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Rtool Project

To stay in business, organizations must develop and maintain a Value Proposition that is compelling, whether you are a high-volume or a low-volume provider of products or services. Customers expect to receive products that work correctly for long as well as also hope continuous delivering of contracted services. Over the last decade, dependability issues have become a critical aspect of that proposition.

If purchased products fail to meet customers’ expectations or are constantly under repairing, replacement of such products would undoubtedly be from a different manufacturer. The same could assert to service providing organizations, since non-availability of contracted service may have economic severe and even catastrophic consequences. Hence, market share will undoubtedly be lost to an alternative provider, and the respective value related to service or product delivered might be drastically affected.

The successful implementation of dependable systems encompasses several aspects within an organization: from business infrastructure to continuous personal, institutional capacity programs; from quality assurance management methods to tools and models for evaluation of quality issues related to the products or services delivered. Nevertheless, the return of such investment is immeasurable, since it might mean the real permanence of the organization in the market.

One particularly sensitive area in which the dependability issue is of particular relevance is related to energy companies. Electric dependability is affected by all four segments of the electricity value chain: generation, transmission, distribution, and end-use. Concerning electronic communication, reliability, as well as availability, are enhanced when additional lines are added to the grid, proper maintenance occurs promptly, and when grid operators can make adjustments, in real-time, to address fluctuations in system conditions, particularly during periods of peak demand.

Dependability evaluation may be carried out through either measuring or considering the system’s models. However, in many situations modeling is the method of choice either because the system might not yet exist or due to the inherent complexity of creating specific scenarios under which the system should be evaluated.

According to the Brazilian Law number 9.991, the energy power companies must annually apply at least 1% of their operating profits in R&D to the Brazilian electric sector. The Brazilian Electric System National Operator (ONS) started its activities in 1998 aiming to control the transmission grid throughout the country. Among the ONS’s assignments, we may highlight the grid enhancement and transmission system control as well as monitoring energy quality levels supplied by the power companies. The Electric Energy Service Regulation Agency (ANEEL) is an autonomous entity associated to Energy Ministry that regulates and appraises the Brazilian electric energy generation, transmission, distribution, and selling as well as is responsible for conflict mediation between interested agents. The ANEEL has defined 99.98% as the minimal availability service level that energy companies should provide to their customers.

The development of advanced technologies, methods, and tools for dependability evaluation are fundamental for allowing the analysis of energy reliability and availability service levels provided by energy companies. This work depicts part of an R&D project applied to the electric sector that was supported by the Brazilian govern. This project aimed at proposing a methodology for dependability evaluation of the communication infrastructure of the electrical transmission system, a library of models, and tool support for implementing the particular methodology and models’ evaluation. The methodology and models described adopted Stochastic Petri nets (SPN) as the modeling formalism for dependability evaluation. The proposed models allow the assessment of availability and reliability estimation considering fault coverage, maintenance policies, and device interdependencies.

© MoDCS Research Group
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