Confidence Limit Analysis and TCLAS software

in Water Distribution Telemetry Systems

Abstract

Efficient control of water distribution systems requires accurate information about its current state. At present in the water industry, modern telemetry hardware systems are beeing employed to meet these needs. Unfortunately, due to financial constraints, it is not practical to measure all variables in the system. Therefore, the information supplied by the telemetry system must be supplemented by pseudomeasurements, such as predictions of consumptions, before a complete operating state of a network can be calculated. These pseudomeasurements are only estimates and hence, contain a great deal of uncertainty. The real meters linked to the telemetry system, although not completely accurate, provide more reliable data. Effectively, they strengthen the monitoring system by reducing reliance on less accurate pseudomeasurements.

Measurement uncertainty clearly has an impact on the accuracy to which state estimates can be calculated. This project has investigated the precise nature and level of this impact [7]. The generic result of this research has been a methodology, termed the Confidence Limit Analysis, which guides the construction of mathematical models of systems which allow for measurement uncertainty [1], [2], [5]. From these models, algorithms are derived which quantify the effect of measurement uncertainty on accuracy of the derived state estimates. Rather than a single deterministic state estimate, the set of all feasible states corresponding to a given level of measurement uncertainty, is calculated. The set is presented in the form of upper and lower bounds for the individual variables, and hence provides limits on the potential error of each variable.

The location of meters about the network strongly influences the accuracy of state estimates. By carefuly designing the meter placement in the telemetry system, it is possible to achieve a much higher level of monitoring accuracy. The design of the metering configuration can be achieved either through an interactive use of our Telemetry Confidence Limit Analysis - TCLAS software [4], [6], [8] or as an off-line optimisation balancing the cost of metering and the required accuracy [3].

Publications

1. Bargiela A., Hainsworth G., Pressure and flow uncertainty in water systems, ASCE Journal of Water Resources Planning and Management, Vol 115, 2, March 1989, pp. 212-229.

2. Bargiela A., Hainsworth G., Pressure and flow uncertainty in water systems, Water Resources Journal, Sept., 1990, pp. 40-48. This paper was selected for a reprint from the ASCE Journal, Vol.115, 2.

3. Hainsworth G., Bargiela A., Optimal telemetry system for water networks, Int. Symposium on Optimal Modeling of Water Distribution Systems, Lexington, K.Y., May 1988.

4. Bargiela A., A graphical interactive software tool for confidence limit analysis, AWWA Conference on Computers and Automation in the Water Industry, Denver, CO, 2-4 April 1989.

5. Bargiela A., Hainsworth G., Confidence limit analysis in water systems, pp. 43-58, in Computer Applications in Water Supply, Vol 2. Systems Optimisation, Coulbeck B., Orr C.H. (Eds.), Research Studies Press U.K., John Wiley and Sons, 1988, ISBN: 0 471917842.

6. Bargiela A., Hainsworth G., Telemetry design with TCLAS software, pp. 1-11, in Computer Applications in Water Supply, Vol 2. Systems Optimisation, Coulbeck B., Orr C.H. (Eds.), Research Studies Press U.K., John Wiley and Sons, 1988, ISBN: 0 471917842.

7. Bargiela A., Managing uncertainty in operational control of water distribution systems", in Integrated Computer Applications, Vol 2, (Ed.) B Coulbeck, J Wiley, 1993, ISBN: 0 471 94232 2, pp 353-363.

8. Hartley J., Bargiela A., An X11 industry standard implementation of the telemetry confidence limit analysis, Poster at Int. Conf. on Integrated Computer Applications, Leicester, 1993

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Last update: 10/4/96

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