Energy Systems

, Volume 10, Issue 2, pp 385–414 | Cite as

An open source tool for reliability evaluation of distribution systems with renewable generators

  • S. Conti
  • S. A. RizzoEmail author
Original Paper


Future smart electrical distribution systems could adopt switch remote control and advanced automation systems to operate in autonomous mode (islanding) some portions of the network in order to improve system reliability. In this perspective, a free code able to assess distribution reliability by using analytical or Monte Carlo simulation methods accounting for intentional islanding operation is presented. An effective network representation and data structure, which have led up to the implementation of two automatic and general procedures, are proposed. The procedures share common underlying information in order to speed up calculation. A further merit of the tool is that it enables the user to quickly and simply create the input files. The reliability indices of three distribution networks have been computed by means of the developed software for different scenarios, that is when island mode of operation is not permitted by regulation, and when island mode is permitted (intentional islanding) with the local load either partially or totally supplied by renewable distributed generators. The free code, the input files and the results related to the considered networks are available online at:


Renewable distributed generation Distribution system reliability Open source software Microgrids Power system simulation Smart grids 


\(\hbox {CAIDI}\)

Customer average interruption duration index

\(\hbox {CBS}\)

Circuit breaker + sectionalizer

\(\hbox {DG}\)

Distributed generator

\(\hbox {EDN}\)

Electrical distribution network

\(\hbox {LP}\)

Load point

\(\hbox {MCS}\)

Monte Carlo simulation (RMCS Random MCS-SMCS Random MCS)

\(\hbox {MTBF}\)

Mean time between failures

\(\hbox {MTTF}\)

Mean time to failure

\(\hbox {MTTR}\)

Mean time to repair

\(\hbox {MV}\)

Medium voltage

\(\hbox {NB}\)

Number of branches

\(\hbox {PoA}\)

Probability of adequacy

\(\hbox {PS}\)

Primary substation

\(\hbox {SB}\)

Source branch

\(\hbox {SN}\)

Source node

\(\hbox {SAIDI}\)

System average interruption duration index

\(\hbox {SAIFI}\)

System average interruption frequency index

\(\hbox {SOB}\)

Set of branches (they are the branches in a segment)

\(\hbox {SON}\)

Set of nodes (they are the nodes in a segment)


Branch failure frequency


Number of customers


Time to be available (it is the time to reconnect the DG units disconnected due to a fault in the network)


Branch repair time (set to MTTR)


Sectionalizer switching time


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  1. 1.Department of Electrical, Electronics and Computer EngineeringUniversity of CataniaCataniaItaly

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