Chronological Monte Carlo-based assessment of distribution system reliability

• Autor(a) principal: Da Silva, Armando M. Leite
• Data de Publicação: 2006
• Outros Autores: Cassula, Agnelo M. [UNESP], Nascimento, Luiz C., Freire Jr., José C. [UNESP], Sacramento, Cleber E., Guimarães, Ana Carolina R.
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1109/PMAPS.2006.360423; http://hdl.handle.net/11449/69253
• topic: Distribution reliability; Markov chains; Monte Carlo simulation; Object-oriented programming; Canning; Computational efficiency; Computer programming languages; Cosmic ray detectors; Distributed parameter networks; Distribution of goods; Electric power distribution; Electric power systems; Electric power transmission networks; Laws and legislation; Local area networks; Monte Carlo methods; Object oriented programming; Power transmission; Probability; Pumps; Risk assessment; Unified Modeling Language; Applied (CO); Balance (weighting); case studies; Computational techniques; Customer services; distribution networks; Distribution system reliability; Distribution systems; Electric power utilities; Financial risks; In order; international conferences; Maximum continuous interruption duration (MCID); Monte Carlo (MC); Monte Carlo Simulation (MCS); Performance-based regulation (PBR); power systems; Probabilistic methods; Regulatory Authority (RA); Reliability index (RI); system reliability; Unified Modeling (UML); Probability distributions

Regulatory authorities in many countries, in order to maintain an acceptable balance between appropriate customer service qualities and costs, are introducing a performance-based regulation. These regulations impose penalties, and in some cases rewards, which introduce a component of financial risk to an electric power utility due to the uncertainty associated with preserving a specific level of system reliability. In Brazil, for instance, one of the reliability indices receiving special attention by the utilities is the Maximum Continuous Interruption Duration per customer (MCID). This paper describes a chronological Monte Carlo simulation approach to evaluate probability distributions of reliability indices, including the MCID, and the corresponding penalties. In order to get the desired efficiency, modern computational techniques are used for modeling (UML -Unified Modeling Language) as well as for programming (Object- Oriented Programming). Case studies on a simple distribution network and on real Brazilian distribution systems are presented and discussed. © Copyright KTH 2006.