation leads to a variable voltage drop, which is mostly considered with load variation. In order to calculate resultant loading, sag, tension, cable length and resistances of an OTL, an uncertainty model based on Standard Affine Arithmetic (SAA) is proposed and the result is compared with the probabilistic Monte Carlo (MC) and Interval Arithmetic (IA) approaches. Based on the test results, the SAA based algorithm gives slightly conservative bound than the IA and MC approaches.

The depletion of fossil fuel is driving the world towards the application of renewable energy sources. However, their intermittent nature, in addition to load variation and transmission line sag-tension change due to temperature, is a great deal of problems for reliable power delivery. Without a reliable power delivery, power generation is just a waste of resources. A reliable power delivery can be achieved when the best and the worst case steady state information of a power system network is known to plan and control accordingly. If a system is affected by the presence of uncertainty, a deterministic load flow analysis fails to provide the worst-case load flow result in a single analysis. As a result, a load flow analysis considering the presence of uncertainty is mandatory. On this paper, a novel complex affine arithmetic (AA) based load flow analysis in the presence of generation and load uncertainties is proposed. The proposed approach is tested on an IEEE bus systems and compared with Monte Carlo approach. The proposed approach convergence faster than the Monte Carlo based method and it is slightly conservative.