Certified Energy Auditor Data Collection and Analysis Questions and Answers

Question 1

An energy auditor is analyzing a building's electricity consumption using a regression model with outside air temperature as the only independent variable. The analysis yields an R-squared (R²) value of 0.65. How should the auditor interpret this result?

Accepted Answer

65% of the variation in electricity consumption is explained by the outside air temperature.

Answer

R-squared, or the coefficient of determination, indicates the proportion of the variance in the dependent variable (energy consumption) that is predictable from the independent variable(s) (outside air temperature). An R² of 0.65 means that 65% of the variability in energy use can be explained by changes in the outside air temperature. It does not mean the model is a bad fit, nor does it perfectly predict consumption, but it is a measure of the model's explanatory power.

Question 2

When analyzing a commercial client's utility bills, an energy auditor notices a significant portion of the monthly electricity cost is attributed to a 'demand charge.' What does this charge typically represent?

Accepted Answer

The highest rate of electricity consumption (kW) recorded during a short interval within the billing period.

Answer

Demand charges are based on the peak rate of energy consumption, measured in kilowatts (kW), during a specific interval (e.g., 15 or 30 minutes) within a billing cycle. This charge compensates the utility for the generation and transmission capacity it must have available to meet the customer's maximum power requirement at any given time, which can be a significant cost component for commercial and industrial customers.

Question 3

An auditor needs to capture the operational profile of a chiller that cycles frequently throughout the day to understand its part-load performance. Which data collection tool and logging interval setting would be most appropriate for this task?

Accepted Answer

A power logger set to a 1- to 5-minute interval.

Answer

To understand the performance of frequently cycling equipment like a chiller, a short logging interval is necessary to capture the changes in power consumption during on/off cycles and varying load conditions. A power logger set to a short interval (e.g., 1, 5, or 10 minutes) can accurately record this dynamic operational profile. Longer intervals, like hourly or daily, would miss these crucial details and average out the data, obscuring the actual performance.

Question 4

Which of the following data analysis techniques is used to normalize a building's energy consumption for weather variations, allowing for a more accurate comparison of energy performance over different time periods?

Accepted Answer

Degree-day analysis

Answer

Degree-day analysis is a common method used to account for the impact of weather on a building's heating and cooling energy consumption. By calculating Heating Degree Days (HDD) and Cooling Degree Days (CDD), an auditor can normalize energy use data, which allows for a fair comparison of consumption between a mild year and a harsh year, or between different months.

Question 5

An energy auditor is developing a calibrated simulation model for an existing building to evaluate potential energy efficiency measures. According to ASHRAE Guideline 14, which two metrics are primarily used to determine if the model is considered well-calibrated against actual utility data?

Accepted Answer

Normalized Mean Bias Error (NMBE) and Coefficient of Variation of the Root Mean Square Error (CV(RMSE))

Answer

ASHRAE Guideline 14, 'Measurement of Energy, Demand, and Water Savings,' specifies statistical criteria for calibrating energy models. The two key metrics are the Normalized Mean Bias Error (NMBE), which indicates the overall bias of the model, and the Coefficient of Variation of the Root Mean Square Error (CV(RMSE)), which measures the variability of the model's predictions. For a model to be considered calibrated, these metrics must typically fall within specified thresholds (e.g., NMBE within ±10% and CVRMSE below 30% for hourly data).

Certified Energy Auditor Certification Practice Test

Certified Energy Auditor Certification Practice Test

Certified Energy Auditor Data Collection and Analysis Questions and Answers