DOI: 10.4018/978-1-4666-9429-3.ch009
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Protection methods, which were described in the previous chapter, save the converter against non-catastrophic faults. However, this method saves the converter but it also takes the converter out of the service. The subject of this chapter is converters that are not damaged but can not operate normally. In this chapter, availability of electric power converters as a most important but usually forgotten parameter is described. The concept of availability was originally developed for repairable systems that are required to operate continuously. It is explained that a system may be unavailable while none of its parts damaged. In fact, there is an important difference between reliability and availability. A converter may be highly reliable but unavailable and vice versa. One of the most important factors for this undesired state is influence of noise. In this chapter, electromagnetic interference and certain methods for reducing its undesired effects on electric power converters are presented. Electric power converters are usually the source of electromagnetic noise due to high operating voltage and/or current. Various techniques for safe operation of sensitive systems that operate close to these converters are described. In the last part of chapter, alarm management is presented based on availability concept. This method is used to prevent fast shutdown of important systems due to dispensable faults.
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Introduction: Available Or Safe?

Figure 1 shows the state of this chapter in the flowchart of the book. The concept of availability was originally developed for repairable systems that are required to operate continuously, i.e., round-the-clock, and are at any random point in time either operating or “down” because of failure and are being worked upon so as to restore their operation in minimum time. In this original concept, a system is considered to be in only two possible states - - operating or in repair -- and availability is defined as the probability that a system is operating satisfactorily at any random point in time, t, when subject to a sequence of “up” and “down” cycles which constitute an alternating renewal process (Kwasinski, Krishnamurthy, Song, & Sharma, 2012).

Figure 1.

State of chapter 9 in the flowchart of the book


A trade-off is a rational selection among alternatives in order to optimize some system parameter that is a function of two or more variables which are being compared (traded off). Examples of system trade-offs involve performance, reliability, maintainability, cost, schedule, and risk. A trade-off may be quantitative or qualitative. Insofar as possible, it is desirable that trade-offs be based on quantifiable, analytic, or empirical relationships. Where this is not possible, then semiquantitative methods using ordinal rankings or weighting factors are often used.

The methodology for structuring and performing trade-off analyses is part of the system engineering process described in Section 4. The basic steps, summarized here are:

  • 1.

    Define the trade-off problem and establish the trade-off criteria and constraints

  • 2.

    Synthesize alternative design configurations

  • 3.

    Analyze these alternative configurations

  • 4.

    Evaluate the results of the analyses with respect to the criteria, eliminating those which violate constraint boundaries

  • 5.

    Select the alternative which best meets criteria and constraint boundaries or iterate the design alternatives, repeating Steps 2 through 5 to obtain improved solutions.

System effectiveness and cost effectiveness models provide the best tools for performing tradeoff studies on the system level. Through the computerized models, any changes in any of the multitude of reliability, maintainability, performance, mission profile, logistic support, and other parameters can be immediately evaluated as to their effect on the effectiveness and total cost of a system. Thus, cost effectiveness modeling and evaluation, besides being used for selecting a specific system design approach from among several competing alternatives, is a very powerful

tool for performing parametric sensitivity studies and trade-offs down to component level when optimizing designs to provide the most effective system for a given budgetary and life cycle cost constraint or the least costly system for a desired effectiveness level.



Availability means the probability that a system is operational at a given time, i.e. the amount of time a device is actually operating as the percentage of total time it should be operating. High-availability systems may report availability in terms of minutes or hours of downtime per year. Availability features allow the system to stay operational even when faults do occur. A highly available system would disable the malfunctioning portion and continue operating at a reduced capacity. In contrast, a less capable system might crash and become totally nonoperational. Availability is typically given as a percentage of the time a system is expected to be available, e.g., 99.999 percent.

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