EWave – Water Supply Energy Management System
EWave – Water supply energy management system
The joint research project EWave, supported by the German ministry of education and research (BMBF), aims to develop and implement a prototype for an energy management decision support system based on mathematical optimization.
Over the past few years, requirements for drinking water supply in Germany have become more and more demanding. While the secure supply of high-quality drinking water for the public was the priority during the past decades, rising energy costs and the energy reform being implemented by the German Federal Government now also require that energy is used efficiently. Water suppliers must therefore rise to the challenge of continuing to prioritize a secure supply of high-quality drinking water while coping with the increasing demand for energy efficiency.
A core feature developed and implemented in the EWave project is a mixed-integer nonlinear programming model for the optimization of operative planning including the processes of water collection, treatment, and distribution. This includes a detailed hydraulic model to adequately describe the predicted state of the network as well as further technical and especially operational restrictions. The main objective is to minimize overall energy consumption mainly arising from active raw and pure water pumps. The computation of an energy efficient proposal of the network control is performed for a fixed time period by a receiding horizon strategy, e.g., every 15 minutes for the next 24 hours. To obtain solutions for the resulting mixed-integer nonlinear nonconvex programming problem we combine state of the art methods from the fields of discrete and continuous optimization. On the one hand mixed-integer linear programming relaxations are computed and solved, which draw on piecewise linear approximation of nonlinear nonconvex functions with a predefined error tolerance. Resulting discrete controls such as on/off switching states of pumps and open/closed states of valves are fixed in a complementary stage where optimal control based methods and continuous nonlinear programming techniques are applied.
For more information, please visit our joint project website.
Alexander Martin (EWave project coordinator)
The research collaboration EWave is supported within the funding program “Future-oriented Technologies and Concepts for an Energy-efficient and Resource-saving Water Management – (ERWAS)” by the German Federal Ministry of Education and Research (BMBF) from 2014 to 2017 under the grants 02WER1323A – 02WER1323F.
Angewandte Mathematik 2 (FAU Erlangen-Nuernberg)
Numerik und wissenschaftliches Rechnen (Technische Universität Darmstadt)
Elektrotechnik, Maschinenbau und Technikjournalismus (Hochschule Bonn-Rhein-Sieg)
RWW Rheinisch-Westfälische Wasserwerksgesellschaft mbH
Bilfinger GreyLogix Aqua GmbH
Wissenschaftliches Rechnen, Universität Mannheim
Solving MINLPs on Loosely-Coupled Networks with Applications in Water and Gas Network Optimization.
Ph.D. thesis, University of Erlangen-Nuremberg, 2013.
A. Morsi, B. Geißler, A. Martin.
Mixed Integer Optimization of Water Supply Networks.
In A. Martin, K. Klamroth, J. Lang, G. Leugering, A. Morsi, M. Oberlack, M. Ostrowski, R. Rosen (Eds), Mathematical Optimization of Water Networks, Vol. 162 of International Series of Numerical Mathematics, pp 35-54, Springer Basel, 2012.
O. Kolb, A. Morsi, J. Lang, A. Martin.
Nonlinear and Mixed-Integer Linear Programming.
In A. Martin, K. Klamroth, J. Lang, G. Leugering, A. Morsi, M. Oberlack, M. Ostrowski, R. Rosen (Eds), Mathematical Optimization of Water Networks, Vol. 162 of International Series of Numerical Mathematics, pp 55-65, Springer Basel, 2012.
A. Martin, K. Klamroth, J. Lang, G. Leugering, A. Morsi, M. Oberlack, M. Ostrowski, R. Rosen (Eds).
Mathematical Optimization of Water Networks.
Vol. 162 of International Series of Numerical Mathematics, Springer Basel 2012.
B. Geißler, A. Martin, A. Morsi, L. Schewe.
Using Piecewise Linear Functions for Solving MINLPs.
In Jon Lee and Sven Leyffer (Eds), Mixed Integer Nonlinear Programming, Vol. 154 of The IMA Volumes in Mathematics and its Applications, pp 287-314, Springer, 2012.
B. Geißler, O. Kolb, J. Lang, G. Leugering, A. Martin, A. Morsi.
Mixed Integer Linear Models for the Optimization of Dynamical Transport Networks.
Mathematical Methods of Operations Research, Volume 73, Number 3, pp 339-362, 2011.