The A-Z of M&T

Activity-based targeting

The process of estimating expected consumption volumes by reference to production throughput, prevailing weather and other “driving factors”. Comparison between expected and actual consumption reveals randomly-occurring accidental avoidable waste.

Benchmarking

Identifying the things that enable good performance, either by critically comparing the performance of similar installations, or (if no comparable cases exist) identifying past periods of better performance.

Cusum

A time-series chart showing the cumulative deviation from expected consumption. Used for identifying past periods of different behaviour, in the setting of ‘tough but achievable’ targets, and to show cumulative savings.

Driving factor

Anything whose variation causes variations in demand for energy, water, or other consumable resources. Common examples include production throughputs and (for assessing the weather) “degree-day” values.

Expected consumption

Theoretical quantity of energy, water, etc., against which actual consumption can be gauged. Can be calculated in various ways ranging from precedent (same period the year before) to rigorous mathematical modelling from first principles, but most commonly calculated using a simple empirical straight-line relationship between past consumption and corresponding values of an appropriate driving factor.

Fixed demand

The “base load” consumption that is incurred regardless of prevailing weather, production output, etc.; as distinct from the variable component of demand.

Gross production

The favoured measure of production activity in energy-intensive manufacturing, as distinct from net or saleable production. Reflects the fact that it may take as much energy to make unsaleable product as saleable. In thorough implementations, it may be necessary to record gross throughput at each significant stage in a process, to recognise the fact that product may either be diverted to scrap between stages, or else held in buffer storage.

Historical baseline

The characteristic performance of a building, vehicle, or manufacturing process, when first assessed at the outset of an energy management programme.

Interval of assessment

The period between exception reports; commonly weekly for industrial plants but often monthly for dispersed estates of buildings. Daily, per-shift and even “real-time” assessments may be worthwhile in some circumstances. Returns of consumption and related driving factors must at least be synchronised with the assessment interval (although more frequent measurements may be of some diagnostic value).

Justification

If excess consumption cannot be justified for operational reasons, it most likely has an avoidable cause which can be identified and corrected. Activity-based targeting techniques rule out excuses (cold weather, low production volumes) by taking these factors into account in the calculation of excess consumption.

Key performance indicator

The ratio between energy (etc) used, and its presumed driving factor. A very weak and unreliable method of reporting, suitable for high-level management presentations but usually of no value for active management control.

Limit, control

Margin of error allowed in the estimation of expected consumption and used to indicate deviations from target that are significant compared with normal variability.

Moving annual total

A method of reporting in which the most recent 12 months (or 52 weeks) of consumption are stated, regardless of the time of year. Applied to budget tracking, provides a more stable estimate of end-of-year outturn than can be obtained by projecting from results for the year to date.

Norm chart

Time-series graph in which actual and expected consumption histories are co-plotted. Useful for demonstrating that one’s targeting method does indeed predict consumption in a reliable fashion.

Overspend league table

Key weekly (or daily, etc) reporting technique in which monitored streams of consumption are listed in descending order of their apparent unaccountable excess costs. Provides a rational view of where best – if anywhere -- to direct investigations and remedial action. Conveniently accommodates any number of streams, whether of energy, water, or other resources, in a single concise summary that requires no specialist knowledge to produce or interpret.

Precedent-based targeting

Targeting method in which, usually, monthly consumption is gauged against the same month a year before. Weak because it assumes (a) that conditions were indeed comparable in the precedent month and (b) that no waste had occurred which would inflate the target for the period being assessed. Precedent-based targets can also be applied to half-hourly or other high-frequency data, usually by defining a profile “template” on the basis of historical performance.

Quiescent threshold

A simple exception-reporting method for high-frequency data in which of out-of-hours consumption is monitored to ensure that it stays below some chosen level. Higher-than-expected consumption often indicates items left running unnecessarily.

Risk of undetected loss

A formal method of evaluating the cost-effectiveness of expenditure on additional metering. Consumption is disaggregated according to where it is used, and differing percentage losses are assumed according to the nature of the application. Systems with low load factors are presumed to have more scope for undetected waste than those which have to operate continuously close to their maximum rating.

Stream

A measurable flow of energy, water, etc,: typically that taken through an individual submeter but would also include consumptions arrived at by difference (between a main meter and its downstream submeters, say) or by adding two or more flows (such as the oil and gas used in a dual-fuel boiler). A stream need not necessarily be metered: it could be computed from changes in stock level, or estimated from a proxy measure such as hours run. Some practitioners treat driving factors as “streams” as well.

Tabular target

Method of calculating expected consumption when there are two or more unrelated driving factors. The energy requirement per unit being known for each factor, their quantities are tabulated each week (say), each being multiplied by its corresponding coefficient and the results totalled, together with any fixed component of consumption, to give the total expected consumption for the week.

Unexpected excess consumption

Waste of energy, water, or other consumables that occurs at random because of technical faults, human error, and so on. Usually remains hidden unless monitoring and targeting reveals that it has occurred.

Variable component of demand

That portion of demand that varies in direct proportion to the relevant driving factor, as distinct from the fixed (i.e. purely time-related) component.

Weather

Fuel requirements for space heating become higher as the weather becomes colder; energy required for chilling increases as it becomes hotter. The outside-temperature effect is usually reckoned in “degree days”. These are calculated in such a way that heating and cooling energy demands are linearly related to the weekly or monthly heating or cooling degree-day figures for the region in which the building is located. An analogous method can be used for estimating energy demands for humidity control. Methods also exist for calculating indices of humidification and dehumidification demand.

X-Y scatter

Graph in which a stream’s consumption is plotted against the relevant driving factor, say on a weekly basis, and usually with a straight line superimposed to represent the achievable target. A “standard” performance line or the “historical baseline” can also be superimposed, the former being used for budget projection.

Year to date

An inferior method of reporting in which consumption etc are reckoned from the start of the accounting year, discarding information from the year before.

Zing

What your energy-management programme will have once M&T reveals how and where energy is being used, and regularly alerts you to hidden avoidable waste.