TY - CHAP A1 - Reich, Marius A1 - Rathjen, Patrick A1 - Adam, Mario ED - Henrik, Lund ED - Brain Vad, Mathiesen ED - Østergaard, Poul Alberg ED - Thellufsen, Jakob Zinck ED - Brodersen, Hans Jørgen T1 - Precomputed ML Surrogates for Energy System Design: Methodology and In-Depth Evaluation T2 - Book of Abstracts 2025: 11th International Conference on Smart Energy Systems, 16-17 September 2025. Copenhagen KW - SmartPrior KW - Energy supply systems KW - Design Optimization KW - Metamodeling KW - Time Series Data Y1 - 2025 UR - https://vbn.aau.dk/ws/portalfiles/portal/796346412/SESAAU2025_Book_of_Abstracts.pdf PB - Aalborg University CY - Aalborg ER - TY - JOUR A1 - Münch, Justin A1 - Priesmann, Jan A1 - Reich, Marius A1 - Tillmanns, Marius A1 - Praktiknjo, Aaron A1 - Adam, Mario T1 - Uplifting the Complexity of Analysis for Probabilistic Security of Electricity Supply Assessments using Artificial Neural Networks JF - Energy and AI N2 - The energy sector faces rapid decarbonisation and decision-makers demand reliable assessments of the security of electricity supply. For this, detailed simulation models with a high temporal and technological resolution are required. When confronted with increasing weather-dependent renewable energy generation, probabilistic simulation models have proven. The significant computational costs of calculating a scenario, however, limit the complexity of further analysis. Advances in code optimization as well as the use of computing clusters still lead to runtimes of up to eight hours per scenario. However ongoing research highlights that tailor-made approximations are potentially the key factor in further reducing computing time. Consequently, current research aims to provide a method for the rapid prediction of widely varying scenarios. In this work artificial neural networks (ANN) are trained and compared to approximate the system behavior of the probabilistic simulation model. To do so, information needs to be sampled from the probabilistic simulation in an efficient way. Because only a limited space in the whole design space of the 16 independent variables is of interest, a classification is developed. Finally it required only around 35 minutes to create the regression models, including sampling the design space, simulating the training data and training the ANNs. The resulting ANNs are able to predict all scenarios within the validity range of the regression model with a coefficient of determination of over 0.9998 for independent test data (1.051.200 data points). They need only a few milliseconds to predict one scenario, enabling in-depth analysis in a brief period of time. KW - Security of electricity supply KW - Probabilistic simulation KW - Metamodeling KW - Artificial neural networks KW - Regression KW - HSD Publikationsfonds KW - DFG Publikationskosten KW - KIVi Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-45359 SN - 2666-5468 N1 - Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - 532148125 and supported by the central publication fund of Hochschule Düsseldorf University of Applied Sciences. PB - Elsevier ER - TY - JOUR A1 - Priesmann, Jan A1 - Münch, Justin A1 - Tillmanns, Marius A1 - Ridha, E. A1 - Spiegel, Thomas A1 - Reich, Marius A1 - Adam, Mario A1 - Nolting, L. A1 - Praktiknjo, Aaron T1 - Artificial intelligence and design of experiments for resource adequacy assessment in power systems JF - Energy Strategy Reviews KW - KiVi KW - Design of experiments KW - Resource adequacy KW - Security of supply KW - Artificial intelligence KW - KIVi Y1 - 2024 U6 - https://doi.org/10.1016/j.esr.2024.101368 SN - 2211-467X VL - 53 PB - Elsevier ER - TY - CHAP A1 - Reich, Marius A1 - Patrick, Rathjen A1 - Adam, Mario ED - Lund, Henrik ED - Mathiesen, Brian Vad ED - Østergaard, Poul Alberg ED - Thellufsen, Jakob Zinck ED - Brodersen, Hans Jørgen T1 - Harnessing Machine Learning for Rapid Optimization: Integration of Time Series Data into Prior Approximation of Energy System Simulations T2 - Book of Abstracts :10th International Conference on Smart Energy Systems KW - SmartPrior KW - Energy supply systems KW - Rule based simulation KW - Design Optimization KW - Metamodeling KW - Time Series Data Y1 - 2024 UR - https://vbn.aau.dk/ws/portalfiles/portal/749867139/SESAAU2024_Book_of_Abstracts.pdf PB - Aalborg University CY - Aalborg ER - TY - CHAP A1 - Gottschald, Jonas A1 - Reich, Marius A1 - Adam, Mario ED - Lund, Henrik ED - Mathiesen, Brian Vad ED - Østergaard, Paul Alberg ED - Brodersen, Hans Jørgen T1 - Lessons Learned: On the Potentials and Challenges of a Model Predictive Controlled DHN Heat Supply T2 - Book of Abstracts: 9th International Conference on Smart Energy Systems. Aalborg Universitet KW - District Heating KW - Machine Learning KW - Model Predictive Control KW - Monitoring KW - BestHeatNet Y1 - 2023 UR - https://vbn.aau.dk/ws/portalfiles/portal/548360793/BoA-2023FINAL-2.pdf SP - 87 EP - 87 PB - Aalborg University CY - Aalborg ER - TY - CHAP A1 - Reich, Marius A1 - Prusas, Benedikt A1 - Adam, Mario ED - Lund, Henrik ED - Mathiesen, Brian Vad ED - Østergaard, Paul Alberg ED - Brodersen, Hans Jørgen T1 - Prior-Approximation of Rule-Based Energy System Simulation for Fast Design Optimization T2 - Book of Abstracts: 9th International Conference on Smart Energy Systems. Aalborg Universitet KW - Energy supply systems KW - Rule based simulation KW - Design Optimization KW - Metamodeling KW - SmartPrior Y1 - 2023 UR - https://vbn.aau.dk/ws/portalfiles/portal/548360793/BoA-2023FINAL-2.pdf PB - Aalborg University CY - Aalborg ER - TY - GEN A1 - Gottschald, Jonas A1 - Reich, Marius A1 - Adam, Mario T1 - Lernende Algorithmen - Künstliche Intelligenz für Wärmenetze T2 - hn21 Journal KW - BestHeatNet Y1 - 2021 UR - https://www.hn-nrw.de/aktivitaeten/publikationen/journal/# IS - 2021 SP - 8 EP - 8 PB - Zentrum für Forschungskommunikation CY - Köln ER - TY - INPR A1 - Priesmann, Jan A1 - Münch, Justin A1 - Ridha, Elias A1 - Spiegel, Thomas A1 - Reich, Marius A1 - Adam, Mario A1 - Nolting, Lars A1 - Praktiknjo, Aaron T1 - Artificial Intelligence and Design of Experiments for Assessing Security of Electricity Supply: A Review and Strategic Outlook N2 - Assessing the effects of the energy transition and liberalization of energy markets on resource adequacy is an increasingly important and demanding task. The rising complexity in energy systems requires adequate methods for energy system modeling leading to increased computational requirements. Furthermore, with complexity, uncertainty increases likewise calling for probabilistic assessments and scenario analyses. To adequately and efficiently address these various requirements, new methods from the field of data science are needed to accelerate current methods. With our systematic literature review, we want to close the gap between the three disciplines (1) assessment of security of electricity supply, (2) artificial intelligence, and (3) design of experiments. For this, we conduct a large-scale quantitative review on selected fields of application and methods and make a synthesis that relates the different disciplines to each other. Among other findings, we identify metamodeling of complex security of electricity supply models using AI methods and applications of AI-based methods for forecasts of storage dispatch and (non-)availabilities as promising fields of application that have not sufficiently been covered, yet. We end with deriving a new methodological pipeline for adequately and efficiently addressing the present and upcoming challenges in the assessment of security of electricity supply. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.48550/arXiv.2112.04889 PB - arXiv ER - TY - GEN A1 - Lambach, Stefan A1 - Kowalski, M. A1 - Reich, Marius A1 - Adam, Mario T1 - Vermessung und Modellierung eines Komfort-Lüftungsgerätes mit passiver Wärmerückgewinnung und aktiver, umschaltbarer Luft/Luft-Wärmepumpe im Kühlbetrieb T2 - KI Kälte Luft Klimatechnik KW - Coolplan-AIR Y1 - 2020 SN - 1865-5432 VL - 56 IS - 10 SP - 48 EP - 55 PB - Hüthig ER - TY - JOUR A1 - Nolting, Lars A1 - Spiegel, Thomas A1 - Reich, Marius A1 - Adam, Mario A1 - Praktiknjo, Aaron T1 - Can energy system modeling benefit from artificial neural networks? Application of two-stage metamodels to reduce computation of security of supply assessments JF - Computers & Industrial Engineering KW - KIVi Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-26979 SN - 0360-8352 VL - 142 PB - Elsevier ER - TY - CHAP A1 - Gottschald, Jonas A1 - Reich, Marius A1 - Adam, Mario A1 - Leibauer, R. T1 - Selbstlernende Betriebsoptimierung einer hybriden Nahwärmeversorgung T2 - Fachkonferenz Digitalisieren - Sektoren koppeln - Flexibilisieren, 24.11.2020, Berlin KW - BestHeatNet Y1 - 2020 CY - Berlin ER - TY - JOUR A1 - Reich, Marius A1 - Gottschald, Jonas A1 - Riegebauer, Philipp A1 - Adam, Mario T1 - Predictive Control of District Heating System Using Multi-Stage Nonlinear Approximation with Selective Memory JF - Energies KW - BestHeatNet KW - DOAJ Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:due62-opus-33627 SN - 1996-1073 VL - 13 IS - 24 PB - MDPI ER - TY - CHAP A1 - Münch, Justin A1 - Reich, Marius A1 - Adam, Mario ED - Wesselak, Viktor T1 - Entwicklung eines Tools zur automatisierten Optimierung von Energiesystemen durch Maschinelles Lernen T2 - RET.Con 2020. 3. Regenerative Energietechnik Konferenz, 13.-14.02.2020, Nordhausen KW - Fast-Energy-Design Y1 - 2020 SN - 978-3-940820-16-7 U6 - https://doi.org/10.22032/dbt.46243 SP - 152 EP - 156 PB - Hochschule Nordhausen CY - Nordhausen ER - TY - JOUR A1 - Biedermann, Till M. A1 - Reich, Marius A1 - Kameier, Frank A1 - Adam, Mario T1 - Assessment of statistical sampling methods and approximation models applied to aeroacoustic and vibroacoustic problems JF - Advances in Aircraft and Spacecraft Science KW - artificial neural networks KW - design of experiments KW - Latin hypercube sampling KW - aeroacoustics KW - aerodynamics KW - spectral analysis Y1 - 2019 UR - http://www.techno-press.org/content/?page=article&journal=aas&volume=6&num=6&ordernum=7 U6 - https://doi.org/10.12989/aas.2019.6.6.531 SN - 2287-528X VL - 6 IS - 6 SP - 529 EP - 550 PB - Techno Press ER - TY - CHAP A1 - Adam, Mario A1 - Gottschald, Jonas A1 - Reich, Marius A1 - Götzelmann, Dennis T1 - BestHeatNet – Selbstlernende Betriebsoptimierung einer hybriden Nahwärmeversorgung T2 - Der Geothermiekongress, 19.-21.11.2019, München KW - BestHeatNet Y1 - 2019 UR - https://www.der-geothermiekongress.de/fileadmin/user_upload/DGK/DGK_2019/Teilnahme/P12_Gottschald_BestHeatNet-124.pdf CY - München ER - TY - CHAP A1 - Reich, Marius A1 - Adam, Mario A1 - Lambach, Stefan T1 - Comparison of different Methods for Approximating Models of Energy Supply Systems and Polyoptimising the Systems-Structure and Components-Dimension T2 - 30th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2017), San Diego, California, USA, 2-6 July 2017 KW - Fast-Energy-Design Y1 - 2018 SN - 9781510862562 SP - 2921 EP - 2933 PB - Curran Associates Inc CY - Red Hook, NY ER - TY - CHAP A1 - Biedermann, Till M. A1 - Reich, Marius A1 - Kameier, Frank A1 - Adam, Mario A1 - Paschereit, C. T1 - Assessment of Statistical Sampling Methods and Approximation Models Applied to Aeroacoustic and Vibroacoustic Problem T2 - NOVEM - 6th conference on Noise and Vibration emerging methods, 07.-09.05.2018, Ibiza / Spain Y1 - 2018 CY - Ibiza ER - TY - CHAP A1 - Gottschald, Jonas A1 - Adam, Mario A1 - Reich, Marius T1 - Multi-Objective Optimization of a District Heating Networks Energy Supply Systems Structure and Dimension T2 - SDH - 5th International Solar District Heating Conference, 11.-12.04.2018, Graz / Austria KW - Fast-Energy-Design Y1 - 2018 UR - https://www.researchgate.net/publication/325896757_Robust_Optimization_of_District_Heating_Networks_Structure_and_Dimension_combining_Metamodels_and_Multi-Objective_Optimization CY - Graz ER - TY - CHAP A1 - Nolting, Lars A1 - Spiegel, Thomas A1 - Reich, Marius A1 - Adam, Mario A1 - Praktiknjo, Aaron T1 - Can Energy System Modeling benefit from Artificial Neural Networks? Application of Two-Stage Metamodels to Reduce Computation of Security of Supply Assessments (Best Application Paper Award) T2 - CIE – 48th International Conference on Computers & Industrial Engineering, 02.-05.12.2018, Auckland / New Zealand KW - KIVi Y1 - 2018 CY - Auckland ER - TY - CHAP A1 - Reich, Marius A1 - Adam, Mario A1 - Gottschald, Jonas T1 - Robust Optimization of District Heating Networks Structure and Dimension combining Metamodels and Multi-Objective Optimization T2 - ECOS - 31th International Conference on Efficiency, Cost, Optimization, Simulation and Enviromental Impact of Energy Systems, 17.-21.06.2018, Guimaraes / Portugal KW - EnergyExpert Y1 - 2018 UR - https://www.researchgate.net/publication/325896757_Robust_Optimization_of_District_Heating_Networks_Structure_and_Dimension_combining_Metamodels_and_Multi-Objective_Optimization CY - Guimaraes ER - TY - CHAP A1 - Gottschald, Jonas A1 - Reich, Marius A1 - Adam, Mario ED - Hochschule Nordhausen, T1 - Multikriterielle Auslegung der Energieversorgung eines Nahwärmenetzes T2 - RET.Con 2018. Tagungsband : 1. Regenerative Energietechnik-Konferenz in Nordhausen 8.-9. Februar 2018 KW - Fast-Energy-Design Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:27-dbt-20200904-111850-006 UR - https://www.db-thueringen.de/receive/dbt_mods_00045831 SP - 141 EP - 148 PB - Hochschule Nordhausen CY - Nordhausen ER -