Demand uncertainty In modelling WDS: scaling laws and scenario generation

Water distribution systems (WDS) are critical infrastructures that should be designed to work properly in different conditions. The design and management of WDS should take into account the uncertain nature of some system parameters affecting the overall reliability of these infrastructures. In this context, water demand represents the major source of uncertainty. Thus, uncertain demand should be either modelled as a stochastic process or characterized using statistical tools. In this paper, we extend to the 3rd and 4th order moments the analytical equations (namely scaling laws) expressing the dependency of the statistical moments of demand signals on the sampling time resolution and on the number of served users. Also, we describe how the probability density function (pdf) of the demand signal changes with both the increase of the user’s number and the sampling rate variation. With this aim, synthetic data and real indoor water demand data are used. The scaling laws of the water demand statistics are a powerful tool which allows us to incorporate the demand uncertainty in the optimization models for a sustainable management of WDS. Specifically, in the stochastic/robust optimization, solutions close to the optimum in different working conditions should be considered. Obviously, the results of these optimization models are strongly dependent on the conditions that are taken into consideration (i.e. the scenarios). Among the approaches for the definition of demand scenarios and their probability-weight of occurrence, the moment-matching method is based on matching a set of statistical properties, e.g. moments from the 1st (mean) to the 4th (kurtosis) order

Demand response within the energy-for-water-nexus - A review. ESRI WP637, October 2019

A promising tool to achieve more flexibility within power systems is demand re-sponse (DR). End-users in many strands of industry have been subject to research up to now regarding the opportunities for implementing DR programmes. One sector that has received little attention from the literature so far, is wastewater treatment. However, case studies indicate that the potential for wastewater treatment plants to provide DR services might be significant. This review presents and categorises recent modelling approaches for industrial demand response as well as for the wastewater treatment plant operation. Furthermore, the main sources of flexibility from wastewater treatment plants are presented: a potential for variable electricity use in aeration, the time-shifting operation of pumps, the exploitation of built-in redundan-cy in the system and flexibility in the sludge processing. Although case studies con-note the potential for DR from individual WWTPs, no study acknowledges the en-dogeneity of energy prices which arises from a large-scale utilisation of DR. There-fore, an integrated energy systems approach is required to quantify system and market effects effectively

The safety case and the lessons learned for the reliability and maintainability case

This paper examine the safety case and the lessons learned for the reliability and maintainability case