Optimizing the pump schedule of water distribution systems using a deep learning meta-model: To what extent can algorithm unrolling optimize the pump schedule of an urban water distribution system?

This thesis investigates the integration of algorithm unrolling and genetic algorithms (GA) for optimizing pump scheduling in water distribution systems (WDS), a critical component for ensuring energy-efficient water delivery. In the context of modern civilization’s reliance on clean, affordable water for diverse uses, the operation of a WDS,...

Pumping when the wind blows: Demand response in the Dutch delta

This thesis investigates the potential of a large pumping station in IJmuiden, the Nether-lands, for participating in Demand Response. Due to climate change, renewable energy is onthe rise. The intermittency of energy, together with its unpredictable supply, are a big hurdlefor the energy transition. Two methods are promising solutions to this...

Convex modeling of pumps in order to optimize their energy use

This study presents convex modeling of drainage pumps so that real-time control systems can be implemented to minimize their energy use. A convex model is built based on pump curves and then used in mixed-integer optimization to allow pumps to be turned on or off. It is implemented as an extension to the open source software package RTC-Tools...