app_longitudinal_BM

Longitudinal benchmarking application

Introduction

Longitudinal benchmarking compares the energy used by a building system or component, against its own performance over time. It aims:

• To determine if energy use has increased or decreased over time.
• To watch for unexpected changes.
• To set goals for future performance.

Pseudo-code: Logitudinal benchmarking

Longitudinal benchmarking aggregates electric load and gas usage on a yearly basis.

Sample explanatory text: "A persistent or large increase in annual energy use indicates possible efficiency opportunities. Conversely, a significant efficiency improvement would result in a downward trend of decreasing bar height."

Program plotLongitudinalBenchmark

• Get inputs:
  • times, vector of date-times (typically a time-specific format).
  • loads, vector of power data recorded at times (float).
  • areaFt2, floor area of corresponding space [ft^2] (float).
• Assume:
  • Data include at least two years of observations.
• Aggregate power data into annual energy intensity:
  • Separate loads into subsets of data that are 12 months long. Mark years so that the last year ends on the last day in times. For example, if the last observation is on 12-June, then every year should end on 12-June. TODO: Is this true in phase-2 code? Possibly it aggregates by calendar year.
  • Set years to an empty list.
  • Set yearlyEnergyIntensities to an empty list.
  • For each year currYear, call the appropriate data currYearLoads:
    • Set currYearEnergy to the time integral of currYearLoads.
    • Set currYearIntensity to the energy intensity, i.e., to currYearEnergy / areaFt2.
    • Append currYear to years.
    • Append currYearIntensity to yearlyEnergyIntensities.
• Make the longitudinal benchmarking plot:
  • Make a bar chart, showing y = yearlyEnergyIntensities as a function of category = years.