Thijs (WP2) – Optimizing scavenger well strategies under parameter uncertainty to maximize allowable freshwater pumping rates in a coastal aquifer, The Netherlands
Scavenger wells offer effective strategies to combat freshwater scarcity and saltwater intrusion in coastal areas by simultaneously extracting fresh and brackish groundwater. This dual extraction intercepts brackish groundwater and limits saltwater upconing, enlarging fresh groundwater supplies and generating additional drinking water resources. While operational scavenger well strategies have been optimized by various approaches, high-resolution field-calibrated […]
Peter (WP6) – SuperADMM: Solving quadratic programs faster with dynamic weighting ADMM
In this paper we develop an accelerated Alternating Direction Method of Multipliers (ADMM) algorithm for solving quadratic programs called superADMM. Unlike standard ADMM QP solvers, superADMM uses a novel dynamic weighting method that penalizes each constraint individually and performs weight updates at every ADMM iteration. We provide a numerical stability analysis, methods for parameter selection […]
Alessia (WP3) – Removal, transport, and transformation of organic micropollutants in managed aquifer recharge: Insights from target and non-target analysis
Managed aquifer recharge (MAR) systems can reduce the stress on groundwater resources by intentionally infiltrating and abstracting (surface) water for drinking water production. Organic micropollutant (OMP) removal and transformation products (TPs) formation in MAR depend on several factors, including their sorption and biodegradation potential. Via target and non-target analyses, we monitored OMPs (parent compounds + […]
Peter (WP6) – Multi-resolution model predictive control with real-time forecasting for water distribution networks
This paper considers the problem of demand prediction for Model Predictive Control (MPC) of drinking water distribution networks (WDNs). The goal is first to analyse how the quality of the demand prediction model affects the MPC control performance under different circumstances. Then, this knowledge is used to define design requirements of such a demand prediction […]
Noelle (WP5) – How is the governance of circular economy of water organized? A systematic review of the literature
Although the concept of circular economy (CE) applied to the field of water (CEW) is relatively new, it offers a promising avenue to challenging water concerns and is increasingly proposed as the way forward in water policy and research. Literature often describes the governance of CEW as a challenge or barrier to CEW. However, the […]
Peter (WP6) – A GPU-aware batched branch and bound method for solving mixed-binary MPC problems
Model Predictive Control is a powerful technique for dynamic optimization in various industrial applications. In many such control applications, some variables are binary in nature, i.e., either on or off. Integrating binary variables into the MPC problem, forming a mixed-binary integer MPC problem, significantly increases the complexity of the problem. A way to handle such […]
Alessio (WP6) – Uncertainty-aware energy storage investment planning through arbitrage in DA and RT markets using novel block orders
Energy Storage Systems (ESS) represent capital-intensive technologies set to play a pivotal role in the future energy landscape. In competitive markets, ESS rely heavily on cross-temporal energy arbitrage within day-ahead markets and across multiple segments, such as day-ahead to real-time markets. However, their revenue potential is heavily reliant on the accuracy of renewable energy generation forecasts, such as wind forecasts, […]
Peter (WP6) – Nonlinear data-driven predictive control design for water distribution networks
In this paper, we present a novel method for controlling Water Distribution Networks (WDNs) using Data-driven Predictive Control (DPC). First, we identify through physical first-principle knowledge that a standard linear predictor is insufficient. However, by mapping the control input as a nonlinear function to a measurable intermediate variable, we can obtain an accurate data-driven predictor. […]
Peter (WP6) – Multilevel parallel GPU implementation of SQP solvers for nonlinear MPC
In recent literature, it has been shown that thenumber of steps in a sequential quadratic programming algorithm for a non-linear model predictive control (NMPC) problem can be greatly reduced by a parallel shooting method. Theefficiency of such a parallel shooting method further dependson how the algorithm is implemented on parallel computingplatforms such as Graphics Processing […]
Peter (WP6) – Real-time demand forecasting and multi-resolution model predictive control for water distribution networks
In this work, we develop a water demand prediction model for MPC that reliably handles unexpected changes from the daily pattern by incorporating a dynamical model over the current measured demand, fitted using machine learning methods. Secondly, in alignment with the new demand estimator, we also propose a multi-resolution MPC prediction horizon. This improves the […]