SAIDI
265 min per year
Average outage minutes (2023)
Great Lakes Energy Coop is a member-owned electric cooperative operating in Michigan under EIA identifier 38084. It reports service to approximately 131,726 customer accounts and generated about $0.23 billion in annual electric revenue, with a service footprint spanning 184 ZIP codes. As a cooperative, its governance is accountable to its ratepayer-members rather than shareholders, which often shapes rate-setting and reinvestment priorities.
In 2023, the average Great Lakes Energy Coop customer experienced 265.2 minutes of power interruptions — a metric called SAIDI (System Average Interruption Duration Index). That sits within the 120–180 minute national benchmark range, indicating performance typical of U.S. distribution utilities. SAIFI — the average number of outage events per customer — was 1.69 for the same period, so customers statistically faced roughly 2 distinct interruptions that year. Excluding major event days (hurricanes, ice storms), SAIDI drops to 202.5 minutes — the gap between that figure and the headline 265.2 reveals how much weather, not day-to-day infrastructure, drove outages.
The EIA dataset includes 4 years of continuous reporting (2020–2023) for Great Lakes Energy Coop, which lets you see whether reliability is trending up or down rather than judging from a single snapshot. SAIDI has improved from 486.3 to 265.2 minutes over that window — a meaningful direction for prospective customers and regulators watching capital investment outcomes. All figures on this page come directly from EIA Form 861, the federal annual electric power industry survey, with service territory ZIPs sourced from OpenEI — you can cross-reference them with your own utility bill or use them when comparing providers before relocating.
SAIDI
265 min per year
Average outage minutes (2023)
SAIFI
1.69 interruptions/yr
Outage frequency (2023)
Customers
131,726
Served in Michigan
265 minutes per customer per year
Minutes without power per year (2023)
| Year | SAIDI (min) | SAIDI nMED | SAIFI | Customers |
|---|---|---|---|---|
| 2020 | 486.3 | 212.3 | 2.570 | 126,926 |
| 2021 | 1221.4 | 204.8 | 3.250 | 128,693 |
| 2022 | 546.1 | 211.0 | 2.370 | 129,926 |
| 2023 | 265.2 | 202.5 | 1.690 | 130,610 |
SAIDI nMED = SAIDI without major event days. Source: EIA Form 861.
Great Lakes Energy Coop serves 184 ZIP codes in Michigan.
Great Lakes Energy Coop had a SAIDI of 265.2 minutes in 2023, meaning the average customer experienced about 265 minutes of outages that year. This is near the national average.
Great Lakes Energy Coop is classified as a Cooperative serving Michigan. Electric cooperatives are member-owned nonprofit utilities, typically serving rural areas.
SAIDI (System Average Interruption Duration Index) measures the average total minutes per year that a customer of Great Lakes Energy Coop experiences power outages. A lower SAIDI indicates better reliability. The national average is roughly 120-180 minutes per year, so comparing Great Lakes Energy Coop's SAIDI to that benchmark shows whether this utility is above or below average.
Great Lakes Energy Coop serves approximately 131,726 customers in Michigan. Customer count can affect reliability metrics because larger utilities may face different infrastructure challenges compared to smaller ones.
Great Lakes Energy Coop has 4 years of reliability data (2020-2023). SAIDI has remained relatively stable over this period. Review the trend table above for year-by-year detail.
SAIDI "without major event days" (SAIDI nMED) excludes outages caused by hurricanes, ice storms, and other catastrophic weather events. It better reflects day-to-day infrastructure reliability rather than vulnerability to extreme weather. Both standard SAIDI and SAIDI nMED are shown in the reliability trend table above.
Disclaimer: This information is provided for informational purposes only and does not constitute professional advice. Data is sourced from the U.S. Energy Information Administration (EIA) Form 861. Consult a qualified professional before making decisions based on this data.
Read our methodology — how this data is sourced, computed, and verified.