TY - CHAP A1 - Altherr, Lena A1 - Conzen, Max A1 - Elsen, Ingo A1 - Frauenrath, Tobias A1 - Lyrmann, Andreas ED - Reiff-Stephan, Jörg ED - Jäkel, Jens ED - Schwarz, André T1 - Sensor retrofitting of existing buildings in an interdisciplinary teaching project at university level T2 - Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel N2 - Existing residential buildings have an average lifetime of 100 years. Many of these buildings will exist for at least another 50 years. To increase the efficiency of these buildings while keeping costs at reasonable rates, they can be retrofitted with sensors that deliver information to central control units for heating, ventilation and electricity. This retrofitting process should happen with minimal intervention into existing infrastructure and requires new approaches for sensor design and data transmission. At FH Aachen University of Applied Sciences, students of different disciplines work together to learn how to design, build, deploy and operate such sensors. The presented teaching project already created a low power design for a combined CO2, temperature and humidity measurement device that can be easily integrated into most home automation systems KW - Building Automation KW - Smart Building KW - CO2 KW - Carbon Dioxide KW - Education Y1 - 2023 SN - 978-3-910103-01-6 U6 - http://dx.doi.org/10.33968/2023.04 N1 - 19. AALE-Konferenz. Luxemburg, 08.03.-10.03.2023. BTS Connected Buildings & Cities Luxemburg (Tagungsband unter https://doi.org/10.33968/2023.01) SP - 31 EP - 40 PB - le-tex publishing services GmbH CY - Leipzig ER - TY - CHAP A1 - Altherr, Lena A1 - Döring, Bernd A1 - Frauenrath, Tobias A1 - Groß, Rolf A1 - Mohan, Nijanthan A1 - Oyen, Marc A1 - Schnittcher, Lukas A1 - Voß, Norbert ED - Reiff-Stephan, Jörg ED - Jäkel, Jens ED - Schwarz, André T1 - DiggiTwin: ein interdisziplinäres Projekt zur Nutzung digitaler Zwillinge auf dem Weg zu einem klimaneutralen Gebäudebestand T2 - Tagungsband AALE 2024 : Fit für die Zukunft: praktische Lösungen für die industrielle Automation N2 - Im Hinblick auf die Klimaziele der Bundesrepublik Deutschland konzentriert sich das Projekt Diggi Twin auf die nachhaltige Gebäudeoptimierung. Grundlage für eine ganzheitliche Gebäudeüberwachung und -optimierung bildet dabei die Digitalisierung und Automation im Sinne eines Smart Buildings. Das interdisziplinäre Projekt der FH Aachen hat das Ziel, ein bestehendes Hochschulgebäude und einen Neubau an klimaneutrale Standards anzupassen. Im Rahmen des Projekts werden bekannte Verfahren, wie das Building Information Modeling (BIM), so erweitert, dass ein digitaler Gebäudezwilling entsteht. Dieser kann zur Optimierung des Gebäudebetriebs herangezogen werden, sowie als Basis für eine Erweiterung des Bewertungssystems Nachhaltiges Bauen (BNB) dienen. Mithilfe von Sensortechnologie und künstlicher Intelligenz kann so ein präzises Monitoring wichtiger Gebäudedaten erfolgen, um ungenutzte Energieeinsparpotenziale zu erkennen und zu nutzen. Das Projekt erforscht und setzt methodische Erkenntnisse zu BIM und digitalen Gebäudezwillingen praxisnah um, indem es spezifische Fragen zur Energie- und Ressourceneffizienz von Gebäuden untersucht und konkrete Lösungen für die Gebäudeoptimierung entwickelt. KW - Anomalieerkennung KW - IoT KW - Überwachung & Optimierung KW - DiggiTwin KW - BIM KW - Smart Building KW - Digitalisierung Y1 - 2024 SN - 978-3-910103-02-3 U6 - http://dx.doi.org/10.33968/2024.67 N1 - 20. AALE-Konferenz. Bielefeld, 06.03.-08.03.2024 (Tagungsband unter https://doi.org/10.33968/2024.29) SP - 341 EP - 346 PB - le-tex publishing services GmbH CY - Leipzig ER - TY - CHAP A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Farnetane, Lucas S. A1 - Pöttgen, Philipp A1 - Vergé, Angela A1 - Pelz, Peter F. T1 - Multicriterial design of a hydrostatic transmission system via mixed-integer programming T2 - Operations Research Proceedings 2015 N2 - In times of planned obsolescence the demand for sustainability keeps growing. Ideally, a technical system is highly reliable, without failures and down times due to fast wear of single components. At the same time, maintenance should preferably be limited to pre-defined time intervals. Dispersion of load between multiple components can increase a system’s reliability and thus its availability inbetween maintenance points. However, this also results in higher investment costs and additional efforts due to higher complexity. Given a specific load profile and resulting wear of components, it is often unclear which system structure is the optimal one. Technical Operations Research (TOR) finds an optimal structure balancing availability and effort. We present our approach by designing a hydrostatic transmission system. Y1 - 2017 SN - 978-3-319-42901-4 SN - 978-3-319-42902-1 U6 - http://dx.doi.org/10.1007/978-3-319-42902-1_41 N1 - International Conference of the German, Austrian and Swiss Operations Research Societies (GOR, ÖGOR, SVOR/ASRO), University of Vienna, Austria, September 1-4, 2015 SP - 301 EP - 307 PB - Springer CY - Cham ER - TY - CHAP A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Schänzle, Christian A1 - Lorenz, Ulf A1 - Pelz, Peter F. T1 - Algorithmic system design using scaling and affinity laws T2 - Operations Research Proceedings 2015 N2 - Energy-efficient components do not automatically lead to energy-efficient systems. Technical Operations Research (TOR) shifts the focus from the single component to the system as a whole and finds its optimal topology and operating strategy simultaneously. In previous works, we provided a preselected construction kit of suitable components for the algorithm. This approach may give rise to a combinatorial explosion if the preselection cannot be cut down to a reasonable number by human intuition. To reduce the number of discrete decisions, we integrate laws derived from similarity theory into the optimization model. Since the physical characteristics of a production series are similar, it can be described by affinity and scaling laws. Making use of these laws, our construction kit can be modeled more efficiently: Instead of a preselection of components, it now encompasses whole model ranges. This allows us to significantly increase the number of possible set-ups in our model. In this paper, we present how to embed this new formulation into a mixed-integer program and assess the run time via benchmarks. We present our approach on the example of a ventilation system design problem. KW - Optimal Topology KW - Piecewise Linearization KW - Ventilation System KW - Similarity Theory Y1 - 2017 SN - 978-3-319-42901-4 SN - 978-3-319-42902-1 U6 - http://dx.doi.org/10.1007/978-3-319-42902-1 N1 - International Conference of the German, Austrian and Swiss Operations Research Societies (GOR, ÖGOR, SVOR/ASRO), University of Vienna, Austria, September 1-4, 2015 SP - 605 EP - 611 PB - Springer CY - Cham ER - TY - CHAP A1 - Altherr, Lena A1 - Ederer, Thorsten A1 - Vergé, Angela A1 - Pelz, Peter F. T1 - Algorithmische Struktursynthese eines hydrostatischen Getriebes T2 - Antriebssysteme 2015 : Elektrik, Mechanik, Fluidtechnik in der Anwendung Y1 - 2015 SN - 978-3-18-092268-3 N1 - Antriebssysteme 2015 - Elektrik, Mechanik, Fluidtechnik in der Anwendung. VDI/VDE-Fachtagung. 11.11.15-12.11.15, Aachen. Veröffentlicht in der Reihe VDI-Berichte, Bandnummer 2268. SP - 145 EP - 155 PB - VDI-Verlag CY - Düsseldorf ER - TY - CHAP A1 - Altherr, Lena A1 - Pelz, Peter F. A1 - Ederer, Thorsten A1 - Pfetsch, Marc E. ED - Jacobs, Georg T1 - Optimale Getriebe auf Knopfdruck: Gemischt-ganzzahlige nichtlineare Optimierung zur Entscheidungsunterstützung bei der Auslegung von Getrieben für Kraftfahrzeuge T2 - Antriebstechnisches Kolloquium ATK 2017 Y1 - 2017 SN - 9783743148970 N1 - Antriebstechnisches Kolloquium ATK 2017, 07.03-08.03.2017. Aachen, Deutschland SP - 313 EP - 325 ER - TY - CHAP A1 - Grund, Raphael M. A1 - Altherr, Lena ED - Reiff-Stephan, Jörg ED - Jäkel, Jens ED - Schwarz, André T1 - Development of an open source energy disaggregation tool for the home automation platform Home Assistant T2 - Tagungsband AALE 2023 : mit Automatisierung gegen den Klimawandel N2 - 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. KW - Home Automation Platform KW - Home Assistant KW - Open Source KW - Machine Learning KW - Energy Disaggregation Y1 - 2023 SN - 978-3-910103-01-6 U6 - http://dx.doi.org/10.33968/2023.02 N1 - 19. AALE-Konferenz. Luxemburg, 08.03.-10.03.2023. BTS Connected Buildings & Cities Luxemburg (Tagungsband unter https://doi.org/10.33968/2023.01) SP - 11 EP - 20 PB - le-tex publishing services GmbH CY - Leipzig ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena T1 - Optimizing the design and control of decentralized water supply systems – a case-study of a hotel building T2 - EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization N2 - 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. KW - Engineering optimization KW - Energy efficiency KW - Water KW - Pump System KW - Latin Hypercube Sampling Y1 - 2018 SN - 978-3-319-97773-7 SN - 978-3-319-97772-0 U6 - http://dx.doi.org/10.1007/978-3-319-97773-7_107 N1 - EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization. 17-19 September 2018. Lisboa, Portugal SP - 1241 EP - 1252 PB - Springer CY - Cham ER - TY - CHAP A1 - Leise, Philipp A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Technical Operations Research (TOR) - Algorithms, not Engineers, Design Optimal Energy Efficient and Resilient Cooling Systems T2 - FAN2018 - Proceedings of the International Conference on Fan Noise, Aerodynamics, Applications and Systems N2 - 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. Y1 - 2018 N1 - International Conference on Fan Noise, Aerodynamics, Applications and Systems 18-20.04.2018 Darmstadt, Deutschland SP - 1 EP - 12 ER - TY - CHAP A1 - Leise, Philipp A1 - Breuer, Tim A1 - Altherr, Lena A1 - Pelz, Peter F. T1 - Development, validation and assessment of a resilient pumping system T2 - Proceedings of the Joint International Resilience Conference, JIRC2020 N2 - 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. KW - water supply system KW - fault detection KW - anticipation strategy Y1 - 2020 SN - 978-90-365-5095-6 N1 - Proceedings of the Joint International Resilience Conference 2020. Interconnected: Resilience Innovations for Sustainable Development Goals. 23 - 27 November, 2020 SP - 97 EP - 100 ER -