HOT|COOL NO. 4/2017 "Technical Innovation and Optimization"

P22

THE MODEL BEHIND THE TOOL The calculation model, illustrated in Figure 1, shows how all the meter readings are used (T,Q) together with a map of the distribution network, to deduce the flow and temperature, (t,q) everywhere in the distribution network. All meters share the same supply unit, and thereby temperature (t_0), which is the starting point of the model.

These outliers are depicting large deviations in the model estimations from the measured data, and indicate customers, or parts of the distribution network, where further attention is needed. Such deviations arise when the model parameters do not match the actual situation.

If the temperatures are propagated through the entire network, and then compared to the actual measured values at the network end points (T,Q), the result is distributed as illustrated in the histogram. Ideally, if the model exactly matches the reality, this histogram should only consist of one single bar (that is, a very narrow distribution). However, because of measurement uncertainties, model uncertainties, missing data etc., the result is a normal distribution with some amount of variation that indicates how well the model fits the data. A certain amount of variation is naturally expected, however, histogram outliers often appear indicating unexpected behaviour.

Figure 1: Illustration of the calculation model in a simplified version. All meter readings come into play simultaneously, and the model then makes it possible to compare the individual meter readings and thereby determine which readings are outliers. Furthermore, the model makes it possible to calculate e.g. flow and temperatures everywhere in the distribution network with high precision because of the large amount of meters connected in all network segments.

Figure 2: Example of calculation output from a specific network branch section superimposed on a map. This shows how the utility’s assumptions match the actual state in the network and reveals opportunities for network optimisation, e.g. the actual coincidence factor or a measure of how much the pipe capacity is utilised. The red circles indicate meters with a measured forward temperature lower than expected, and thereby represents an unanticipated high heat loss. The blue circles indicate meters that measure a higher forward temperature than expected. The top text box illustrates a virtual probe used to “measure” the heat load, forward and return temperature of this particular branch in the distribution network. The pipe coloring indicates the return temperature value (the brighter the color the higher return temperature). However, the pipe coloring could also show the heat load, the flow velocity etc. in order to get a clear overview of the distribution network state.

For further information please contact: Kamstrup A/S Att. Steen Schelle Jensen, Head of Product Management Or Morten Karstoft Rasmussen, Data Scientist

+45 8993 1191 / ssj@kamstrup.com +45 8993 1606 / mok@kamstrup.com kamstrup.com

Industrivej 28, Stilling DK-8660 Skanderborg

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