Refine
Year of publication
Document Type
- Conference Proceeding (20)
- Part of a Book (11)
- Article (10)
- Book (1)
Language
- English (42) (remove)
Keywords
- MINLP (5)
- Engineering optimization (4)
- Optimization (3)
- Powertrain (3)
- Technical Operations Research (3)
- Energy efficiency (2)
- Experimental validation (2)
- Optimal Topology (2)
- Process engineering (2)
- Pump System (2)
- Ventilation System (2)
- Water (2)
- Water distribution system (2)
- mathematical optimization (2)
- BEV (1)
- Booster Stations (1)
- Buffering Capacity (1)
- Building Automation (1)
- CO2 (1)
- Carbon Dioxide (1)
- Case Study (1)
- Case study (1)
- Chance Constraint (1)
- Controller Parameter (1)
- Cooling system (1)
- Discrete Optimisation (1)
- Drinking Water Supply (1)
- Education (1)
- Efficiency (1)
- Efficiency optimization (1)
- Energy (1)
- Energy Disaggregation (1)
- Engineering Application (1)
- Engineering optimisation (1)
- Gearbox (1)
- Global optimization (1)
- Graph Theory (1)
- Home Assistant (1)
- Home Automation Platform (1)
- Industrial optimisation (1)
- Latin Hypercube Sampling (1)
- Level Control System (1)
- MILP (1)
- Machine Learning (1)
- Machine learning (1)
- Mixed Integer Programming (1)
- Mixed-Integer Nonlinear Optimisation (1)
- Mixed-integer nonlinear black-box optimization (1)
- Mixed-integer nonlinear problem (1)
- Mixed-integer nonlinear programming (1)
- Mixed-integer programming (1)
- Multi-criteria optimization (1)
- Network (1)
- Network design (1)
- OR 2019 (1)
- Open Source (1)
- Optimal Closed Loop (1)
- Paper recycling (1)
- Piecewise Linearization (1)
- Piecewise linearization (1)
- Product family optimization (1)
- Pumping systems (1)
- Resilience (1)
- Resilience Assessment (1)
- Resilience assessment (1)
- Resilience metric graph theory (1)
- Resilient infrastructure (1)
- Similarity Theory (1)
- Smart Building (1)
- Solver Per- formance (1)
- Stochastic Programming (1)
- System Design (1)
- System Design Problem (1)
- TGA (1)
- Technical Operation Research (1)
- Uncertainty (1)
- Validation (1)
- WLTP (1)
- Water Distribution (1)
- Water Supply Networks (1)
- Water Supply System (1)
- Water supply system (1)
- anticipation strategy (1)
- availability (1)
- business analytics (1)
- decision analytics (1)
- design of technical systems (1)
- digital economy (1)
- energy efficiency (1)
- energy transfer (1)
- fault detection (1)
- genetic algorithm (1)
- global optimization (1)
- heating system (1)
- legal obligations (1)
- mixed-integer linear programming (1)
- optimization (1)
- product liability (1)
- programming (1)
- remote sensing (1)
- resilience (1)
- slum classification (1)
- stochastic optimization (1)
- sustainability (1)
- system optimization (1)
- system synthesis (1)
- technical operations research (1)
- water supply design (1)
- water supply system (1)
Institute
- Fachbereich Elektrotechnik und Informationstechnik (42) (remove)
Algorithmic design and resilience assessment of energy efficient high-rise water supply systems
(2018)
High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building.
In order to reduce energy consumption of homes, it is important to make transparent which devices consume how much energy. However, power consumption is often only monitored aggregated at the house energy meter. Disaggregating this power consumption into the contributions of individual devices can be achieved using Machine Learning. Our work aims at making state of the art disaggregation algorithms accessibe for users of the open source home automation platform Home Assistant.
To increase pressure to supply all floors of high buildings with water, booster stations, normally consisting of several parallel pumps in the basement, are used. In this work, we demonstrate the potential of a decentralized pump topology regarding energy savings in water supply systems of skyscrapers. We present an approach, based on Mixed-Integer Nonlinear Programming, that allows to choose an optimal network topology and optimal pumps from a predefined construction kit comprising different pump types. Using domain-specific scaling laws and Latin Hypercube Sampling, we generate different input sets of pump types and compare their impact on the efficiency and cost of the total system design. As a realistic application example, we consider a hotel building with 325 rooms, 12 floors and up to four pressure zones.
The overall energy efficiency of ventilation systems can be improved by considering not only single components, but by considering as well the interplay between every part of the system. With the help of the method "TOR" ("Technical Operations Research"), which was developed at the Chair of Fluid Systems at TU Darmstadt, it is possible to improve the energy efficiency of the whole system by considering all possible design choices programmatically. We show the ability of this systematic design approach with a ventilation system for buildings as a use case example.
Based on a Mixed-Integer Nonlinear Program (MINLP) we model the ventilation system. We use binary variables to model the selection of different pipe diameters. Multiple fans are model with the help of scaling laws. The whole system is represented by a graph, where the edges represent the pipes and fans and the nodes represents the source of air for cooling and the sinks, that have to be cooled. At the beginning, the human designer chooses a construction kit of different suitable fans and pipes of different diameters and different load cases. These boundary conditions define a variety of different possible system topologies. It is not possible to consider all topologies by hand. With the help of state of the art solvers, on the other side, it is possible to solve this MINLP.
Next to this, we also consider the effects of malfunctions in different components. Therefore, we show a first approach to measure the resilience of the shown example use case. Further, we compare the conventional approach with designs that are more resilient. These more resilient designs are derived by extending the before mentioned model with further constraints, that consider explicitly the resilience of the overall system. We show that it is possible to design resilient systems with this method already in the early design stage and compare the energy efficiency and resilience of these different system designs.
The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design.
In order to maximize the possible travel distance of battery electric vehicles with one battery charge, it is mandatory to adjust all components of the powertrain carefully to each other. While current vehicle designs mostly simplify the powertrain rigorously and use an electric motor in combination with a gearbox with only one fixed transmission ratio, the use of multi-gear systems has great potential. First, a multi-speed system is able to improve the overall energy efficiency. Secondly, it is able to reduce the maximum momentum and therefore to reduce the maximum current provided by the traction battery, which results in a longer battery lifetime. In this paper, we present a systematic way to generate multi-gear gearbox designs that—combined with a certain electric motor—lead to the most efficient fulfillment of predefined load scenarios and are at the same time robust to uncertainties in the load. Therefore, we model the electric motor and the gearbox within a Mixed-Integer Nonlinear Program, and optimize the efficiency of the mechanical parts of the powertrain. By combining this mathematical optimization program with an unsupervised machine learning algorithm, we are able to derive global-optimal gearbox designs for practically relevant momentum and speed requirements.
The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example
system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient
system behaviour.