Selection of Surge Protection Module Components for Communication Lines Using a Genetic Algorithm

Abstract

Among a variety of problems with communication lines, the faults of surge protection modules in railway applications have a significant impact on the transmission line availability, especially if the devices are located in lightning-prone areas or other high-energy exposure areas, such as voltages or current changes. An advanced optimization of the surge protection module is proposed together with its verification, based on simulated waveforms for components and their limitations (e.g., power, peak power, maximum voltages, maximum currents, etc.). It allows for gathering information about the safety margin for each parameter of the components. This can be used to manage the probability of damage to the protection module. The authors have shown the power distribution during exposure that should be considered while developing new devices for railway transportation industry.

Energy distribution on surge arrester elements selected by genetic algorithm in railway systems

“…It is possible to find articles presenting the need for performing device operation simulation before testing [11] in the relevant literature. A schematic diagram and an advance analysis of GA in terms of designing a protection module in railway industry is presented in [12], but some improvements are possible. The question is what will happen when the disturbance does not reach sparkover voltage, i.e.…”

“…The goal of fitness function is to find a suboptimal specification of a protection module with preselected components and avoid critical overload parameters (voltages, currents and power defined by a manufacturer for a specific component). Therefore, the fitness function evaluates the solution provided by GA [12] and takes the voltages, currents and power dissipation on an element (𝑀 𝑘 𝑖 ) into account, compares the obtained values to maximum conditions (maximum stress in terms of voltage/current/power 𝑀 ̂𝑘 𝑖 ). The denominator has a valuation parameter (𝛽 𝑘 𝑖 ) in order to limit any damage to the most critical elements.…”

“…the configuration of the GA' and stopping criteria, parameters description, algorithm flow etc. are presented in [12].…”

The Effect of Cable Aging on Surge Arresters Designed by Genetic Algorithm

“…A detailed discussion of the signal shape in the time domain and the required response time of the analyzed circuit is presented in ref. [23]. Based on this, the time of surge arrester behavior verification was set to 300 µs.…”

“…A schematic diagram and a preliminary analysis of GA in terms of the development of a surge arrester module in the railway environment are shown in [23], but some modifications are needed. As a result of the new assumptions, the goal functions have been updated with the following components: an additional test case (when a gas discharge tube-GDT is not involved), a part that optimizes the number in the resistor groups, and limiting the total volume of resistance in the surge arrester.…”