Energy Monitoring is primarily a management technique.
Energy Monitoring is primarily a management technique that enables industries to control energy consumption accurately. Energy monitoring and targeting(M&T) is an approach in energy management to eliminate waste, reduce current level of energy use and optimize existing operation efficiency. This is based on the simple management principle “You can’t manage what you can’t measure” . M&T is an activity, which uses information on energy consumption as a basis of control and management of energy use. This activity is a part of broader energy management activity.
Fig-1 : Conceptual Venn diagram of Monitoring & Targeting (M&T) and its overlap with other Energy and business operation activities.
The main phases of M&T are described in figure below:
Energy modeling is mainly divided in two categories. The first one is called forward energy modeling, which consists in the generation of a computer-based simulation of the facility. Forward models are centered in assuming most of the variables to determine the cooling and heating load of the building. This is done by simulating the thermal performance of the facility and estimating the electricity and gas consumption to find its total energy use. The second method is called inverse energy modeling, which is based on the development of a mathematical equation (usually resulting from a regression type of analysis), that relates the energy use with the buildings energy drivers (weather, occupant activity and/or production or a combination of these). Inverse modeling uses the actual energy consumption (electricity or gas) along time rather than the heat interactions to model the building
Monitoring & Targeting with Cumulative Sum Control Algorithm.
The Cumulative Sum of Residuals (CUSUM) algorithm is one of the first methods suggested for statistically detecting changes in engineered processes. It is the most commonly suggested statistical aid for measuring and verifying (M&V) energy saving and for performing M&T.
A CUSUM chart represents the difference between the baseline or the best-fit line (Expected or standard consumption from regression model) and the actual consumption points relative to the same time period of the base line.
There are two types of CUSUM charts. The parametric form and the recurrent form. The parametric form relies on the linear regression to predict energy consumption or the best-fit line.
Typical CUSUM graph will follow trends and indicates the random fluctuation of energy consumption that oscillates around standard or expected consumption. This will continue until something occurs to alter the pattern of consumption as a result of an energy saving measure or increase in energy usage due to fault.
Fig-2 : Example of a typical CUSUM chart ( reff:. Carbon Trust, 2010)
The final part of the analysis in M&T is the creation of energy consumption targets based on the performance observed in the CUSUM chart. It will set a target or threshold cap, within which the energy consumption can fluctuate without showing an alert. These targets are based on the actual performance of the industry energy consumption, they will show its best realistic possible behaviour.