Reliability of a system is difficult to measure. Perhaps the best way is through evaluation of the consequences of possible consumer interruptions. Investigations have shown that the best measure of reliability is that of consumer reaction.
Five conditions that have been identified impact the value an average consumer puts on an unsupplied megawatt-hour of lost energy:
A number of indices have been developed, primarily for the distribution system, to provide another measure of reliability:
SAIFI (System Average Interruption Frequency Index) measures the average frequency of sustained interruptions per customer
SAIDI (System Average Interruption Duration Index) measures the average time that all customers are interrupted
CAIDI (Customer Average Interruption Duration Index) represents the average time required to restore service to the average customer per sustained outage
MAIFI (Momentary Average Interruption Frequency Index) tracks the average frequency of momentary interruptions, typically defined as less than five minutes
Five conditions that have been identified impact the value an average consumer puts on an unsupplied megawatt-hour of lost energy:
- The activities affected by the curtailment and, therefore, the time of day and mix of customers
- The number of interruptions
- Availability of advance warning
- Weather conditions and, therefore, the time of year
- The duration of the interruption
Figure 9-1 shows that this reaction increases dramatically as the frequency of outages increase, as the duration of the outage increases, and with the magnitude or extent of the outage. The following function presents a means of evaluating this reaction:
R = function of {K, F, T, P, t}
Where K is an empirical coefficient proportional to the consumer’s dependence on electricity, F is the frequency of interruptions, T is equal to duration of the interruptions, P is the amount of load interrupted, and t is the time when the interruption occurs. Experience has shown that K increases with increasing consumption of electricity per customer, and t is greatest at the time of day, week, or year when people suffer the greatest hardships if service is interrupted. This criterion for reliability evaluation does not consider other curtailments of service, such as voltage or frequency reductions. These “partial” curtailments are not as important to most consumers as a complete interruption but they should also be considered.
R = function of {K, F, T, P, t}
Where K is an empirical coefficient proportional to the consumer’s dependence on electricity, F is the frequency of interruptions, T is equal to duration of the interruptions, P is the amount of load interrupted, and t is the time when the interruption occurs. Experience has shown that K increases with increasing consumption of electricity per customer, and t is greatest at the time of day, week, or year when people suffer the greatest hardships if service is interrupted. This criterion for reliability evaluation does not consider other curtailments of service, such as voltage or frequency reductions. These “partial” curtailments are not as important to most consumers as a complete interruption but they should also be considered.
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| Figure 9-1. NERC regions. Source: NERC. |
SAIFI (System Average Interruption Frequency Index) measures the average frequency of sustained interruptions per customer
SAIDI (System Average Interruption Duration Index) measures the average time that all customers are interrupted
CAIDI (Customer Average Interruption Duration Index) represents the average time required to restore service to the average customer per sustained outage
MAIFI (Momentary Average Interruption Frequency Index) tracks the average frequency of momentary interruptions, typically defined as less than five minutes