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Chillers + cooling towers · energy + water · verified monthly

AI for chiller plants that shows its work.

Gigabiome manages chiller energy and cooling-tower water as one system. Your operators approve every change, and a monthly report, verified to IPMVP (the industry standard for measuring savings), shows what changed in kWh and gallons. Plant Check, free to use, shows how it works on your own BMS export: AI identifies your points, physics checks the result, and every number is calculated directly from your data.

Run Plant Check on your export Apply for the pilot

Starts with an export you already have. No hardware needed to start, no IT project. How onboarding works

Plant Check: free · no account · CSV up to 5 MB · raw file never stored

Scope
chiller kW/ton · tower fan energy · cycles · blowdown · dosing
Mode
advisory; operators approve every change
Proof
monthly report, verified to IPMVP
Stage
pilot program, selecting first plants
Plant Check · replaySAMPLE DATA · LBNL
REPLAY

CHL · 27

  • CHL_CD_FLOW_1
  • CHL_CD_FLOW_2
  • CHL_CD_FLOW_3
  • CHL_COMP_SPD_CTRL_1
  • CHL_COMP_SPD_CTRL_2
  • CHL_COMP_SPD_CTRL_3
  • CHL_CW_FLOW_1
  • CHL_CW_FLOW_2
  • CHL_CW_FLOW_3
  • CHL_POW_1
  • CHL_POW_2
  • CHL_POW_3
  • CHL_SWCD_TEMP_1
  • CHL_SWCD_TEMP_2
  • CHL_SWCD_TEMP_3
  • CHL_RW_TEMP_1
  • CHL_RW_TEMP_2
  • CHL_RW_TEMP_3
  • CHL_STA_1
  • CHL_STA_2
  • CHL_STA_3
  • CHL_RWCD_TEMP_1
  • CHL_RWCD_TEMP_2
  • CHL_RWCD_TEMP_3
  • CHL_SW_TEMP_1
  • CHL_SW_TEMP_2
  • CHL_SW_TEMP_3

CT · 22

  • CT_FAN_SPD_1
  • CT_FAN_SPD_2
  • CT_FAN_SPD_3
  • CT_FAN_SPD_CTRL_1
  • CT_FAN_SPD_CTRL_2
  • CT_FAN_SPD_CTRL_3
  • CT_FLOW_1
  • CT_FLOW_2
  • CT_FLOW_3
  • CT_POW_1
  • CT_POW_2
  • CT_POW_3
  • CT_RW_TEMP_1
  • CT_RW_TEMP_2
  • CT_RW_TEMP_3
  • CT_STA_1
  • CT_STA_2
  • CT_STA_3
  • CT_SW_TEMPSPT
  • CT_SW_TEMP_1
  • CT_SW_TEMP_2
  • CT_SW_TEMP_3

CWL_SEC · 12

  • CWL_SEC_CW_FLOW
  • CWL_SEC_DP
  • CWL_SEC_DPSPT
  • CWL_SEC_LOAD
  • CWL_SEC_PM_POW_1
  • CWL_SEC_PM_POW_2
  • CWL_SEC_PM_SPD_1
  • CWL_SEC_PM_SPD_2
  • CWL_SEC_PM_STA_1
  • CWL_SEC_PM_STA_2
  • CWL_SEC_RW_TEMP
  • CWL_SEC_SW_TEMP

CWL_PRI · 7

  • CWL_PRI_CW_FLOW
  • CWL_PRI_PM_POW_1
  • CWL_PRI_PM_POW_2
  • CWL_PRI_PM_POW_3
  • CWL_PRI_RW_TEMP
  • CWL_PRI_SW_TEMP
  • CWL_PRI_SW_TEMPSPT

CDWL · 6

  • CDWL_CW_FLOW
  • CDWL_PM_POW_1
  • CDWL_PM_POW_2
  • CDWL_PM_POW_3
  • CDWL_RW_TEMP
  • CDWL_SW_TEMP

OA · 2

  • OA_TEMP
  • OA_TEMP_WB

TWV · 1

  • TWV_CTRL

Export as read

Points
77 + timestamp
Rows
2,976
Interval
15 min
Period
Jul 1, 2018 → Jul 31, 2018
Names
as exported, not renamed

23 of 77 mapped · 54 not used

  • Chiller power ×3CHL_POW_1–3
  • Cooling-tower fan power ×3CT_POW_1–3
  • Pump power ×8CDWL_PM_POW_1–3, CWL_PRI_PM_POW_1–3, CWL_SEC_PM_POW_1–2
  • Measured cooling load ×1CWL_SEC_LOAD
  • Chilled-water flow ×1CWL_PRI_CW_FLOW
  • Chilled-water supply temperature ×1CWL_PRI_SW_TEMP
  • Chilled-water return temperature ×1CWL_PRI_RW_TEMP
  • Condenser water to tower ×1CDWL_RW_TEMP
  • Condenser water from tower ×1CDWL_SW_TEMP
  • Cooling-tower fan speed ×1CT_FAN_SPD_1
  • Outdoor wet-bulb temperature ×1OA_TEMP
  • Outdoor dry-bulb temperature ×1OA_TEMP_WB
REFERENCE MAPPING

In Plant Check, the AI proposes a mapping like this and you confirm every row.

How mapping works ↓

Physics checks · mapping taken from point names alone

PHYSICS CHECK
  • Temperatures are plausible6 checked✓ PASS
  • Chilled-water supply is colder than return1 checked✓ PASS
  • Water from the tower is colder than water to it1 checked✓ PASS
  • Wet-bulb is not above dry-bulb1 checked⚠ FLAG

    Wet-bulb is above dry-bulb in 98% of rows, which is physically impossible. The two columns may be swapped or mislabelled in the export.

  • Fan speed set as a fraction stays at or below 11 checked✓ PASS
  • Power readings are not negative14 checked✓ PASS
OA_TEMP → Outdoor dry-bulb temperature (going by the name)OA_TEMP → Outdoor wet-bulb temperature (reference mapping)OA_TEMP_WB → Outdoor wet-bulb temperature (going by the name)OA_TEMP_WB → Outdoor dry-bulb temperature (reference mapping)

The check flags; it never changes a mapping. The reference mapping assigns the pair from the plant's control sequence (evidence below). In Plant Check, you confirm or swap them.

With the reference mapping: 0 of 24 flagged ↓ How the physics checks work

Calculated from the data · no AI involved · reference mapping

  • Share of running hours with the mapped tower fan at ≥95% speed

    Tower 1 fouled: 85.9%

    Same plant, no fault: 9.3%

    Change: +76.6 pts

  • Tower fan energy per ton-hour

    Tower 1 fouled: 96.9 Wh/ton-h

    Same plant, no fault: 67.1 Wh/ton-h

    Change: +44%

  • Tower approach, worst 10% of running intervals

    Tower 1 fouled: 10.7 °F

    Same plant, no fault: 8.8 °F

    Change: +1.9 °F

  • Share of plant electricity used in standby hours

    Tower 1 fouled: 7.4%

    Same plant, no fault: 7.4%

    no change

  • Chiller efficiency (energy-weighted)

    Tower 1 fouled: 1.710 kW/ton

    Same plant, no fault: 1.681 kW/ton

    Change: +1.7%

Same plant, same weather. Fouling lowers cooling tower 1's heat-transfer coefficient (UA) to 65%. How each number is calculated ↓

Tower 1 fan at ≥95% speed · share of running 15-min intervals+76.6 pts

Fault-free run: 9.3%, fouled run: 85.9%

Tower fan energy per ton-hour · all 3 towers+44%

Fault-free run: 67.1 Wh/ton-h, fouled run: 96.9 Wh/ton-h

Chiller kW/ton, energy-weighted · the chillers barely changed+1.7%

Fault-free run: 1.681 kW/ton, fouled run: 1.710 kW/ton

Tower 1 fan speed · every 15-minute interval · July 2018

No faults≥95%: 9.3%
Tower 1 fouled · UA × 0.65≥95%: 85.9%
  • Chillers off
  • Standby (below 5% of peak load)
  • Fan speed while running:
  • <50%
  • 50–80%
  • 80–90%
  • 90–95%
  • ≥95%

Tap, hover or use ↑/↓ to read a day.

Same plant, same weather. Fouling lowers cooling tower 1's heat-transfer coefficient (UA) to 65%.

77 points + timestamp ·2,976 rows ·15-min ·24 checks, 1 flagged on names alone ·25 metrics ·reference mapping

Sample data: LBNL's public simulated chiller plant. Plant Check, replayed on July 2018 with cooling tower 1 fouled (Granderson et al., 2022, CC BY 4.0). Point names and values are the file's own. The mapping here is our reference mapping; in Plant Check the AI proposes one and you confirm it. Methods and data →

How Plant Check works

From 77 point names to numbers you can check

Plant Check runs the same analysis Gigabiome runs on every plant it manages. Here is each step, on a sample file.

Map: AI proposes, you confirm

Every BMS names its points its own way: CHL_POW_1, CDWL_SW_TEMP, CWL_PRI_RW_TEMP. Plant Check's AI reads the point names, value ranges and a few sample rows, and proposes what each point measures and its unit, with a confidence level and a one-line reason. You confirm or change every row. Nothing is calculated until you do.

On this sample file, the AI's proposed mapping matched the engineer's reference mapping on all 78 points.

Where the mapped points sit

REFERENCE MAPPING
Where the mapped points sit in the chiller plantBuilding load, chilled-water loop, three chillers, condenser-water loop and three cooling towers with a shared basin, with each mapped BMS point pinned to its equipment. Make-up, blowdown and chemical feed have no point in the dataset.BUILDINGLOADCH-1CH-2CH-3BASINCT-1CT-2CT-3OUTDOOR AIRCHL_POW_1CHL_POW_2CHL_POW_3CT_POW_1CT_POW_2CT_POW_3CT_FAN_SPD_1CWL_PRI_CW_FLOWCWL_PRI_SW_TEMPCWL_PRI_RW_TEMP8 pump power pointsCWL_SEC_LOADCDWL_RW_TEMPCDWL_SW_TEMPOA_TEMP → wet-bulb (reference)OA_TEMP_WB → dry-bulb (reference)MAKE-UP— no point in datasetCHEMICAL FEED— no point in datasetBLOWDOWN— no point in dataset
  • CDWL_RW_TEMP: Condenser water to tower
  • CDWL_SW_TEMP: Condenser water from tower
  • CHL_POW_1: Chiller power
  • CHL_POW_2: Chiller power
  • CHL_POW_3: Chiller power
  • CT_FAN_SPD_1: Cooling-tower fan speed
  • CT_POW_1: Cooling-tower fan power
  • CT_POW_2: Cooling-tower fan power
  • CT_POW_3: Cooling-tower fan power
  • CWL_PRI_CW_FLOW: Chilled-water flow
  • CWL_PRI_RW_TEMP: Chilled-water return temperature
  • CWL_PRI_SW_TEMP: Chilled-water supply temperature
  • CWL_SEC_LOAD: Measured cooling load
  • OA_TEMP: Outdoor wet-bulb temperature
  • OA_TEMP_WB: Outdoor dry-bulb temperature
  • 8 pump power points: CDWL_PM_POW_1, CDWL_PM_POW_2, CDWL_PM_POW_3, CWL_PRI_PM_POW_1, CWL_PRI_PM_POW_2, CWL_PRI_PM_POW_3, CWL_SEC_PM_POW_1, CWL_SEC_PM_POW_2
  • Make-up, blowdown and chemical feed: no point in dataset.

CHL 27 · CT 22 · CWL_SEC 12 · CWL_PRI 7 · CDWL 6 · OA 2 · TWV 1

This dataset has no make-up, blowdown, conductivity or chemistry points. Energy and water data usually live in separate systems; Gigabiome puts both on one timeline.

23 mapped points, pinned to their equipment. Our reference mapping, written from the dataset's point list.

AI proposal for this file

WRITTEN BY AI · Sep 30, 2026 · UNEDITED

The AI's proposal matched our reference mapping, role and unit, on 78 of 78 points

One run of the AI on this file, shown exactly as returned: not edited or re-run.

Check: physics before math

Before anything is calculated, fixed engineering rules test the mapping against physics: supply colder than return, wet-bulb never above dry-bulb, plausible temperatures and fan speeds, no negative power. A check can flag a mapping; it never changes one.

Physics checks on a mapping by point name

PHYSICS CHECK
  • Temperatures are plausible6 checked✓ PASS

    Every mapped temperature stays within −20 to 140 °F after unit conversion.

    • CWL_PRI_SW_TEMP · 42.8–54.1 °F
    • CWL_PRI_RW_TEMP · 42.9–62.8 °F
    • CDWL_RW_TEMP · 60.2–96.6 °F
    • CDWL_SW_TEMP · 60.0–88.3 °F
    • OA_TEMP_WB · 53.2–94.8 °F
    • OA_TEMP · 51.5–80.4 °F
  • Chilled-water supply is colder than return1 checked✓ PASS

    Flags when supply is warmer than return in more than half the rows.

    • CWL_PRI_SW_TEMP, CWL_PRI_RW_TEMP · 0.0% of rows
  • Water from the tower is colder than water to it1 checked✓ PASS

    Flags when water from the tower is warmer than water to the tower in more than half the rows.

    • CDWL_SW_TEMP, CDWL_RW_TEMP · 0.0% of rows
  • Wet-bulb is not above dry-bulb1 checked⚠ FLAG

    Flags when wet-bulb exceeds dry-bulb in more than 5% of rows.

    Wet-bulb is above dry-bulb in 98% of rows, which is physically impossible. The two columns may be swapped or mislabelled in the export.

    • OA_TEMP_WB, OA_TEMP · 97.8% of rows
  • Fan speed set as a fraction stays at or below 11 checked✓ PASS

    Flags when a fan speed mapped as a fraction exceeds 1.05.

    • CT_FAN_SPD_1 · max 1.00
  • Power readings are not negative14 checked✓ PASS

    Flags a power column with negative readings in more than 1% of rows.

    • CHL_POW_1 · 0.0% of rows negative
    • CHL_POW_2 · 0.0% of rows negative
    • CHL_POW_3 · 0.0% of rows negative
    • CT_POW_1 · 0.0% of rows negative
    • CT_POW_2 · 0.0% of rows negative
    • CT_POW_3 · 0.0% of rows negative
    • CDWL_PM_POW_1 · 0.0% of rows negative
    • CDWL_PM_POW_2 · 0.0% of rows negative
    • CDWL_PM_POW_3 · 0.0% of rows negative
    • CWL_PRI_PM_POW_1 · 0.0% of rows negative
    • CWL_PRI_PM_POW_2 · 0.0% of rows negative
    • CWL_PRI_PM_POW_3 · 0.0% of rows negative
    • CWL_SEC_PM_POW_1 · 0.0% of rows negative
    • CWL_SEC_PM_POW_2 · 0.0% of rows negative
Each dot is one hour (hourly means). The check ran on all 2,976 15-minute rows: “Wet-bulb is above dry-bulb in 98% of rows, which is physically impossible. The two columns may be swapped or mislabelled in the export.” Why the reference mapping swaps the pair: LBNL inventory §1.2, Eq. 3 (tower leaving-water setpoint = wet-bulb + 8 °F). CT_SW_TEMPSPT − OA_TEMP: mean 7.93 °F, sd 0.76. CT_SW_TEMPSPT − OA_TEMP_WB: mean 1.16 °F, sd 4.86. More in Methods.

Calculate: standard engineering math, no AI

Every number is calculated directly from your data, using the mapping you confirmed: energy-weighted kW/ton, lift, tower approach, fan energy per ton-hour, standby energy, and how each varies over running hours. The same data always gives the same numbers.

Calculation sheet · tower 1 fouled

CALCULATED FROM THE DATA
  1. Chiller efficiency (energy-weighted)= chiller kWh ÷ ton-hours= 113,300 kWh ÷ 66,248 ton-h≈ 1.710 kW/ton
  2. Tower fan energy per ton-hour= tower fan kWh ÷ ton-hours × 1,000= 6,422 kWh ÷ 66,248 ton-h × 1,000≈ 96.9 Wh/ton-h
  3. Tower approach, worst 10% of running intervals= 90th percentile of (CDWL_SW_TEMP − OA_TEMP) over running intervals= 10.7 °F
  4. Hours with chillers running= 1,799 running intervals × 0.25 h≈ 450 h
Each line works a figure out from the fouled run's other figures, so you can check the arithmetic yourself.

Tower approach over running intervals

CALCULATED FROM THE DATA
Share of running 15-minute intervals by tower approach (°F). Markers show the median and the worst 10%. Same plant, same weather. Fouling lowers cooling tower 1's heat-transfer coefficient (UA) to 65%.
View as table
Running 15-minute intervals per 0.5 °F bin of tower approach.
Tower approach (°F)No faultsTower 1 fouled · UA × 0.65
4.0–4.520
4.5–5.040
5.0–5.5112
5.5–6.02010
6.0–6.5349
6.5–7.08120
7.0–7.521879
7.5–8.0568156
8.0–8.5574393
8.5–9.0174548
9.0–9.567226
9.5–10.02598
10.0–10.5960
10.5–11.0453
11.0–11.5431
11.5–12.0225
12.0–12.5119
12.5–13.0021
13.0–13.5115
13.5–14.0022
14.0–14.508
14.5–15.004

Median chiller kW/ton by outdoor wet-bulb band

CALCULATED FROM THE DATA
Bands with fewer than 5 running hours are hatched.
View as table
Running hours and median chiller kW/ton per outdoor wet-bulb band, both runs.
Wet-bulb bandHours · No faultskW/ton · No faultsHours · Tower 1 fouled · UA × 0.65kW/ton · Tower 1 fouled · UA × 0.65
55–60 °F10.51.19710.51.213
60–65 °F48.21.34148.21.377
65–70 °F1621.512162.21.533
70–75 °F1331.711132.81.737
75–80 °F951.961952.003
80–85 °F11.84611.874

Explain: AI writes it, but can't invent a number

AI writes a short explanation of the results. It sees the calculated figures, which points are missing and which checks flagged. It cannot type a number itself: it can only cite figures we calculated, and we insert the values. If it writes a number of its own, or cites a figure we never calculated, the whole explanation is rejected. Nothing is patched up after the fact.

The number rule, in action

EXAMPLE DRAFTS

The AI may not write a number, in digits or in words. Where it needs a figure, it cites one we calculated, and we insert the value with its unit.

  • Draft: Approach sits at [Tower approach to wet-bulb (median while running)] while running.

    PUBLISHED

    Reads: Approach sits at 8.7 °F while running.

  • Draft: Approach is about 8 degrees.

    REJECTED

    Why: It typed a number itself.

  • Draft: Approach is about eight degrees.

    REJECTED

    Why: It wrote a number as a word ('eight').

  • Draft: Savings of [dollars saved: not a figure we calculate].

    REJECTED

    Why: It cited a figure we never calculated.

Example drafts we wrote, each run through the same check every Plant Check explanation must pass. The published value is the one calculated for the fouled tower.

AI explanation for this file

WRITTEN BY AI · Sep 30, 2026 · UNEDITED
This simulated plant runs at 1.710 kW/ton at the chillers and 2.909 kW/ton whole-plant, with pumps and a tower running near full fan speed pointing to the biggest areas to examine.

Captured Sep 30, 2026

One run of the AI on this file, shown exactly as returned and put through the same number check: not edited or re-run.
Run it on the sample dataUpload your export

Onboarding

Getting started takes an export, not an IT project

Four steps from first conversation to your first monthly verified report. You start with data your BMS already keeps, and your operators stay in charge throughout.

  1. Step 1

    Send a trend export

    Your BMS already logs chiller power, loop temperatures and flows. Export a month or more as CSV; we send point-by-point instructions for common BMS platforms. No hardware needed to start, no network changes.

    Your timeTypically under an hour

  2. Step 2

    We map and baseline

    We identify every point (the AI proposes, an engineer checks), run the physics checks and build your baseline.

    Your timeOne short call to confirm the point list

  3. Step 3

    Recommendations you approve

    Specific setpoint and water-side recommendations. Your operators accept or reject each one. Nothing is written to your equipment.

    Your decisionAccept or reject each one

  4. Step 4

    Monthly verified report

    kWh and gallons against your baseline, guardrails, and dollars at your tariffs. When you'd rather not send files, a cellular gateway we install, off your IT network, replaces the monthly export.

    You receiveA verified report every month

What we need from you
  • A BMS trend export (or read-only access later)
  • Water-treatment service logs, if you have them
  • Your utility tariffs
What we never do
  • Write to your controls without approval
  • Replace your BMS, your water-treatment company or your qualified person
What we add where it helps
  • Read-only flow meters on make-up and blowdown lines
  • Conductivity sensing where your tower controller doesn't log it
  • A cellular gateway, off your IT network, so reports run without exports

Most exports cover the chiller side well and the water side poorly. We supply and install these, priced separately from the service, so water savings can be measured, not estimated. None of it is needed to start.

Where AI is used

Where AI is used, and where it isn't

AI does two jobs: it proposes what your points are, and it writes the explanation. It never produces a number. Every figure is calculated directly from your data.

Where AI is used in Gigabiome, and where it isn't

  • Identify your points

    In Plant Check
    Done by
    AI proposes what each point is; you confirm every row
    Does it produce numbers?
    No. It only labels points. Nothing is calculated until you confirm.

  • Physics checks

    In Plant Check
    Done by
    Fixed engineering rules
    Does it produce numbers?
    No. They flag a suspect mapping; they never change it.

  • Performance figures

    In Plant Check
    Done by
    Standard engineering formulas, applied to your data
    Does it produce numbers?
    Yes. This is the only step that produces numbers.

  • Written explanation

    In Plant Check
    Done by
    AI, citing only figures we calculated
    Does it produce numbers?
    No. If it writes a number of its own, the explanation is rejected.

  • Baseline and verified savings

    In the monthly service
    Done by
    A weather- and load-normalized baseline, verified to IPMVP
    Does it produce numbers?
    Yes, calculated from each pilot site's own data each month

  • Recommendations

    In the monthly service
    Done by
    An optimizer within guardrails
    Does it produce numbers?
    Will propose changes; none reaches the plant without operator approval

One system

Your chillers and cooling tower share one loop. Gigabiome manages it as one system.

Chiller optimization tunes setpoints and staging for energy. Water treatment manages chemistry and compliance for the tower. Both meet in the condenser loop, where every decision touches energy and water at once: scale on condenser tubes shows up as higher kW/ton, and colder condenser water costs tower fan energy.

Gigabiome looks at both sides together and weighs the trade-offs:

Colder condenser water
trades off against more tower fan energy
Higher cycles
trades off against scale risk
Treatment program
trades off against tube fouling

Every result is measured against a weather- and load-normalized baseline, so a mild month is never mistaken for a saving.

Who typically sees what

Who typically sees what in a chiller plantTwo dashed scopes over the same plant: a chiller optimizer typically sees the chillers, the chilled-water loop and condenser-water temperatures; a water-treatment program typically sees the basin, make-up, blowdown and chemical feed. They overlap over the condenser loop and towers.BUILDINGLOADCH-1CH-2CH-3BASINCT-1CT-2CT-3OUTDOOR AIRMAKE-UPCHEMICAL FEEDBLOWDOWNWhat a chiller optimizer typically seesWhat a water-treatment programtypically seesGigabiome: both, on one timeline
Typical scopes, not a claim about any one vendor. Chiller vs cooling tower, with sources →

Operating model

Advisory first. Verified monthly.

Nothing reaches your plant without an operator's approval, and nothing counts as a saving without a baseline and its uncertainty.

  1. Read: read-only data access
  2. Baseline: weather- and load-normalized
  3. Recommend: setpoints within guardrails
  4. Operator approves: the only path onward
  5. Monthly verified report: kWh and gallons, verified
  6. Then back to Read

Report format — filled in with your plant's data each month

Monthly verified report

  1. 01Energy, verified

    Plant kWhfilled in from your plant's data
    Adjusted baseline kWhfilled in from your plant's data
    Baseline fit CV(RMSE)filled in from your plant's data
    Baseline fit NMBEfilled in from your plant's data
    Fractional savings uncertaintyfilled in from your plant's data

  2. 02Water, verified

    Make-up galfilled in from your plant's data
    Blowdown galfilled in from your plant's data
    Cycles of concentrationfilled in from your plant's data

  3. 03Guardrails

    Scaling indexfilled in from your plant's data
    Biocide residualfilled in from your plant's data
    Legionella resultsfilled in from your plant's data

  4. 04Actions and acceptance

    Recommendationsfilled in from your plant's data
    Acceptedfilled in from your plant's data
    Rejectedfilled in from your plant's data

  5. 05Dollars, reported last

    Energyfilled in from your plant's data
    Demandfilled in from your plant's data
    Water and sewerfilled in from your plant's data
How the monthly report works

Free calculators

  • Cooling tower water balance

    Evaporation, makeup and blowdown for a cooling tower from flow, range and cycles of concentration, with annual gallons and cost.

    Makeup = E × C ÷ (C − 1), E = 0.00085 × Q × R

  • Cycles of concentration savings

    How much makeup water and blowdown you save by raising a cooling tower's cycles of concentration, in gallons and dollars.

    Makeup = E × C ÷ (C − 1), at C now and C target

  • Chiller plant energy cost

    Annual chiller electricity and cost from plant size, full-load hours and kW/ton, and what an efficiency improvement is worth.

    kWh = tons × EFLH × kW/ton

Guides

  1. Chiller vs cooling tower

    Updated 2026-09-29 · 3 sources · 3 min

  2. Cycles of concentration

    Updated 2026-09-29 · 3 sources · 3 min

  3. Condenser approach, tower approach and fouling

    Updated 2026-09-29 · 3 sources · 3 min

  4. NYC cooling tower rules in 2026

    Updated 2026-09-29 · 4 sources · 3 min

  5. Local Law 97 and chiller plants

    Updated 2026-09-29 · 3 sources · 2 min

  6. Measurement and verification for chiller plants

    Updated 2026-09-29 · 3 sources · 3 min

Pilot program: a small number of plants, measured properly

We onboard a limited number of plants at a time: water-cooled chiller plants that run most of the year, such as hospitals, campuses, labs and data rooms. It starts with a BMS trend export you already have, then recommendations your operators approve and a monthly verified report.

  • Water-cooled chillers with cooling towers
  • BMS trends of chiller kW, loop temperatures and flows
  • Tower water logs: conductivity, cycles, chemistry
Tell us about your plantStart with Plant Check