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The increasing penetration level of energy generation from renewable sources is demanding for more accurate and reliable forecasting tools to support classic power grid operations (e.g., unit commitment, electricity market clearing or…

Machine Learning · Computer Science 2020-07-17 Michela Moschella , Mauro Tucci , Emanuele Crisostomi , Alessandro Betti

Nowadays, it is broadly recognized in the power system community that to meet the ever expanding energy sector's needs, it is no longer possible to rely solely on physics-based models and that reliable, timely and sustainable operation of…

Machine Learning · Computer Science 2022-11-16 Yuzhou Chen , Tian Jiang , Miguel Heleno , Alexandre Moreira , Yulia R. Gel

The Intergovernmental Panel on Climate Change proposes different mitigation strategies to achieve the net emissions reductions that would be required to follow a pathway that limits global warming to 1.5{\deg}C with no or limited overshoot.…

Systems and Control · Electrical Eng. & Systems 2021-12-10 Jonathan Dumas

The energy efficiency aspect of cellular networks is a vital topic of research over the recent days. As energy consumption is on the rise and the price of electricity is increasing very rapidly, necessity to reduce electricity usage in…

Networking and Internet Architecture · Computer Science 2018-10-08 Imtiaz Nasim , Mostafa Zaman Chowdhury , Md. Syadus Sefat

The power grid frequency is the central observable in power system control, as it measures the balance of electrical supply and demand. A reliable frequency forecast can facilitate rapid control actions and may thus greatly improve power…

Physics and Society · Physics 2020-08-24 Johannes Kruse , Benjamin Schäfer , Dirk Witthaut

Demand-side management presents significant benefits in reducing the energy load in smart grids by balancing consumption demands or including energy generation and/or storage devices in the user's side. These techniques coordinate the…

Optimization and Control · Mathematics 2016-05-06 Javier Zazo , Santiago Zazo , Sergio Valcarcel Macua

To mitigate climate change, the share of renewable energies in power production needs to be increased. Renewables introduce new challenges to power grids regarding the dynamic stability due to decentralization, reduced inertia, and…

Machine Learning · Computer Science 2026-05-06 Christian Nauck , Michael Lindner , Konstantin Schürholt , Frank Hellmann

The transition from traditional power grids to smart grids, significant increase in the use of renewable energy sources, and soaring electricity prices has triggered a digital transformation of the energy infrastructure that enables new,…

Machine Learning · Computer Science 2025-05-30 Carolina Fortuna , Gregor Cerar , Blaz Bertalanic , Andrej Campa , Mihael Mohorcic

Accurate forecasting of the electrical load, such as the magnitude and the timing of peak power, is crucial to successful power system management and implementation of smart grid strategies like demand response and peak shaving. In…

Machine Learning · Computer Science 2024-11-26 Dafang Zhao , Xihao Piao , Zheng Chen , Zhengmao Li , Ittetsu Taniguchi

Most electricity systems worldwide are deploying advanced metering infrastructures to collect relevant operational data. In particular, smart meters allow tracking electricity load consumption at a very disaggregated level and at high…

Machine Learning · Statistics 2020-03-09 Andrés M. Alonso , F. Javier Nogales , Carlos Ruiz

The progress of some AI paradigms such as deep learning is said to be linked to an exponential growth in the number of parameters. There are many studies corroborating these trends, but does this translate into an exponential increase in…

Machine Learning · Computer Science 2023-03-30 Radosvet Desislavov , Fernando Martínez-Plumed , José Hernández-Orallo

This work studies how the communication network between proactive consumers affects the power utilization and fairness in a simplified direct-current micro-grid model, composed by three coupled layers: physical (an electric circuit that…

Multiagent Systems · Computer Science 2018-02-13 Florian Kühnlenz , Pedro H. J. Nardelli , Hirley Alves

Increasingly complex neural network architectures have achieved phenomenal performance. However, these complex models require massive computational resources that consume substantial amounts of electricity, which highlights the potential…

Machine Learning · Computer Science 2025-06-03 Leo Mei , Mark Stamp

User scheduling, beamforming and energy coordination are investigated in smart-grid powered cellular networks (SGPCNs), where the base stations are powered by a smart grid and natural renewable energy sources. Heterogeneous energy…

Information Theory · Computer Science 2020-01-30 Yanjie Dong , Md. Jahangir Hossain , Julian Cheng , Victor C. M. Leung

Water consumption remains a major concern among the world's future challenges. For applications like load monitoring and demand response, deep learning models are trained using enormous volumes of consumption data in smart cities. On the…

Machine Learning · Computer Science 2023-01-31 Mohammed El Hanjri , Hibatallah Kabbaj , Abdellatif Kobbane , Amine Abouaomar

Renewable-energy-based grids development needs new methods to maintain the balance between the load and generation using the efficient energy storages models. Most of the available energy storages models do not take into account such…

Signal Processing · Electrical Eng. & Systems 2019-06-10 Denis Sidorov , Qing Tao , Ildar Muftahov , Aleksei Zhukov , Dmitriy Karamov , Aliona Dreglea , Fang Liu

The growing complexity of the power grid, driven by increasing share of distributed energy resources and by massive deployment of intelligent internet-connected devices, requires new modelling tools for planning and operation. Physics-based…

Machine Learning · Statistics 2018-11-26 Francesco Fusco

The interest in developing smart cities has increased dramatically in recent years. In this context an intelligent transportation system depicts a major topic. The forecast of traffic flow is indispensable for an efficient intelligent…

Machine Learning · Computer Science 2020-06-09 Ralf Rüther , Andreas Klos , Marius Rosenbaum , Wolfram Schiffmann

Smart grids extremely rely on Information and Communications Technology (ICT) and smart meters to control and manage numerous parameters of the network. However, using these infrastructures make smart grids more vulnerable to cyber threats…

Machine Learning · Computer Science 2021-02-12 Hossein Mohammadi Rouzbahani , Hadis Karimipour , Lei Lei

Long-term planning of a robust power system requires the understanding of changing demand patterns. Electricity demand is highly weather sensitive. Thus, the supply side variation from introducing intermittent renewable sources, juxtaposed…

Machine Learning · Computer Science 2022-09-13 Reshmi Ghosh , Michael Craig , H. Scott Matthews , Constantine Samaras , Laure Berti-Equille