Hi Peter, Power Factor (calculated from energy) was just used as an example of a more complex expression using division that should be aggregated before the expression is evaluated in order to get the expected result. While this may not be relevant to the PF analysis and billing determinants that you are looking at (which I think from the other post is PF at time of peak demand), we've had a number of requests from clients in areas where customers are billed on "average" power factor (calculated from total monthly kWh and total monthly kVARh) to be able to chart this in Trend Analysis. Tony's example used SUM PER DAY, but it would be the same idea, just using SUM PER MONTH, when viewing monthly average power factor in Trend. The ability to view Power Factor in Trend is new. We didn't initially expose it because of precisely what you have raised here- there are different expectations of how rolling-up power factor to monthly (daily, weekly,yearly) intervals should be handled. We implemented the "average" power factor method as described above, but don't currently have an easy "out of the box" setting to tell the system to show PF at time of peak kW (or peak kVA) when rolling up the data. Some of the scenarios that you can set up fairly easily are: "Average" power factor calculated from energy (aggregate energy before calculating power factor) Calculate the power factor at the lowest level interval (e.g. 15-minute) and then show the Average of those values (probably the least desirable scenario) Calculate the power factor at the lowest level interval (e.g. 15-minute) and then show the Minimum of those values Calculate the power factor at the lowest level interval (e.g. 15-minute) and then show the Maximum of those values The aggregation method (average, min, or max) is set for a measurement group, and you can define multiple measurement groups with the different methods if you want to compare the various values on a chart. If you want a report on your monthly PF at time of peak demand over the last year, you could set up a more complex expression to calculate this. There's an example here if you are interested: Using an expression to find PF at time of peak demand (and other coincident values) PAM supports interval data in all different lengths below hourly. I believe the most common we see is 15-minute, but we have half hourly, 5-minute, 10-minute, etc. If you want to see the lower level interval metered data, you can do this in Load Profile. In addition, the statistics in Load Profile offer some of the Power Factor data that I think you are looking for (min, max, average, PF at time of peak demand). Trend Analysis does aggregate the data to hourly as the lowest interval length supported, and also rolls up to daily, weekly, monthly, yearly. It aggregates using the measurement group's aggregation method, so energy streams will add up the half hourly data, Demand streams will take the maximum half-hourly value, temperature will take the average of all the intervals, etc. These aggregation methods are set for each measurement group. You can break the data into time of day periods (in PAM these are Site Schedules) and show these in Trend, or use them in calculated expressions. I'm not exactly clear on the question in your example, but I think you are asking if PAM aggregates all of the energy (or cost or other data) for a day and then somehow averages that back into each time period. If that is the concern, the answer is no, PAM doesn't aggregate/average when using the site schedule feature. PAM actually works at the lowest level in almost all cases. The feature to roll-up the data first before calculating the expression was specifically added (with a special directive to do so) to handle the average power factor scenario because most of the time PAM does operate on the lowest level before rolling things up. For example, in Trend analysis when breaking down the data by Site Schedule, each interval data point is allocated to a TOU bucket before those buckets are rolled up individually. Each interval data point in the shaded area (here on Load Profile, 9am-5pm weekdays) is included when adding up to get the daily (or monthly or yearly) total. The max demand for each time period is only from the intervals that fall into the time period definition. Same thing if you are calculating cost from energy * price. As Tony mentioned above, multiplication will always operate at the lowest level and then aggregate after. So if you want to aggregate your cost per TOU period on an expression which is Energy * Price, it will calculate the cost at each lowest-level interval (e.g. 30-minutes), and then add those up for each TOU period for your selected time range (e.g. per week or per month). There are some complexities in setting this up (using Site Schedules in expressions if you want TOU-specific pricing), but it will work as you want it to. There are a couple of other shortcomings that I know we have related to what you mentioned. The first is seasonal TOD definitions. Right now you can define TOU periods on different days of the week, include special days (e.g. holidays), but there is no support for seasonality or annual effective dates. The second you can see in the screen capture above: we don't actually show the timestamp of the min/max demand in the statistics window of the Trend Analysis. You have to click on the day to see the hour, or jump over to Load Profile to see the exact timestamp. I hope this answers the gist of all of the questions, but let me know if not! I'm happy to follow up with some time on the phone if it would be helpful. Cheers, Cindy
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