• Complex EnPI calculations: When simple EnPIs, as described above, do not
adequately explain what is happening within a process, MVR models can be used
to gain insights into the correlation of several independent influences and thus better
understand the interaction of different loads and subprocesses within the plant.
• Measurement and verification: When energy conservation measures or capital
projects are proposed and justified, they are usually based on some underlying
assumptions about expected savings and gains in energy efficiency. With MVR
analysis, process conditions can be modeled both before and after the project is
completed, allowing plant personnel to view energy savings on a normalized
basis, taking into account changes in production volume, runtime, or any other
variable included in the model to see how well the project has performed.
• Forecasting: Once an MVR analysis has been completed, the resultant model can
be used to make predictions, projections, or forecasts on how both energy
consumption and EnPIs will be impacted over hours, days, weeks, months, or
years. Actual conditions can be tracked in real time and compared with expected
results to alarm plant operators on potential conditions leading to energy waste,
poor EnPI performance, or demand spikes. As a subset of forecasting, MVR
models can be used for budgeting and targeting