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Residential customers have traditionally not been treated as individual entities due to the high volatility in residential consumption patterns as well as a historic focus on aggregated loads from the utility and system feeder perspective.…

The relationship between electricity demand and variables such as economic activity and weather patterns is well established. However, this paper explores the connection between electricity demand and social aspects. It further embeds…

Computation and Language · Computer Science 2025-07-09 Yun Bai , Simon Camal , Andrea Michiorri

Energy load forecasting plays a crucial role in optimizing resource allocation and managing energy consumption in buildings and cities. In this paper, we propose a novel approach that leverages language models for energy load forecasting.…

Artificial Intelligence · Computer Science 2023-10-30 Hao Xue , Flora D. Salim

Efficient load forecasting is needed to ensure better observability in the distribution networks, whereas such forecasting is made possible by an increasing number of smart meter installations. Because distribution networks include a large…

Machine Learning · Computer Science 2022-04-04 Miha Grabner , Yi Wang , Qingsong Wen , Boštjan Blažič , Vitomir Štruc

Motivated by the increasing integration among electricity markets, in this paper we propose two different methods to incorporate market integration in electricity price forecasting and to improve the predictive performance. First, we…

Statistical Finance · Quantitative Finance 2017-12-08 Jesus Lago , Fjo De Ridder , Peter Vrancx , Bart De Schutter

Building design optimization often depends on physics-based simulation tools such as EnergyPlus, which, although accurate, are computationally expensive and slow. Surrogate models provide a faster alternative, yet most are…

Machine Learning · Computer Science 2026-03-13 Piragash Manmatharasan , Girma Bitsuamlak , Katarina Grolinger

The relationship between electricity demand and weather is well established in power systems, along with the importance of behavioral and social aspects such as holidays and significant events. This study explores the link between…

Computation and Language · Computer Science 2024-01-31 Yun Bai , Simon Camal , Andrea Michiorri

This study proposes a novel framework for long-term electricity demand prediction based solely on historical consumption data, without relying on external variables such as temperature or economic indicators. The method combines…

Machine Learning · Computer Science 2025-03-31 Toma Masaki , Kanta Tachibana

Short term load forecasts will play a key role in the implementation of smart electricity grids. They are required to optimise a wide range of potential network solutions on the low voltage (LV) grid, including integrating low carbon…

Applications · Statistics 2019-10-17 Stephen Haben , Georgios Giasemidis , Florian Ziel , Siddharth Arora

Electricity price forecasting is a critical tool for the efficient operation of power systems and for supporting informed decision-making by market participants. This paper explores a novel methodology aimed at improving the accuracy of…

Applications · Statistics 2025-01-13 Bartosz Uniejewski , Florian Ziel

Educational institutions are essential for economic and social development. Budget cuts in Brazil in recent years have made it difficult to carry out their activities and projects. In the case of expenses with water and electricity,…

This paper examines the relationship between system imbalance and several explanatory variables within the French electricity system. The factors considered include lagged imbalance values, observations of renewable energy sources (RES)…

Systems and Control · Electrical Eng. & Systems 2025-07-14 Jonathan Dumas , Sébastien Finet , Nathalie Grisey , Ibtissam Hamdane , Paul Plessiez

In electricity markets, retailers or brokers want to maximize profits by allocating tariff profiles to end consumers. One of the objectives of such demand response management is to incentivize the consumers to adjust their consumption so…

Machine Learning · Computer Science 2022-02-14 Jyoti Narwariya , Chetan Verma , Pankaj Malhotra , Lovekesh Vig , Easwara Subramanian , Sanjay Bhat

Ensuring grid stability in the transition to renewable energy sources requires accurate power demand forecasting. This study addresses the need for precise forecasting by differentiating among industrial, commercial, and residential…

Machine Learning · Computer Science 2025-06-06 Asier Diaz-Iglesias , Xabier Belaunzaran , Ane M. Florez-Tapia

As renewable distributed energy resources (DERs) penetrate the power grid at an accelerating speed, it is essential for operators to have accurate solar photovoltaic (PV) energy forecasting for efficient operations and planning. Generally,…

Machine Learning · Statistics 2017-09-26 Hossein Sangrody , Morteza Sarailoo , Ning Zhou , Nhu Tran , Mahdi Motalleb , Elham Foruzan

Electricity networks are vulnerable to weather damage, with severe events often leading to faults and power outages. Timely forecasts of fault occurrences, ranging from nowcasts to several days ahead, can enhance preparedness, support…

Applications · Statistics 2026-03-03 Mateus Maia , Daniela Castro-Camilo , Jethro Browell

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

Accurate electricity demand forecasting is crucial to meet energy security and efficiency, especially when relying on intermittent renewable energy sources. Recently, massive savings have been observed in Europe, following an unprecedented…

Applications · Statistics 2026-05-05 Nathan Doumèche , Yann Allioux , Yannig Goude , Stefania Rubrichi

Forecasting building energy consumption has become a promising solution in Building Energy Management Systems for energy saving and optimization. Furthermore, it can play an important role in the efficient management of the operation of a…

Machine Learning · Computer Science 2023-12-01 Mohamad Khalil , A. Stephen McGough , Hussain Kazmi , Sara Walker

Renewable Energies (RES) penetration is progressing rapidly: in France, the installed capacity of photovoltaic (PV) power rose from 26MW in 2007 to 8GW in 2017 [1]. Power generated by PV plants being highly dependent on variable weather…

Applications · Statistics 2019-10-15 Kevin Bellinguer , Robin Girard , Guillaume Bontron , Georges Kariniotakis