pySIMDEUM - An open-source stochastic water demand end-use model

[EN] Water demand is a crucial input parameter in water distribution system analysis because it can fluctuate over various temporal and spatial scales. In the past, researchers developed stochastic models that can provide realistic consumption patterns for simulations to account for those demand dynamics. Parameters for stochastic models are usually retrieved by fitting these models on smart water meter data. The stochastic demand model SIMDEUM uses an entirely different approach by generating highly realistic water demands based on (country-specific) statistical information only, without the need for measurements. While this approach makes SIMDEUM widely applicable in the water sector, its widespread usage within the community has been hindered due to its software implementation and availability. We produced pySIMDEUM, an open-source and object-oriented implementation of the SIMDEUM software in the popular and freely available programming language Python. The pySIMDEUM software package is not only publicly available for usage within the water field — it is also intended to build the cornerstone of a widespread pySIMDEUM community of active developers. We want to use the WDSA/CCWI conference to address interested researchers or practitioners in the water sector and invite them to contribute to the software package as active part of the pySIMDEUM community. We will show SIMDEUM’s history and past applications, the mathematical approach behind SIMDEUM and pySIMDEUM, where to download and install the pySIMDEUM package, the structure of the program, and a minimal example of how easily pySIMDEUM can be used to generate realistic stochastic water demand patterns from scratch. Furthermore, we will highlight possible future applications of the new pySIMDEUM tool. These applications include automatic parametrisation of pySIMDEUM parameters on smart meter data, coupling stochastic demands directly with hydraulic solvers, or how to enable city-scale stochastic demand simulations.Steffelbauer, D.; Hillebrand, B.; Blokker, M. (2024). pySIMDEUM - An open-source stochastic water demand end-use model. Editorial Universitat Politècnica de València. https://doi.org/10.4995/WDSA-CCWI2022.2022.1477

Modeling the influence of district heating systems on drinking water temperatures in domestic drinking water systems within domestic properties

In this research, we investigated the influence of the heating of drinking water in the connection pipe under the influence of nearby district heating and the effect this has on water temperatures throughout the domestic drinking water system (DDWS) of a typical Dutch domestic property. We found that stagnant water in the connection pipe warms up fast, reaching the surrounding ground temperature in about 15 min, and these temperatures can be found throughout the house at taps such as the shower and the kitchen tap. Flowing water in the connection pipe is also, depending on the pipe length, heated up several degrees. The prevention of high temperatures in the soil around the connection pipe is the best measure to prevent high drinking water temperatures at the taps.Sanitary Engineerin