Under the provisions of Massachusetts Green Communities 2016 funding and as a subcontractor to Guardian Energy Management Services, Advanced Energy Intelligence ("AEI") is delivering the reporting on this website in order to satisfy the requirements of the funding and Guardian's purchase order number 5040-AEI. Specifically, this web site covers line item 1 of our proposal to Guardian to provide "Main Meter Analytical Services" for the Winthrop William P. Gordon Middle School and Fort Banks Elementary School. The reporting we are providing here is known by our product designation "SoftStart".
For the website and reporting results for the Arthur T. Cummings Elementary School (GEMS PO Number 5039-AEI), please visit https://www.aeintelligence.com/gems-winthrop/cummings.
Scope of Work
Using Energy Profiler Online (EPO) data for Fort Banks Elementary school, we examined the electric energy use at the school for the years 2012 through 2016. We present the data in various ways to focus attention on specific behaviors at the facility that help to inform the way the school uses electricity and how that usage might be improved.
In this initial review, we combine the EPO data with weather, ISO New England loads, and baseline utility rates to better understand the influences on the building, and the resulting changes in costs associated with those influences. This first phase is a very preliminary and high level baseline assessment of the facility and does not propose any prescriptive remedies.
After the First Phase
In subsequent work which will continue throughout 2017, we will continue to update the charts and commentary each month as new monthly EPO data is made available. Coincident with this work, we will start to engage the BAS data which should be online by mid-January, and this extra level of detail will begin to inform what we see at the main meter. We also expect to learn more about the specific billing parameters in effect from National Grid and Direct Energy to develop a more accurate pro forma billing engine which will be useful for (a) billing reconciliation and (b) consideration of alternate rate schedules or commodity agreements. Finally, as we approach the summer cooling season, we will pay special attention to peak demands by using historic data combined with BAS data to establish guidelines and measurements for peak demand reduction. Our continued effort will include the tracking of key metrics determined by us, Guardian or Town of Winthrop, especially if those metrics can support ECMs that should have a positive effect at the main meter.
Presentation of Results
The visualizations and statistics presented on this website are particularly dense and may take a while to fully digest. As such, AEI does not consider this written work to be sufficient for the scope of work, but fully expects to present the results in person or via web conference to Guardian and to Town of Winthrop at Guardian's direction, at a place and time suitable to Guardian. Additionally, our reluctance to talk about prescriptions during this early phase is largely because we have questions and should take into account BAS data for a more accurate assessment. While AEI is now very familiar with the way electricity is used at the two facilities in Winthrop, it makes sense to better understand where there may have been specific influences on the behavior of the buildings in order to develop more targeted recommendations through the year.
Going forward, we expect to update the website each month, and report quarterly on any trends or noteworthy events. Moving into the summer as we pay daily attention to peak demands, we will put Winthrop on our watch list and include them in our ISO New England SMS and E-Mail alerts.
Quarterly Reports and Update Notes for this site have been moved to the GEMS Winthrop homepage.
The table below shows several high-level statistics for the site, meant only to give a very broad overview of the electricity usage, costs, and assumed parameters.
|Total Usage, kWh|
|EPO Data, Hours|
|Average Load, kW|
|Conditioned Space, ft2|
|Electric EUI, kBtu/ft2/year|
|Cost and Cost/ft2, $
(National Grid G-3 Pro Forma)
We note the following things since they have an effect on subsequent data presentations and discussions:
- Total kWh usage increases significantly year over year from 2012 through 2016; at the same time we show a flat occupied square footage of 80,000ft2. In the absence of other viable explanations for the increase in electricity usage, it makes sense that our assumption that the size of the building has not changed may be flawed.
- There are 8,760 hours in a standard year, and we note that EPO data was missing for several hours in each year, most notably in 2015 and 2014. We do not adjust for the missing data but will look at missing data logic when appropriate.
- Something happened at the building in December 2014 at which point the median demand at the facility went from around 50kW to consistently over 80kW.
- The color coding of monthly values from green to red nominally tries to reflect "better" to "worse", respectively. But it's not always clear when such a scale should apply. For example, when we calculate the ratio of monthly peak to median loads, a high ratio might mean very high peaks. But a low ratio could mean that the median load is undesirably high. Neither situation might be ideal and the arbitrary choice of a color-coded to suggest a better or worse condition may be inappropriate.
Cumulative Load Plots
Active Cumulative Load Charts
Sections 03.02 through 03.05 are deprecated as of January 2018 in favor of the interative chart here in 05.01.
Summer Occupied Hours Only
Winter Occupied Hours Only
Shoulder Occupied Hours Only
The median load for all hours in the year has steadily increased at Fort Banks over the past 5 years, from a median of 76.9kW in 2012 to 111.3 in 2015. This is not especially important or relevant since the increase in usage may have come from additional occupancy, facility expansion, or other usage reasons. It is worth noting that in 2012 through 2014, the facility showed good weekend setback - the orange weekend values showed a stronger tendency to be below the median than in 2015 and 2016.
Filtering the annual hours for just Summer Peak Hours (Mon-Fri, 6am to 6pm), we see a steady improvement in efficiency over the past 5 years. Instead of summer peak hours concentrated above the median value, we see a more even distribution and this has the effect of bringing the median down from 161.9kW in 2013 down to 133.5 in 2016. This is the corollary to what we observe when looking at all hours - the recent trend for peak summer hours to be found below the median explains why off-peak and weekend hours are now more likely to be found above the median.
Winter occupied hours show a steady decline from 2014 to 2016, suggesting that as with summer there is a more even distribution of loads through the year.
Given that summer and winter occupied hours seem to hint at a positive trend, the overall increase in the median load over the past 5 years is due to lack of control during the unoccupied hours. We'll show below how the lack of strong night and weekend setback are largely responsible for the overall increase in demand at the facility.
Weather Normalization and Correlation
Before we consider whether or not it makes sense to normalize years to account for weather, we first look at how the building load correlates with weather (defined by Weather Underground Air Temperatures for ZIP 02152). Where the correlation is poor, it makes little sense to expect that normalizing for HDD in winter or CDD in summer is meaningful in any way. To give weather the benefit of the doubt, we show regressions of load on OA Temperatures for the specific seasons in each year, since correlations are usually improved when isolating specific seasons of the year.
Summer Occupied Hours versus Weather
Winter Occupied Hours versus Weather
Weather Normalization Annual HDD/CDD
|Year||Act Hours||Act kWh||Adjusted kWh||Adjusted kWh/(HDD+CDD)||Weather Adjusted Change||HDD||CDD|
We show the main meter interval data in a 7-Day composite profile to get a feel for how well the building sets back on weekends, and to a lesser degree, at night. Each chart shows the 15 minute readings for the months of June through August. We are looking for reduced loads on Saturdays and Sundays, and then for unusually high mid-day peaks in the occupied weekdays. The overnight hours appear as troughs in between the occupied mid-day hours, and we look for them to be sharp and defined which would coincide with a good end-of-day setback and sharp morning start-up policies.
Active Weekly Profile Chart
Summer (June, July, August)
School Year (September through May)
Daily Profiles by Month
In this presentation of the data, we build a composite daily profile for each month. This is not a very common presentation of 15-minute utility data, but it serves to show what an average day looks like for each month in the given year. It is not intended to inform night or weekend setback, but instead to illustrate a rough look at an average day for each month in the year.
Active Daily Profiles by Month
Daily Profiles by Month
The 95th percentile loads at Fort Banks have steadily risen over the years. Starting in December of 2013, we note the significant full-time load of about 50kW that pushes all the data up by that amount until February or March of the following year. In December of 2016, it looks like this load may have become less than full-time since many hours in that month returned to their pre-2013 5th percentile values.
Weekday nights, median night time load compared to median daytime load. (6am-6pm for daytime). We look at night and weekend setbacks as a measure of how well the building reduces energy usage during unoccupied hours.
Begining in December 2013, it appears that a significant always-on load came online and remains online into February and March each winter. This new load has raised the unoccupied median load since that time. The median occupied load has also risen but to a lesser degree, and the result is that our measure of the night setback ratio has dropped significantly. A ratio of 1.5 for example means that the occupied median load is only 50% higher than the unoccupied median load, and this would seem to be an indication of the building's inability to come to a clean stop each day.
Unoccupied kW/1000ft2 Comparison to Three Boston Schools
As an independent measure of night setback, we made a similar calculation using a few schools in the City of Boston for a comparison. The 2.5th or 5th percentile kW value is commonly used as a proxy for how well buildings set back during the unoccupied hours.
The data in the tables below show the Winthrop Ft Banks School had a 5th percentile kW of 0.365 kW/1000ft2 in 2012 that has increased to 0.716 kW/1000ft2 in 2016.
The 2012 value should be considered as a worth target which is very close to the 0.3 kW/1000ft2 average from three schools of similar size in Boston.
|School||Size, ft2||5th Percentile kW||kW/1000ft2|
|Fort Banks, 2012||80,000||29.2||0.365|
|Fort Banks, 2016||80,000||57.3||0.716|
Weekday daytime load compared to all weekend hours.
The weekend setback ratio of Weekday Occupied to Weekend All Hours median loads shows a change over the past 5 years similar to what we saw in the Night Setback section above. This makes sense, since the new always-on load that appeared in December 2013 would have a similar effect on weekend hours as it does on weekday unoccupied hours.
Load versus ISO New England
Data available from ISO New England back to 2014. Section 10.02 is deprecated in favor of the active chart in 10.01 which is more interactive and granular.
Active Chart Regression on ISO NE Demand
Our comments here are largely the same as those for Cummings.
Using 5-minute interval data from ISO New England, we like to plot a facility's coincident load to see if the building correlates with the grid. As an aside, ISO New England loads correlate fairly well with weather (temperature and humidity) so it's not usually very surprising to find that a site's correlation with weather looks a lot like its correlation with the grid since there is a common dependent variable.
Just the same, correlating with the grid is meaningful in terms of visualizing whether or not a site has a strong demand response to those conditions where ISO New England is nearing its peak and may call for its annual peak hour. Ordinarily, we would expect to the facility load flat-line or decrease when ISO NE reports loads above 23,000MW since we know from history that the potential for an annual peak hour is higher than normal.
In the case of Fort Banks - and not uncommon with schools in general - we see relatively poor correlation with ISO, especially in the summer months. In the summer, even an active school typically has a lower profile than it does during the school year, whereas the grid doesn't have the luxury of reducing its demand. We do note a few things in the chart that are worth mentioning:
- Fort Banks is above its 95th percentile load during many different seasons of the year, sometimes even in winter, when ISO NE is only at 13,000MW or higher. While the grid may be at a relatively low demand state, that doesn't necessarily provide any predictive value for how the school is operating.
- Fort Banks might actually have a relatively low load when the grid is at or above 20,000MW (roughly the grid's 80th percentile). We can likely attribute this to the summer season when the school is in an unoccupied state on hot days with high regional demand.
- In the upper right hand quadrant for any of the years 2014 to 2016 shown above, we can tell that Fort Banks does not engage in any meaningful demand response associated with alerts from ISO New England because we see that at 23,000MW and higher, the load at the school seems to be arbitrary. If the school were engaging in a specific response to grid alerts, we would expect to see even a slight negative correlation where loads in the school decrease as ISO's demand increases.
The R2 correlations show the relationship between the school and ISO to be weak. We also filtered for only summer occupied hours and could get a correlation of around 0.40 (as well as similar correlations when looking at weather), and for this reason we don't put a lot of stock in any weather normalization year/year at the facility since well over 50% of the variance in energy use is explained by factors other than weather.
[NOTE to Guardian on Berlin: With the installed AEI/Obivus/Verizon real-time metering installed at the two locations there, we will be reporting in real-time ISO New England load and the Berlin Municipal Building and Memorial School coincidental loads. This means real-time SMS and E-Mail alerts that take into account both the building's peaking condition as well as ISO's load, even if the two are not correlated.]
ICAP Tag and Capacity Charges
Capacity charges for FY17 are a foregone conclusion and are $15.00/kW. The charges for FY18 are $9.55/kW and the ICAP tag associated with facilities in the ISO New England service area will be determined when the grid sets its peak hour for the fiscal year beginning on June 1, 2017.
We assume there is an ICAP tag effect in the Direct Energy contracts at Cummings and Fort Banks, and will learn the details of how this rate affects the monthly bills when we examine both the National Grid and Direct Energy billing statements. For the record, it looks like the ICAP tag for Fort Banks should be around 247kW since that was the facility load on August 12, 2016 during the 2pm hour when ISO New England saw its peak annual hour.
We do not account for the Direct Energy contract when making our calculations in this section or in the Billing Data section below. Instead, we make all calculations based on the stock National Grid G-3 rate schedule and assume that National Grid is the fuel supplier.
Monthly Demand Charges
The nature of any demand-based utility rate schedule is such that a disproportionate share of the monthly utility bill is from charges associated with the peak demand in the billing period. In the table below, we use the stock National Grid G-3 distribution demand rate of $5.75 to calculate the cost of the hours in each period that exceed the 95th percentile load in the month. By definition then, we are looking at the 5% of the hours in each month and the cost we calculate is the difference between the 95th percentile and the peak.
By way of example, in May 2016 Fort Banks had a peak load of 282.2kW and a 95th percentile load of 195.5kW. Therefore, 5% of the hours in the month (37 hours) had an average hourly load between 195.5kW and 282.2kW. If those hours could have capped at the 95th percentile load of 195.5kW, the savings in the month would have been $499 in demand charges alone, plus a smaller savings (not shown) of about $208 associated with the coincident reduction in usage at $0.13/kWh.
We show a total in 2016 of $3,591 in cost or savings associated with loads above the 95th percentile, which amounts to approximately 2.6% of the total electricity bill for Fort Banks in 2016.
While a 2.6% savings might not seem like a large amount, we believe that the true demand charges are around $20/kW and not the $5.75/kW rate shown on the G-3 rate schedule. We can make a more accurate calculation when we see the rates associated with the Direct Energy contract, assuming that those bills break out the demand charges separately from usage.
Our AEI Billing Engine uses the EPO data and utility rate schedule to do a backward-looking pro forma calculation of what the monthly utility bills should have been for the facility. The accuracy of our calculations will depenend on our assumptions of the utility rates that are in effect for each period, and only to the extent that the EPO data is complete when compared to the data used by the utility when calculating the bill.
In the specific case of Cummings and Fort Banks, we are making a known invalid assumption - that the fuel supply was provided by National Grid according to its G-3 NEMA supply schedule. After we are able to review actual National Grid and Direct Energy bills from the site we will update this table to more accurately reflect the rates that are in effect. We will continue to show the stock National Grid calculation so that a cost comparison can be made; the facility should be able to recognize and quantify the benefit that we expect to find as a result of the contract with Direct Energy.
Winthrop Fort Banks ES
epo.1628552000-FORT-BANKS-SCHOOL.1.kW for kW, Rate Schedule NG G3
|Energy (Supply) Charges||TOTAL EST BILL (NationalGrid Supply)|
|Period||Peak Demand Date/Time||Period Max 5' kW||Period
|Distribution (On Peak)
|Distribution (Off Peak)
|2019-06 (26)||2019-06-06 13:15 Thu||228.96||20,031||32,144||52,175||$1,316.52||$258.20||$172.29||$1,598.11||$0.091480||$4,772.93||$8,118.05|
|2019-05 (31)||2019-05-24 11:45 Fri||188.28||29,907||24,276||54,182||$1,082.61||$385.50||$130.12||$1,659.60||$0.109220||$5,917.77||$9,175.58|
|2019-04 (30)||2019-04-08 10:00 Mon||164.16||31,353||34,303||65,657||$943.92||$404.15||$183.86||$2,011.06||$0.109100||$7,163.13||$10,706.12|
|2019-03 (31)||2019-03-25 10:00 Mon||159.12||33,968||44,102||78,070||$914.94||$437.84||$236.39||$2,391.29||$0.122150||$9,536.26||$13,516.71|
|2019-02 (28)||2019-02-01 09:30 Fri||183.96||32,757||40,406||73,163||$1,057.77||$422.24||$216.58||$2,240.98||$0.156470||$11,447.80||$15,385.36|
|2019-01 (31)||2019-01-31 09:45 Thu||182.52||38,441||40,754||79,196||$1,049.49||$495.51||$218.44||$2,425.76||$0.153410||$12,149.40||$16,338.60|
|2018-12 (31)||2018-12-18 08:30 Tue||189.36||30,964||33,889||64,852||$1,088.82||$399.12||$181.64||$1,986.43||$0.132270||$8,578.02||$12,234.04|
|2018-11 (27)||2018-11-07 11:00 Wed||180.00||27,210||29,159||56,369||$1,035.00||$350.74||$156.29||$1,726.57||$0.111650||$6,293.55||$9,562.14|
|2018-10 (31)||2018-10-10 10:15 Wed||258.12||36,113||31,999||68,112||$1,484.19||$465.50||$171.51||$2,086.27||$0.103310||$7,036.64||$11,244.11|
|2018-09 (11)||2018-09-26 09:00 Wed||244.08||9,418||15,815||25,233||$1,403.46||$121.40||$84.77||$772.88||$0.102000||$2,573.75||$4,956.26|
|2018-08 (14)||2018-08-28 13:30 Tue||205.20||11,264||20,354||31,618||$1,179.90||$145.19||$109.10||$968.46||$0.101290||$3,202.60||$5,605.25|
|2018-07 (16)||2018-07-17 12:30 Tue||227.88||13,453||21,302||34,754||$1,310.31||$173.40||$114.18||$1,064.52||$0.101840||$3,539.36||$6,201.77|
|2018-06 (28)||2018-06-18 12:30 Mon||275.40||26,977||40,995||67,973||$1,583.55||$347.74||$219.74||$2,082.01||$0.100310||$6,818.35||$11,051.38|
|2018-05 (31)||2018-05-29 11:00 Tue||232.20||38,740||28,924||67,664||$1,335.15||$499.35||$155.03||$2,072.53||$0.102270||$6,919.95||$10,982.02|
|2018-04 (30)||2018-04-26 13:15 Thu||201.24||31,189||36,344||67,533||$1,157.13||$402.03||$194.80||$2,068.54||$0.101920||$6,882.97||$10,705.46|
|2018-03 (31)||2018-03-21 10:15 Wed||195.48||35,730||44,610||80,340||$1,124.01||$460.56||$239.11||$2,460.82||$0.115370||$9,268.83||$13,553.32|
|2018-02 (28)||2018-02-07 10:00 Wed||180.36||29,817||37,208||67,025||$1,037.07||$384.34||$199.44||$2,052.97||$0.142590||$9,557.07||$13,230.88|
|2018-01 (31)||2018-01-30 10:30 Tue||197.28||41,712||46,575||88,287||$1,134.36||$537.67||$249.64||$2,704.23||$0.140320||$12,388.44||$17,014.34|
|2017-12 (31)||2017-12-13 10:00 Wed||191.52||34,039||41,688||75,727||$1,101.24||$438.76||$223.45||$2,319.52||$0.112990||$8,556.39||$12,639.36|
|2017-11 (30)||2017-11-03 12:15 Fri||206.64||33,568||36,095||69,663||$1,188.18||$432.69||$193.47||$2,133.79||$0.095860||$6,677.92||$10,626.04|
|2017-10 (31)||2017-10-24 12:00 Tue||227.16||36,906||31,900||68,806||$1,306.17||$475.72||$170.99||$2,107.54||$0.092990||$6,398.29||$10,458.70|
|2017-09 (30)||2017-09-05 14:15 Tue||270.00||32,546||42,582||75,128||$1,552.50||$419.51||$228.24||$2,301.17||$0.096100||$7,219.79||$11,721.21|
|2017-08 (31)||2017-08-31 10:00 Thu||196.56||23,355||40,202||63,557||$1,130.22||$301.04||$215.48||$1,946.74||$0.095280||$6,055.68||$9,649.16|
|2017-07 (31)||2017-07-12 10:15 Wed||208.44||24,555||48,807||73,362||$1,198.53||$316.51||$261.61||$2,247.07||$0.098230||$7,206.32||$11,230.03|
|2017-06 (30)||2017-06-13 11:45 Tue||267.12||31,972||50,177||82,149||$1,535.94||$412.12||$268.95||$2,516.24||$0.093210||$7,657.15||$12,390.40|
|2017-05 (31)||2017-05-18 10:00 Thu||261.36||39,369||32,903||72,272||$1,502.82||$507.47||$176.36||$2,213.69||$0.071110||$5,139.27||$9,539.61|
|2017-04 (30)||2017-04-28 12:00 Fri||227.52||34,201||40,378||74,579||$1,308.24||$440.85||$216.43||$2,284.36||$0.085020||$6,340.71||$10,590.58|
|2017-03 (31)||2017-03-20 09:30 Mon||194.40||43,602||48,665||92,267||$1,117.80||$562.03||$260.85||$2,826.15||$0.098100||$9,051.43||$13,818.26|
|2017-02 (28)||2017-02-15 11:45 Wed||205.20||36,655||46,840||83,494||$1,179.90||$472.48||$251.06||$2,557.43||$0.120650||$10,073.60||$14,534.48|
|2017-01 (31)||2017-01-12 12:30 Thu||226.44||44,079||51,834||95,914||$1,302.03||$568.18||$277.83||$2,937.84||$0.115760||$11,102.99||$16,188.88|
|2016-12 (28)||2016-12-16 09:15 Fri||204.12||35,855||43,417||79,272||$1,173.69||$462.18||$232.71||$2,428.10||$0.089610||$7,103.57||$11,400.26|
|2016-11 (30)||2016-11-02 11:45 Wed||240.48||43,268||43,837||87,105||$1,382.76||$557.73||$234.96||$2,668.03||$0.073910||$6,437.93||$11,281.42|
|2016-10 (31)||2016-10-04 08:30 Tue||230.04||34,368||33,988||68,356||$1,322.73||$443.00||$182.18||$2,093.75||$0.070340||$4,808.17||$8,849.83|
|2016-09 (30)||2016-09-14 12:15 Wed||298.80||34,766||46,500||81,266||$1,718.10||$448.13||$249.24||$2,489.18||$0.072590||$5,899.11||$10,803.77|
|2016-08 (31)||2016-08-12 13:30 Fri||250.56||31,194||44,688||75,881||$1,440.72||$402.09||$239.53||$2,324.25||$0.077520||$5,882.33||$10,288.91|
|2016-07 (31)||2016-07-28 12:30 Thu||226.44||26,674||47,872||74,546||$1,302.03||$343.83||$256.59||$2,283.34||$0.080450||$5,997.21||$10,183.00|
|2016-06 (30)||2016-06-07 13:45 Tue||263.52||29,896||41,031||70,927||$1,515.24||$385.35||$219.93||$2,172.49||$0.073440||$5,208.88||$9,501.90|
|2016-05 (31)||2016-05-26 09:15 Thu||282.24||45,409||36,773||82,182||$1,622.88||$585.33||$197.10||$2,517.24||$0.066880||$5,496.35||$10,418.90|
|2016-04 (30)||2016-04-12 10:15 Tue||232.20||36,175||38,177||74,352||$1,335.15||$466.30||$204.63||$2,277.40||$0.075690||$5,627.69||$9,911.17|
|2016-03 (31)||2016-03-09 13:15 Wed||257.04||49,835||47,993||97,828||$1,477.98||$642.38||$257.24||$2,996.47||$0.084560||$8,272.33||$13,646.40|
|2016-02 (29)||2016-02-25 08:45 Thu||227.16||39,964||47,308||87,272||$1,306.17||$515.14||$253.57||$2,673.16||$0.095890||$8,368.56||$13,116.59|
|2016-01 (31)||2016-01-19 10:15 Tue||219.96||44,148||54,760||98,907||$1,264.77||$569.07||$293.51||$3,029.53||$0.145630||$14,403.88||$19,560.76|
|2015-12 (31)||2015-12-22 17:30 Tue||225.72||43,169||46,596||89,764||$1,297.89||$556.44||$249.75||$2,749.48||$0.123110||$11,050.87||$15,904.43|
|2015-11 (30)||2015-11-06 13:30 Fri||276.48||40,498||40,389||80,886||$1,589.76||$522.01||$216.48||$2,477.55||$0.097710||$7,903.40||$12,709.21|
|2015-10 (31)||2015-10-29 12:15 Thu||286.20||45,592||38,113||83,705||$1,645.65||$587.68||$204.28||$2,563.87||$0.074470||$6,233.48||$11,234.97|
|2015-09 (30)||2015-09-29 12:15 Tue||308.88||42,261||50,849||93,110||$1,776.06||$544.75||$272.55||$2,851.97||$0.071260||$6,635.05||$12,080.38|
|2015-08 (31)||2015-08-26 11:30 Wed||231.84||25,943||48,077||74,020||$1,333.08||$334.40||$257.69||$2,267.22||$0.077290||$5,720.98||$9,913.38|
|2015-07 (31)||2015-07-20 12:30 Mon||253.44||28,171||45,338||73,509||$1,457.28||$363.12||$243.01||$2,251.57||$0.095050||$6,987.00||$11,301.98|
|2015-06 (30)||2015-06-09 13:00 Tue||297.36||36,061||46,400||82,461||$1,709.82||$464.83||$248.70||$2,525.79||$0.081120||$6,689.26||$11,638.41|
|2015-05 (31)||2015-05-28 14:00 Thu||318.60||47,060||39,691||86,751||$1,831.95||$606.60||$212.75||$2,657.19||$0.072680||$6,305.09||$11,613.58|
|2015-04 (30)||2015-04-13 12:30 Mon||242.28||43,803||45,929||89,733||$1,393.11||$564.62||$246.18||$2,748.51||$0.088560||$7,946.72||$12,899.15|
|2015-03 (31)||2015-03-12 08:15 Thu||219.24||49,268||54,444||103,711||$1,260.63||$635.06||$291.82||$3,176.68||$0.134320||$13,930.52||$19,294.71|
|2015-02 (9)||2015-02-24 08:45 Tue||211.32||12,318||15,383||27,701||$1,215.09||$158.78||$82.45||$848.47||$0.192190||$5,323.81||$7,628.60|
Given our assumptions that National Grid is the fuel supplier at the site, we can see that their relatively high supply rate explains more than half the bill. The balance is from distribution charges, whether based on the peak kW in the billing period (demand), or some blended calculation that is considered a distribution charge on a usage basis.
We believe that the actual distribution demand charge in effect at Cummings is more likely in the $20/kW range given that we know ICAP capacity charges are $15/kW for FY17, so we expect this table to be updated in the near future with more accurate parameters. AEI considers this a standard utility bill review and will make every effort to help Winthrop reconcile any billing discrepancies and offer guidance on whether or not a better billing rate might apply.
This table will be updated in the course of normal monthly processing as each new month of EPO data becomes available through the rest of the year.
Cummings / Fort Banks Comparison
Cummings has a much cleaner night and weekend setback posture than Fort Banks. Even though Cummings is 50% larger than Fort Banks with higher peak hours (95th percentile of 248.9kW compared with 192.0 for Fort Banks), it had a lower median and average hourly load than Fort Banks.
Fort Banks has an interesting always-on winter load component of about 50kW in January and then to a lesser degree in February and March. A 50kW load running 24x7 for 3 months at $0.13/kWh costs about $14,000 in usage and is responsible for an additional $300 to $1,000/month in demand charges (using a range of $5.75/kW to $20/kW).