4. Bad utility bill data is
giving me indigestion.
I need audits and
check reports.
5. The most important step is to use audits!
This recommended group of Quick Check Audits will catch the
most obvious keying errors. You can make them more sensitive.
6. Use AN27 on each
batch, on all bills
created last week, or
on all bills in last
month’s billing period
to ‘eyeball’ possible
errors. The yellow
star denotes the bill
being checked; it’s
always on far right.
7. AN01 and AN02, or the Calendarized versions CAL06 and
CAL07, are great quick checks for historical data. Run once
per commodity.
8. Try the new NORM11 to quickly see deviations from same
month last year and same month baseline year.
11. One meter has two different UOM in history. This can affect
reports, cost avoidance, audits, budgets, accruals and interfaces.
12. Administration – Units of Measure – Mixed UOM shows
discrepancies and gives you an easy way to fix them.
13. A fixed bill record looks like this. In this case the user keyed
originally as CF, then used the fixer to change to Gal, then
used it again to change to CCF. All prior values are
documented.
20. My feet ache because I’m
carrying abnormal load…factor.
Report AN12 will spot it.
21. Load Factor: Ratio of actual kWh usage to maximum theoretical kWh
usage
Actual usage – from the utility bill
Max theoretical usage = Maximum kW demand x hours in billing period
This is what you could have used if running at max power for the entire
month
Example: Peak demand = 100 kW (the “all on” condition)
Billing period = 30 days = 720 hours
Max theoretical usage = 100 kW x 720 hrs = 72,000 kWh
Billed usage = 40,000 kWh
Load Factor = 40,000/72,000 = 0.56 = 56%
22. Normal load factor: 40% - 60% (Schools, offices, “9 to 5” facilities)
Low load factor: Your usage is very “spikey.” Some high peaks
but typical usage is low.
Examples: Outdoor recreation (under 15%)
Standby fire pumps (under 5%)
Storm water ejector pumps (under 5%)
Meter or billing error
High load factor: Your usage is very constant. (Utility companies
like this and often offer high load factor discounted rates. Be sure
you take advantage!)
Examples: Data center (80 – 95%)
24/7 lighted parking deck (85 – 95%)
Refrigerated warehouse (70 – 90%)
Supermarket (70 – 85%)
24/7 facility (50 – 75%)
Meter or billing error (over 100%)
23. Low Load Factor – It must be outdoor recreation, standby
pumps, or data error.
24. High Load Factor – Over 100% is impossible (except with
some Billed Demand ratchet rates); these are data errors.
25. Load Factor is shown in chart form for each meter in
Buildings & Meters – Actual Data – Demand
27. My buildings and meters need to join a
peer group in Groups & Benchmarking.
28.
29. Click on the parent category and then + to create a user-
defined group. Yellow are manually maintained, purple are
super-easy and convenient “auto” groups.
34. Quickly – weeks before receiving the electric bill – spot
curious spikes, missing weekend and nighttime setbacks,
unseen equipment cycling, too-early, too-late control
settings and other money-saving insights. Smart CAPture
lets you start capturing the savings before receiving the bill!
38. So many features! Select columns, set filters, arrange column
order, set sort order (even multi-layer), export your list and your
columns to Excel, select and act on many at once, drill into
individual bill records.
42. Accounting Calendar
Accounts
Accounts User Defined Fields
Channels
Cost Avoidance Adjustments
Cost Centers
Customers
G/L
Meters
Meters User Defined Fields
Organizations & Buildings
Place User Defined Fields
Simple Bill Split Distributions
Simple Submeter
Distributions
Users
Vendors
Vendors User Defined Fields
Separate Update spreadsheets for each of these types of data
43. Each Update spreadsheet shows existing data and lets you
update (in white columns only) just what you need.