EL CEREBRO Y LA INTELIGENCIA EMOCIONAL

Reliability indices are used by system planners and operators as a tool to improve the level of service to customers. Planners use them to determine the requirements for generation, transmission, and

distribution capacity additions. Operators use them to ensure that the system is robust enough to withstand possible failures without catastrophic consequences.

2.2.1

Generation

Reliability is measured using the available data, which varies across utilities and across system components. One metric universal to all utilities is the loss-of-load probability (LOLP).

“Overall system reliability is often expressed as a loss-of-load probability, or LOLP. Although based upon a probabilistic analysis of the generating resources and the peak loads, the LOLP is not really a probability. Rather, it is an expected value calculated on either an hourly or daily

basis. A typical LOLP is “one day in ten years” or “0.1 days in a year.” This is often

misinterpreted as a probability of 0.1 that there will be an outage in a given year. Loss-of-load probability characterizes the adequacy of generation to serve the load on the system. It does not model the reliability of the transmission and distribution system where most outages occur

(Kueck et al. 2004).”(Emphasis added.)

Note that the LOLP is a function of the generation and peak loads – it does not include any failures in the T&D systems.

2.2.2

Transmission

Transmission failures are relatively rare and indices are not typically used to keep track of transmission line failure rates. However, at least one reliability council, East Central Area Reliability (now a part of Reliability First along with other reliability coordinators), calculates an availability that is a function of outage duration and number of circuits (East Central Area Reliability Coordination Agreement 2000). Rather, the system is designed and operated so that there is always additional transmission capacity in place to handle any unexpected line failures.

“The bulwark of reliability for bulk power transmission systems has long been the use of "worst single contingency" design and operation– often referred to as the "n-1" principle or criterion. It's kind of the "prime directive" of reliable power system operation. In short, it means that the system is planned and operated in such a way that it can sustain the worst single disturbance possible without adverse consequences– consequences like overloads on other facilities, instability, or loss of firm customer load. The contingency is usually the sudden outage of a key high voltage transmission line or major generating unit (Loehr 2001).”

2.2.3

Distribution

Other reliability metrics are based upon customer outage data, and the vast majority of these outages reflect faults and failures in the distribution system. These data describe how often electrical service was interrupted, how many customers were involved with each outage, how long the outages lasted, and how much load went unserved. Industry indices are defined in Institute of Electrical and Electronics Engineers (IEEE) Standard 1366.17 _{The most commonly used are listed here.}

SAIFI, or system average interruption frequency index, is the average frequency of sustained

interruptions per customer over a predefined area. It is the total number of customer interruptions divided by the total number of customers served.

SAIDI, or system average interruption duration index, is commonly referred to as customer minutes of interruption or customer hours, and is designed to provide information as to the average time the customers are interrupted. It is the sum of the restoration time for each interruption event multiplied by the number of interrupted customers for each interruption event divided by the total number of customers. CAIDI, or customer average interruption duration index, is the average time needed to restore service to the average customer per sustained interruption. It is the sum of customer interruption durations divided by the total number of customer interruptions.

A reliability index that considers momentary interruptions is MAIFI, or the momentary average interruption frequency index.

MAIFI is the total number of customer momentary interruptions divided by the total number of customers served. Momentary interruptions are defined in IEEE Standard 1366 as those that result from each single operation of an interrupting device such as a recloser.

Unfortunately, it is very difficult to compare these indices from one location to another or from one utility to another because of differences in how they are calculated. Some utilities exclude outages

due to major events, or normalize their results for adverse weather. For the SAIDI calculation, some utilities consider an outage over when the substation is returned to service and others consider it over when the customer is returned to service, a difference in approach that can change the SAIDI by a factor of two. Some utilities use automatic data collection and analysis while others rely on manual data entry and spreadsheet analysis.

Depending upon the utility, momentary outages may be classified as a power quality event rather than a reliability event. Less often used indices include ASIFI, the Average System Interruption Frequency, and ASIDI, the Average System Interruption Duration. Both of these factors incorporate the magnitude of the load unserved during an outage. However, less than 10% of utilities track these indices (McDermott and Dugan 2003). Considering that the data collection and reporting of reliability indices vary over a broad range, their usefulness in assessing DG effects may be limited.

Another common reliability index is referred to as “nines.” This index is based upon the expected minutes of power availability during the year. For example, if the expected outage is 50 minutes per year, the power is 99.99% available or four nines. However, if this index is calculated using the LOLP it won’t reflect outages in the T&D systems. If the nines are calculated based on the SAIDI, the nines index will give some indication of the average system availability, but not the availability for any particular customer.

“Conventional bulk supply systems, from a service interruption perspective, deliver power with reliability in the range of 99.0% up to 99.9999% (also referred to as “two nines” up to “six nines,” respectively) and average reliability being about three to four nines, or 99.9% to 99.99%. Rural electric customers typically experience the least reliable power in the range of two or three nines. Urban customers served by networks typically have the highest reliability with five or six nines (Gellings et al. 2004).”

Considering that the data collection and reporting of reliability indices vary over a broad range, their usefulness in assessing DG effects may be limited.