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Accurate estimates of network parameters are essential for modeling, monitoring, and control in power distribution systems. In this paper, we develop a physics-informed graphical learning algorithm to estimate network parameters of…

Machine Learning · Computer Science 2021-02-19 Wenyu Wang , Nanpeng Yu

This article deals with the problem of finding the best topology, pipe diameter choices, and operation parameters for realistic district heating networks. Present design tools that employ non-linear flow and heat transport models for…

Computational Engineering, Finance, and Science · Computer Science 2020-10-19 Maarten Blommaert , Yannick Wack , Martine Baelmans

Gas Transmission Networks are large-scale complex systems, and corresponding design and control problems are challenging. In this paper, we consider the problem of control and management of these systems in crisis situations. We present…

Artificial Intelligence · Computer Science 2012-10-01 Amir Noori , Mohammad Bagher Menhaj , Masoud Shafiee

We present a comparative study of different probabilistic forecasting techniques on the task of predicting the electrical load of secondary substations and cabinets located in a low voltage distribution grid, as well as their aggregated…

Machine Learning · Computer Science 2020-04-17 Lorenzo Nespoli , Vasco Medici , Kristijan Lopatichki , Fabrizio Sossan

Improving the accuracy of soil moisture estimation is required for advancing irrigation scheduling and water conservation efforts. Central to this task are soil hydraulic parameters, which govern moisture dynamics but are rarely known…

Systems and Control · Electrical Eng. & Systems 2025-06-06 Bernard T. Agyeman , Erfan Orouskhani , Mohamed Naouri , Willemijn Appels , Maik Wolleben , Jinfeng Liu , Sirish L. Shah

When the dynamical data of a system only convey dynamic information over a limited operating range, the identification of models with good performance over a wider operating range is very unlikely. Nevertheless, models with such…

Systems and Control · Electrical Eng. & Systems 2020-09-07 Leandro Freitas , Bruno H. G. Barbosa , Luis A. Aguirre

To operate process engineering systems in a safe and reliable manner, predictive models are often used in decision making. In many cases, these are mechanistic first principles models which aim to accurately describe the process. In…

Machine Learning · Computer Science 2022-05-20 Timur Bikmukhametov , Johannes Jäschke

Virtual representations of physical critical infrastructures, such as water or energy plants, are used for simulations and digital twins to ensure resilience and continuity of their services. These models usually require 3D point clouds…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Mike Diessner , Yannick E. Tarant

Heat pumps (HPs) have emerged as a cost-effective and clean technology for sustainable energy systems, but their efficiency in producing hot water remains restricted by conventional threshold-based control methods. Although machine learning…

Machine Learning · Computer Science 2025-06-23 Manal Rahal , Bestoun S. Ahmed , Roger Renstrom , Robert Stener , Albrecht Wurtz

This paper focuses on multiscale dynamics occurring in steam supply systems. The dynamics of interest are originally described by a distributed-parameter model for fast steam flows over a pipe network coupled with a lumped-parameter model…

Dynamical Systems · Mathematics 2023-05-15 Hikaru Hoshino , Yoshihiko Susuki , Takashi Hikihara

Port-Hamiltonian (pH) systems are a very important modeling tool in almost all areas of systems and control, in particular in network based model of multi-physics multi-scale systems. They lead to remarkably robust models that can be easily…

Optimization and Control · Mathematics 2019-03-19 Karim Cherifi , Volker Mehrmann , Kamel Hariche

In this paper, we propose a data-driven leak localization method for water distribution networks (WDNs) which combines two complementary approaches: graph-based interpolation and dictionary classification. The former estimates the complete…

Machine Learning · Computer Science 2021-10-14 Paul Irofti , Luis Romero-Ben , Florin Stoican , Vicenç Puig

Smart thermostats are one of the most prevalent home automation products. They learn occupant preferences and schedules, and utilize an accurate thermal model to reduce the energy use of heating and cooling equipment while maintaining the…

Systems and Control · Electrical Eng. & Systems 2021-08-31 Md Monir Hossain , Tianyu Zhang , Omid Ardakanian

The high penetration of distributed renewable energy resources in power systems has changed their dynamic behavior, not only at the distribution level but also at the transmission levels. For analyses performed in this new reality of…

Systems and Control · Electrical Eng. & Systems 2022-07-26 Rodrigo A. Ramos , Ahda P. Grilo-Pavani , Artur B. Piardi , Tatiane C. C. Fernandes

The transition to 4th generation district heating creates a growing need for scalable, automated design tools that accurately capture the spatial and temporal details of heating network operation. This paper presents an automated design…

Computational Engineering, Finance, and Science · Computer Science 2024-01-30 Yannick Wack , Martin Sollich , Robbe Salenbien , Jan Diriken , Martine Baelmans , Maarten Blommaert

Integration of physics and machine learning in virtual flow metering applications is known as gray-box modeling. The combination is believed to enhance multiphase flow rate predictions. However, the superiority of gray-box models is yet to…

Systems and Control · Electrical Eng. & Systems 2021-10-12 M. Hotvedt , B. Grimstad , D. Ljungquist , L. Imsland

Cost-effective water distribution network (WDN) design with acceptable pressure performance is crucial for the management of drinking water in cities. This paper presents a Microsoft Excel tool to model, simulate, and optimize WDNs with…

Systems and Control · Electrical Eng. & Systems 2024-05-16 Marcus Nóbrega Gomes , Igor Matheus Benites , Salma M. Elsherif , Ahmad F. Taha , Marcio H. Giacomoni

Hydrogen's growing role in the transition towards climate-neutral energy systems necessitates structured modeling frameworks. Existing gas network models, largely developed for natural gas, fail to capture hydrogen systems distinct…

Optimization and Control · Mathematics 2025-12-03 Abdullah Shahin , Hannes Gernandt , Anton Plietzsch , Johannes Schiffer

Control of water distribution networks (WDNs) can be represented by an optimization problem with hydraulic models describing the nonlinear relationship between head loss, water flow, and demand. The problem is difficult to solve due to the…

Optimization and Control · Mathematics 2019-02-19 Shen Wang , Ahmad F. Taha , Nikolaos Gatsis , Marcio Giacomoni

A two-dimensional model is proposed for energy efficiency assessment through the simulation of heat transfer in building envelopes, considering the influence of the surrounding environment. The model is based on the \DF ~approach that…

Computational Engineering, Finance, and Science · Computer Science 2021-11-18 Julien Berger , Suelen Gasparin , Walter Mazuroski , Nathan Mendes
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