Taming the Wind
We received the February issue of Public Utilities Fortnightly and it is going around the office with a special earmark for your article on “Taming the Wind .”
It is a pleasure to read. The article captures just about perfectly the value of forecasting in cost-effectively and reliably integrating wind power, of balancing in large markets, of geographical spread, and more. It also looks at what the future could hold.
Again, it is a pleasure, both accurate and refreshing! With best regards, and best wishes for your publication,
— Christine Real de Azua, Assistant Director of Communications, American Wind Energy Association (AWEA), Washington, D.C.
I was reading through Charles Thurston’s article in the March issue of Fortnightly ( “Coming to America ”), and was interested in understanding the System Average Interruption Duration Index (“SAIDI”). Is this the number of total customer outage hours divided by total customers?
— Eric Eriksen, Vice President, Alaska Electric Light & Power Co., Juneau, Ak.
Editor’s note: Ali Ipakchi at Kema Consulting tells us the simple definition of SAIDI is the total minutes, on average, that customers are without electricity in a year, including both planned and unplanned minutes off supply. Formula: the product of the number of minutes of each interruption duration times the number of customers affected, divided by the total number of customers.
[In the same article] Thurston asserts that other countries are ahead of the United States in applying new technologies to utilities, and supports this assertion, in part, with a chart comparing SAIDI performance in various countries.
SAIDI is not without controversy as a measure of utility service performance. For example, when New York was considering the SAIDI as a replacement for its then-existing Customer Average Interruption Duration Index (CAIDI) and System Average Interruption Frequency Index (SAIFI) service performance standards, concern was expressed about the SAIDI masking performance as indicated by the number of interruptions (system reliability) and their average length (response time).
For the United States, Thurston shows the average interruption times for four regions (Atlantic, Midwest, Midwest-Rural, and Pacific Northwest), three states (California segregated between Northern and Southern, Florida and Texas), the average, and best practices. For outside the United States, he shows times for Hong Kong, Scotland, Singapore, the United Kingdom average, the European Union average, and best practices. Thurston’s comparisons suggest that population density, climate, terrain, and geography are significant influences on the depicted relationships—perhaps even more significant than adoption of new technologies.
Relationships that suggest the influence of population density are: The European Union average interruption time being less than half of the U.S. average; the Hong Kong and Singapore times being about one-quarter of the European Union average and less than 10 percent of the U.S. average; the Southern California time being about one-third of Northern California; the Midwest time being about two-thirds of Midwest-Rural and Pacific Northwest; and the Texas time being higher than for Florida, Midwest, and Southern California, and lower than for Northern California.
Relationships that suggest the influence of