Reliability evaluation and comparison for next-generation substation function based on IEC 61850 using Monte Carlo simulation

• Published in: 2013 1st International Conference on Communications, Signal Processing and Their Applications pp. 1 - 6
• Main Authors: Mekkanen, M., Virrankoski, R., Elmusrati, M., Antila, E.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.02.2013
• Subjects: Estimation; IEC61850; Monte Carlo methods; Monte Carlo simulation; Probability of failure; Protection and control function; Relaibility; Reliability; Substation automation; Substations; Switches; Topology
• ISBN: 1467328200; 9781467328203
• DOI: 10.1109/ICCSPA.2013.6487306

The traditional way to evaluate the system reliability or a probability of failure in the system is to use one of two basic approaches, direct analytical techniques or stochastic simulation. The emerging concept of Smart Grid requires advanced automation solutions for distributed electricity production and distribution. The automation system must fill the performance, availability and reliability requirements, including a probability of failure level under the specified limits. IEC61850 is a recent standard for electrical substation automation and it is also extended to the communication between substations. It provides interoperability in substation automation systems (SAS) consisting of devices by different vendors. This paper discusses about the evaluation of system reliability and the probability of failure existing in one protection intelligent electronic devices (IED), the evaluation of the general protection function and the breaker failure protection (BFP) function for practical small transmission substation T1-1. Different practical configurations are considered. A sequential Monte Carlo method is used to simulate the reliability and probability of failure. Comparison between analytical and simulation results is made by increasing the number of trails. Our result indicates how much the redundant ring architecture increases the reliability compared to the cascaded architecture. Applied Monte Carlo simulation method is also a flexible solution that has the ability to change, expand input data and include different parameters without a need to change the underlying software.