No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Correction of Demand Patterns on the Basis of Pressure Measurements
Abstract
Computer models of water distribution systems (WDS) contain patterns of demands. Usually these patterns are obtained on the basis of typical hourly demands for different type of consumers. Experience in calibration of WDS models shows large uncertainties of hourly demands estimated in such a manner. Demands are usually measured for quite long periods of time (e.g. month, week) and give information only on the average base demand. The typical patterns of demands, which are used for the lack of more detailed information, may differ from real hourly demands in time (e.g. during different weekdays) and in space (e.g. because of different daily plans of the residents of different parts of the region). The aim of this investigation was to correct water flow fluxes in District Meter Areas (DMA) on the basis of pressure measurements. Correction of water fluxes has been accomplished for the model calibrated using the same typical patterns for all consumers despite of location. Three different way of the correction have been considered in the paper. All of them have been tested on the operational WDS.
... Results may differ from actual demands in time (e.g. during different weekdays) and in location of demand (e.g. because of different daily movement of the residents at different parts of the region). Great differences between typical and actual demand patterns have been indicated in [2,3]. Thus base demands and corresponding patterns contain large uncertainties which decrease precision of calibration of model. ...
All computer models of water distribution systems (WDS) have to contain information about demands. Usually demands are derived based on customer's water meters weekly or monthly readings. It gives information only about the average demand. Dynamics of hourly, daily and weekly demands are usually estimated based on typical demand patterns of different type of consumer groups like domestic households, hospitals or hotels. Estimation of demand dynamics by this manner inevitably decreases precision of calibration. Calculations show that differences between real-time and typical demand can influence results of calibration. The paper proposes some methods to minimize this influence. Special software has been developed for estimation of real-time water demands in a WDS. Algorithms and software checked on an operational WDS.
The aim was to estimate real-time demands in a water distribution system on the basis of pressure measurements. The task was formulated as an optimization procedure to find water flows correcting typical demands that will minimize differences between measured and modelled pressures. The Levenberg–Marquardt algorithm (LMA) and the Genetic algorithm (GA) were tested to solve the problem. Results showed that the LMA works much faster than the GA. It was also found that the higher the demands the lower is the sensitivity of the results to random errors in pressure measurements. Measurements in an operational WDS were used in calculations.
Experience in calibration of water distribution system (WDS) models shows large uncertainties of demands estimated on the basis of typical hourly values for different types of consumers. The typical dynamics of demands, which are used for the lack of more detailed information, differ from real-time demands in time and in space. It makes it difficult to estimate real-time water fluxes in WDS which are necessary for evaluation of the propagation rate of the contaminated zones in case of deliberate or accidental chemical or biological threats. The aim of this investigation was to test the possibility of estimating real-time water flow fluxes in District Meter Areas (DMAs) on the basis of pressure measurements. Results have been tested on the operational WDS.
Water demands vary and consideration of the probabilistic nature of the variations should lead to more instructive assessments of the performance of water distribution systems. Water consumption data for several households were analysed using the chi-square technique and it was found that distributions worth considering under certain circumstances include the normal and lognormal. Reliability values were calculated for a range of critical demand values and the corresponding confidence levels determined from the probability distributions. Water consumption was assumed to be pressure dependent and the modelling of the water distribution system was carried out accordingly. This peaking factor approach coupled with the statistical modelling of demands provides a more realistic way of incorporating variations in demands in the evaluation and reporting of system performance than the traditional single demand value approach in that the extent to which a network can satisfy any demand and the probability that the demand will occur can be recognized explicitly. The method is illustrated by an example.