Relative Humidity - NYC Energy Tools

Understand how to measure Relative Humidity. Learn which tools and meter specifications you need to capture valid relative humidity readings. Follow a clear, step-by-step procedure to take multiple spot measurements and record your data for analysis and use in calculations.

Used to measure:

Measurement Overview

What:Hourly measurements of relative humidity.

Why:Used for calculations such as regression models to estimate the heat and energy recovered by an air-to-air heat/energy recovery system.

Duration:Measurements should be taken at one-hour average intervals; do not use instantaneous values. When taking one-hour measurements, the logger detects humidity several times every hour and stores the average value. Sometimes humidity can fluctuate over a one-hour period, and the instantaneous value will not indicate that change.

When:Measurements should be when the system of interest is operating under normal conditions.

Type of Measurement:Direct.

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This technique uses data loggers to take long-term measurements of relative humidity (% RH) at one-hour intervals. This technique can be used to characterize the performance of heat/energy recovery ventilators. Data is used for calculations such as regression models to estimate the heat and energy recovered by an air-to-air heat/energy recovery system. For a more detailed description of how relative humidity data is used in calculations, please refer to the Air-to-Air Heat Transfer calculation methodology.

Relative humidity measurements should be taken at one-hour intervals and paired with the temperature of the system if both variables are required to characterize performance. Measurements should be taken at one-hour average intervals; do not use instantaneous values. When taking one-hour measurements, the logger detects humidity several times every hour and stores the average value. Sometimes humidity can fluctuate over a one-hour period, and the instantaneous value will not indicate that change.

The duration of the long-term measurement should be a minimum of six weeks. Measurements should be when the system of interest is operating under normal conditions.

info Types of Measurements

Direct: Specifies a quantity of the exact item being measured.
Proxy: Provides an indication of the system operation but does not directly measure the quantity in question.

Measurement Tools

The measurement tool required for this procedure is a humidity data logger.

The data loggers should be installed in the ductwork with the air stream. The relative humidity data measured by the logger should be collected as hourly average values; not as instantaneous values. When operating under this method, the logger detects humidity fluctuations across the hour and stores the average value of those fluctuations, rather than the measured relative humidity value at an instantaneous point in time (which does not account for those changes).

info Tip

Most loggers can simultaneously measure temperature and humidity. If both variables are needed, relative humidity and temperature should be recorded at the same time. The same data loggers can be used to measure humidity when monitoring outdoor air temperature or system air temperature.

NYC agency personnel can borrow measurement data loggers, meters, or sensors from our tool library, by selecting tools based on the required measurement duration. See recommended tools found in our library:

HOBO Temp/RH Logger Onset MX2301

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Weatherproof data logger that measures and records temperature and relative humidity in outdoor environments.

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info Logger Setup

Please note that loggers will require setup with a computer or phone using the manufacturer’s proprietary software prior to installation and measurement logging and that older loggers will require the use of a cable to connect to a computer. Refer to the measurement equipment’s user manual for a detailed description of setup requirements.

Measurement Steps

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Prepare Tools

Use the manufacturer’s software to set up and launch the logger(s). Refer to the equipment’s user manual for detailed instructions on how to set up the logger.

Logging interval: 1-hour
Date and time to start logging
Date and time to stop logging
Values to measure: Relative Humidity (%), Temperature (F) if necessary
Sampling interval: 1-second

How to configure the MX2301 logger on HOBOConnect (6 min).

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Install Tools

To accurately measure relative humidity of outside air, use a weatherproof data logger only.

Place the logger inside of the air duct as close as possible to the outside air damper. Alternatively, install the logger on the roof or somewhere with little foot traffic but away from direct sunlight.
To measure relative humidity of the air streams inside of an AHU, place the loggers inside of the ductwork. AHUs typically have panels that open to reach inside of ductwork. There are up to four air streams inside an AHU: outside air, return air, mixed air, and supply/discharge air. A separate data logger should be used for each air stream.
Confirm that the logger is recording, and that the sensor is accurately identifying the airstream’s temperature. If the logger has a screen, check that the temperature value is displayed on the logger screen. If the logger does not have a screen, use the software to connect to the logger and check the temperature it detects.

info Tip

Air handling units come in all sizes, and there is no single method for properly installing all relative humidity loggers. Installing at the mixing plenum/chamber is the most challenging because you are trying to measure the mixed air temperature, which is the combination of return air and outside air.

info Tip

Mixed air relative humidity is particularly challenging to measure, as some mixed air chambers make it difficult to position a data logger for accurate readings. The measurement uncertainty introduced is unknown. Experiment with different logger placements within the air chamber to improve accuracy.

warning Warning

Do not place the loggers near heating or cooling coils. Do not move the logger after it has been installed.

How to install MX2301 MX1101 UX100 temperature loggers (5 min).

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Verify Data Acquisition

Wait 24-48 hours to verify data collection. Return to the location of the measured equipment and use a laptop or a phone with the manufacturer’s proprietary software installed to do the following:

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Do not remove the logger or sensors. If you remove the logger, you may need to start over with the setup and installation process.

If necessary, connect the logger to a laptop or phone via USB cable. Otherwise, use the software to connect with the data logger via Bluetooth.
Analyze the data with a plot graph. This can be done with the proprietary software or Microsoft Excel after exporting the dataset as a .csv file.
Determine whether the measured results align with the expected RH values based on observed weather trends.

How to check data of bluetooth loggers using HOBOConnect (6 min).

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Retrieve Tools and Data

After verifying that the logger is collecting data, do the following:

Allow the logger to collect data for the remainder of the measurement period.
After the measurement period has concluded, remove the logger from the panel.
If necessary, connect the logger to a laptop or phone via USB cable. Otherwise, use the software to connect with the data logger via Bluetooth.
Use the proprietary software to stop the logger and end data collection.
Download all data from the logger and save the file in the .csv file format for analysis.

How to extract data from the logger and convert to csv on HOBOConnect (5 min).

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Select Calculator(s)

These calculators will output estimated annual energy consumption or heat transfer for relevant components using measured data. Download the calculator for your specific component’s measurement strategy and add your measurement data.

Fans and Motors

For AHU, Condenser, Burner and Cooling Tower Fans and Motors.

Variable Speed Fan Energy (kW) Calculator

Estimates annual electricity usage of two variable-speed fan motors using power data.

Measurements Required:

Download Calculator download

Calculation Methodology

This calculation is for VFD-controlled fans that are operated at different speeds proportional to the heating/cooling load. Because the heating/cooling load of a facility is mainly affected by outdoor air temperature (OAT), this data must be collected as well. Measured input data include average hourly power draw (kW) and average hourly OAT.

The calculator uses the following methodology to compute annual energy consumption of a variable speed fan:

Perform second-order polynomial regression analysis of true RMS power as a function of OAT. (Worksheet: “Step 3. Regression”) for supply and return fans.

\begin{equation} P_{f}(OAT) = a*OAT^{2} + b*OAT + c \end{equation}

Where,

$P_{f} =$ Average hourly true RMS Power for either supply or return fan, f, kW

$a,b,c =$ Regression coefficients

$OAT_{f} =$ Outdoor air temperature for either supply or return fan, f

Determine if the supply and return motors are on or off at each measurement interval based on the input true RMS power values (Worksheets: “Step 4. Schedule Calcs”).

\begin{equation} On_{f}(t_{f}) = \begin{cases} 1 & \text{if } P_{f}(t_{f}) > 0\\ 0 & otherwise \end{cases} \end{equation}

Where,

$P_{f}(t_{f}) =$ Measured power

$On_{f}(t_{f}) =$ Motor is on at time, $t_{f}$ for either supply or return fan, f, binary

Average hourly % motor is on for each hour of each day of the week, for supply and return fan motors (Worksheet: “Step 5. Daily Avg Schedule Calc”).

\begin{equation} \overline{\%FanOn}_{d,h,f} = \frac{\sum_{n_{f}=1}^{N_{f}(d,h)} On_{f}(t_{f})}{N_{f}(d,h)} \end{equation}

Where,

$\overline{\%FanOn}_{d,h,f} =$ Average % time motor is on per hour for given day of week, d, and hour of day, h, for either supply or return fan, f, %

$N_{f}(d,h) =$ Total number of measured data points that fall on day of week, d, and hour od day, h, for either supply or return fan, f

$n_{f} \in t_{f}(d,h) =$ Index for subset of measured data points that fall on day of week, d, and hour of day, h, for either supply or return fan, f

Calculated energy (kWh) every hour based on normalized annual OAT for the supply and return fan motors (Worksheet: “Step 6. Energy Calcs,” column F & G).

\begin{equation} E_{f} = \sum_{t=1}^{8760} P_{f}(OAT'(t))*\overline{\%FanOn}_{d,h,f}(t) \end{equation}

Where,

$E_{f} =$ Annual energy usage for either supply or return fan, f, kWh

$OAT'(t) =$ Climate normal outdoor air temperature from National Weather Service at station closest to site, F

Total energy used by Fan Motor (Worksheet: “Step 7. Results”).

\begin{equation} E = E_{supply} + E_{return} \end{equation}

Where,

$E =$ Total energy usage for the Fan Motor, kWh

Constant Speed CT Fan Energy (Runtime) Calculator

Estimates annual electricity consumption for up to four (4) constant speed cooling towers, using motor runtime data.

Measurements Required:

Download Calculator download

Calculation Methodology

This calculation is for a cooling tower with constant-speed fans. Measured input data include spot measurements for true power and motor operational time per hour, as measured by motor on/off loggers on each fan in the tower.

The calculator uses the following methodology to compute annual energy consumption of a constant speed cooling tower fan:

Convert seconds on per hour to average energy per hour (Worksheet: “Step 2. Energy Calcs”). Repeat for all fans and then sum to get a total for the cooling tower. Note that since the data loggers cannot be perfectly synced, the time stamp for the dataset for each fan will be different. The workbook time-aligns the datasets.

\begin{equation} \overline{E}_{f}(t) = \frac{On_f(t)*P_f}{3600} \end{equation}

\begin{equation} \overline{E}(t) = \sum_{f=1}^{F} \overline{E}_{f}(t) \end{equation}

Where,

$\overline{E}_{f}(t) =$ Average hourly fan motor energy on for each fan, f, kWh

$t =$ Time index

$On_{f}(t) =$ Measured time that motor is on for each fan, f, seconds

$P_{f} =$ One-time power measurement for each fan, f, kW

$\overline{E}(t) =$ Total average energy of all fan motors, kWh

$F =$ Total number of fans

Wet-bulb temperature is calculated from the measured dry-bulb temperature and measured relative humidity with the following empirical equation (Worksheet: “Step 3 Wetbulb Calcs”)[1].

\begin{equation} T_{wb} = T_{db}tan^{-1}[0.151977(RH+8.313659)^{1/2}] \end{equation}

\begin{equation*} +tan^{-1}(T_{db}+RH) \end{equation*}

\begin{equation*} -tan^{-1}(RH-1.676331)+0.00391838(RH)^{3/2} \end{equation*}

\begin{equation*} *tan^{-1}(0.023101*RH) - 4.686035 \end{equation*}

Where,

$T_{wb} =$ Wet-bulb temperature, C

$T_{db} =$ Dry-bulb temperature, C

$RH =$ Relative Humidity, %

To model the total fan energy at different wet-bulb temperatures, a second-order polynomial regression model is fitted, with total fan energy as a function of wet-bulb temperature (Worksheet: “Step 4 Regression”).

\begin{equation} E(T_{wb}) = a*T_{wb}^{2} + b*T_{wb} + c \end{equation}

Where,

$E(T_{wb}) =$ Average hourly fan energy, kWh

$a,b,c =$ Regression Coefficients

Calculate operating hours (Worksheet: “Step 5 Daily Op Hrs”).

\begin{equation} On(t) = \begin{cases} 1 & \text{if } \overline{E}(t) > 0\\ 0 & \text{if } \overline{E}(t) = 0 \end{cases} \end{equation}

\begin{equation} \overline{On}_{d,h} = \begin{cases} 1 & \text{if } \overline{E}(n) > 0 \text{ for any } n \in N(d,h) \\ 0 & 0 \end{cases} \end{equation}

Where,

$On(t) =$ Cooling tower fans are on, binary

$\overline{On}_{d,h} =$ Cooling tower is on for a given day of the week, d, and hour of the day, h, binary

$N(d,h) =$ Total number of measured data points that fall on day of week, d, and hour of the day, h

$n \in N(d,h) =$ Index for the subset of measured data points that fall on day of week, d, and hour of the day, h

Calculate energy used for full year for each fan (Worksheet: “Step 6 Results”).

\begin{equation} E = \sum_{t=1}^{8760} \overline{On}_{d,h}(t) * CoolingSeason(t) * E(T_{wb}(t)) \end{equation}

Where,

$E =$ Annual energy, kWh

$CoolingSeason(t) =$ Does the given hour, t, fall within the cooling season, binary

Variable Speed CT Fan Energy (kW) Calculator

Estimates annual electricity consumption for multiple variable speed cooling tower fans, using power data.

Measurements Required:

Download Calculator download

Calculation Methodology

This calculation is for a cooling tower with variable-speed fans. Measured input data is average hourly power draw (in kW) as measured by a power logger for one fan in the cooling tower. It is assumed that all the remaining fans are run at the same speed.

The calculator uses the following methodology to compute annual energy consumption of a variable speed cooling tower fan:

Total energy for each hour (Worksheet: “Step 2 Energy Calcs”). Since the measured power value (kW) is the average for an hour, it is equivalent to the energy for the hour (kWh).

\begin{equation} \overline{E}(t) = \overline{E}_{1}(t) * F \end{equation}

Where,

$\overline{E}_{1}(t) =$ Average hourly fan motor energy for the measured fan, kWh

$\overline{E} =$ Total average energy of all fan motors, kWh

$F =$ Total number of fans in the cooling tower

$t =$ Time index

Wet-bulb temperature is calculated from the measured dry-bulb temperature and measured relative humidity with the following empirical equation (Worksheet: “Step 3 Wetbulb Calcs”)[1].

\begin{equation} T_{wb} = T_{db}tan^{-1}[0.151977(RH+8.313659)^{1/2}] \end{equation}

\begin{equation*} +tan^{-1}(T_{db}+RH) \end{equation*}

\begin{equation*} -tan^{-1}(RH-1.676331)+0.00391838(RH)^{3/2} \end{equation*}

\begin{equation*} *tan^{-1}(0.023101*RH) - 4.686035 \end{equation*}

Where,

$T_{wb} =$ Wet-bulb temperature, C

$T_{db} =$ Dry-bulb temperature, C

$RH =$ Relative Humidity, %

To model the total fan energy at different wet-bulb temperatures, a second-order polynomial regression model is fitted, with total fan energy as a function of wet-bulb temperature (Worksheet: “Step 4 Regression”).

\begin{equation} E(T_{wb}) = a*T_{wb}^{2} + b*T_{wb} + c \end{equation}

Where,

$E(T_{wb}) =$ Average hourly fan energy, kWh

$a,b,c =$ Regression Coefficients

Calculate operating hours (Worksheet: “Step 5 Daily Op Hrs”).

\begin{equation} On(t) = \begin{cases} 1 & \text{if } \overline{E}(t) > 0\\ 0 & \text{if } \overline{E}(t) = 0 \end{cases} \end{equation}

\begin{equation} \overline{On}_{d,h} = \begin{cases} 1 & \text{if } \overline{E}(n) > 0 \text{ for any } n \in N(d,h) \\ 0 & 0 \end{cases} \end{equation}

Where,

$On(t) =$ Cooling tower fans are on, binary

$\overline{On}_{d,h} =$ Cooling tower is on for a given day of the week, d, and hour of the day, h, binary

$N(d,h) =$ Total number of measured data points that fall on day of week, d, and hour of the day, h

$n \in N(d,h) =$ Index for the subset of measured data points that fall on day of week, d, and hour of the day, h

Calculate energy used for full year for each fan (Worksheet: “Step 6 Results”).

\begin{equation} E = \sum_{t=1}^{8760} \overline{On}_{d,h}(t) * CoolingSeason(t) * E(T_{wb}(t)) \end{equation}

Where,

$E =$ Annual energy, kWh

$CoolingSeason(t) =$ Does the given hour, t, fall within the cooling season, binary

Troubleshooting

This section provides some troubleshooting tips for the most common issues with tool installation.

Verify that the logger is calibrated. Re-calibrate the tool if necessary. Adjust the placement of the logger and ensure that the logger is installed correctly and that there is no interference from heating and cooling coils.