Outages in the electric grid can be costly for society. Because of this, reliability is one of the parameters used to regulate network companies. Reliability in electrical grids can be measured with SAIDI, system average interruption duration index, which for Fortum Distribution has increased in Stockholm’s distribution network (11 kV) in the early 2000’s. By using outage data for Stockholm from 2011-2013, sets of parameters to be used for reliability calculations in the network information program Tekla NIS were derived. Two different options for investment were then analysed: changing old cables with high fault frequencies, and installing automatic switching in distribution substations. These options were also analysed in a simplified model built in Microsoft Excel. The model calculates the reliability of Stockholm’s distribution network using Markov chains and the network’s average line from a transmission substation’s feeder. The Excel model is faster than Tekla NIS but is limited and less detailed, however the results from Tekla NIS and the Excel model were found to be almost equivalent. The priority for reliability investments in Stockholm should be to change old cables of the type FCJJ since it increases the fault frequencies in the network, while an ageing network decreases the grid fees Fortum Distribution can charge. Simplifications and assumptions, due to insufficient outage data and some problems with Tekla NIS, had to be made when deriving parameters for reliability calculations in both Tekla NIS and the Excel model. However, Tekla NIS can be used to incorporate reliability analysis in network planning, but since Fortum Distribution currently only uses it sparsely, further testing and analysis of the programme is recommended if the usage is to increase. The Excel model can be used for making fast and rough estimates of the result of the two analysed options of investment. / <p>I den tillgängliga fulltexten är tre figurer med tillhörande information i kapitel 2.4 borttagna från originalrapporten efter önskemål från samarbetspartner.</p>

I detta examensarbete har en tillförlitlighetsmetod tagits fram som väger samman kostnadspåverkande faktorer för investeringar och underhåll i eldistributionssystem med kostnader förknippade med avbrott. Syftet med metoden är att möjliggöra för nätplanerare och projektörer att jämföra olika investeringsalternativ för att kunna kostnadseffektivisera investeringarna i eldistributionssystem. Med tillförlitlighetsanalys kan den förväntade avbrottstiden i systemets uttagspunkter beräknas. Kopplas en kostnad till den förväntade avbrottstiden i uttagspunkterna kan den förväntade avbrottskostnaden för distributionssystemet beräknas.   Syftet med simuleringarna har varit att undersöka om det går att minimera den totala kostnaden, investeringskostnader samt förväntade avbrottskostnad, genom slumpvisa investeringar i systemets ledningssektioner. Simuleringarna har genomförts på ett fiktivt mindre system. Systemet möjliggör analys av resultaten, men är ändå tillräckligt komplext för att påvisa problematik som kan uppstå. Simuleringarna visar att den framtagna metoden är robust och fungerar på önskat vis. Det visade sig också att simuleringstiden, även med ett stort antal slumpvisa investeringstillfällen, är kort vilket gör att modellen även kan användas för mer komplexa nät. / This MSc project develops a method that combines factors that affect the investment and maintenance costs in electrical power systems with costs associated with outage. This gives the system planner an opportunity to compare different alternatives for investments to receive a low total cost. Using system reliability analysis the outage time for the load points in the system can be decided. If the expected outage time is associated with a cost, it is possible to calculate the expected outage cost for the system.   The purpose of the simulations has been to examine if it is possible to minimize the total cost by doing randomized investments on power lines in the system. The simulations are carried out on a fictional, small system. Because of the specific design, it is easy to analyze results but also complex enough to show problems that can occur in the system. The simulations show that the model is robust and the expected results were accomplished. The simulations also showed that, even for a large amount of events, the time for the simulation is short. This shows that the model is suitable also for larger systems.