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The advance in remote sensing techniques, especially the development of LiDAR scanning systems, allowed the development of new methods for power line corridor surveys using a digital model of the powerline and its surroundings. The advanced diagnostic techniques based on the acquired conductor geometry recalculation to extreme operating and climatic conditions were proposed using this digital model. Although the recalculation process is relatively easy and straightforward, the uncertainties of input parameters used for the recalculation can significantly compromise such recalculation accuracy. This paper presents a systematic analysis of the accuracy of the recalculation affected by the inaccuracies of the conductor state equation input variables. The sensitivity of the recalculation to the inaccuracy of five basic input parameters was tested (initial temperature and mechanical tension, elasticity modulus, specific gravity load and tower span) by comparing the conductor sag values when input parameters were affected by a specific inaccuracy with an ideal sag-tension table. The presented tests clearly showed that the sag recalculation inaccuracy must be taken into account during the safety assessment process, as the sag deviation can, in some cases, reach values comparable to the minimal clearance distances specified in the technical standards.

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This article deals with the assessment of the reliability of sensitive equipment due to voltage sags. The most frequent problems of power quality are voltage sags. Equipment that cannot withstand short-term voltage sag is defined as sensitive device. Sensitivity of such equipment can be described by the voltage-tolerance curves. A device (generator) to generate voltage sags (also interruptions) with duration at least 1 ms has been designed and developed for this purpose. Equipment sensitive to voltage sags was tested using this generator. Overall, five types of sensitive equipment were tested: personal computers, fluorescent lamps, drives with speed control, programmable logic controllers, and contactors. The measured sensitivity curves of these devices have been used to determine the number of trips (failures) due to voltage sags. Two probabilistic methods (general probability method and cumulative probability method) to determine probability of equipment failure occurrence are used. These methods were applied to real node in the distribution system with its actual performance of voltage sags/swells. The calculations also contain different levels of sensitivity of the sensitive equipment.

Photovoltaic (PV) arrays are used in many applications such as water heating, battery charging, hybrid vehicles and grid connected photovoltaic power plants. Their main disadvantage is that their output strongly depends on weather conditions, mainly on a solar irradiance and temperature, thus influencing the operation of each system they feed. Since the changes of PV production could be very fast, it is necessary to use dynamic modelling to evaluate PV system's behavior during these changes. This could be quite challenging, especially if the application is modelled and analyzed from longer-term point of view. This paper describes partial results achieved during the process of building such a model. Simulation models of PV array and DC boost converter with MPPT controller created in software Ptolemy II by using synchronous data flow and finite state machine domain will be presented and evaluated.Index Terms--Finite state machine, mathematical model, maximum power point trackers, photovoltaic systems.