Evaluation of smart technology for the improvement of reliability in a power distribution system.

Abstract

Electricity distribution networks are susceptible to random faults. On occurrence of a fault the upstream breaker on the faulty section trips. This leads to supply interruption to all customers connected to that affected section. Depending on the network configuration, opening and closing of breakers to try and restore supply to unaffected sections does take some time. This dissertation evaluates the application of selected smart technologies with the aim of improving the reliability of Eskom’s medium voltage (MV) networks. The intent is to reduce the outage duration, frequency of outages, maintenance costs, and operational expenditure while improving overall system performance. The reliability of a distribution system depends on a number of factors including the location (urban or rural), environment, the type of system and the type equipment installed. Factors that affect the customer supply availability include the failure rate of equipment and the duration of an outage. The outcome of the application of smart technology on the MV network will influence the availability of customer supply as the technology could not only be used to reduce the failure rate of the system but also decrease the time spent on fault finding and maintenance due to greater visibility system wide. Historical and predictive approaches are the two power system reliability assessments that are predominantly used. Both approaches are applied whereby expected performance is modelled, given the specific network topology, past performance, customer numbers, operating environment, etc. A number of network components including transformers, lines, isolators, and fuses are used and applied in a systematic manner to calculate the expected downtime experienced by the customer supplied on different connections of the network with different smart technology interventions. To achieve this, a methodology is developed and verified by comparing the calculated results with DigSilent PowerFactory simulations using a few selected samples of the existing networks from the KwaZulu Natal Operating Unit (KZN OU). The application of smart technology has confirmed an improvement on overall outage duration while improving system performance.