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Related papers: Short-Term Power Demand Forecasting for Diverse Co…

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Short-term load forecasting (STLF) is essential for the reliable and economic operation of power systems. Though many STLF methods were proposed over the past decades, most of them focused on loads at high aggregation levels only. Thus,…

Machine Learning · Computer Science 2019-03-27 Yayu Peng , Yishen Wang , Xiao Lu , Haifeng Li , Di Shi , Zhiwei Wang , Jie Li

Accurate load forecasting is critical for electricity market operations and other real-time decision-making tasks in power systems. This paper considers the short-term load forecasting (STLF) problem for residential customers within a…

Machine Learning · Computer Science 2021-11-24 Yuqi Zhou , Arun Sukumaran Nair , David Ganger , Abhinandan Tripathi , Chaitanya Baone , Hao Zhu

Short-Term Load Forecasting (STLF) is a fundamental component in the efficient management of power systems, which has been studied intensively over the past 50 years. The emerging development of smart grid technologies is posing new…

Optimization and Control · Mathematics 2017-02-28 The-Hien Dang-Ha , Filippo Maria Bianchi , Roland Olsson

Accurate short-term load forecasting is essential for the efficient operation of the power sector. Forecasting load at a fine granularity such as hourly loads of individual households is challenging due to higher volatility and inherent…

Signal Processing · Electrical Eng. & Systems 2022-05-17 Haris Mansoor , Sarwan Ali , Imdadullah Khan , Naveed Arshad , Muhammad Asad Khan , Safiullah Faizullah

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

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

Short Term Load Forecast (STLF) is necessary for effective scheduling, operation optimization trading, and decision-making for electricity consumers. Modern and efficient machine learning methods are recalled nowadays to manage complicated…

Applications · Statistics 2021-10-20 Junjie Hu , Brenda López Cabrera , Awdesch Melzer

Short term Load Forecasting (STLF) plays an important role in traditional and modern power systems. Most STLF models predominantly exploit temporal dependencies from historical data to predict future consumption. Nowadays, with the…

Machine Learning · Computer Science 2025-02-19 Quoc Viet Nguyen , Joaquin Delgado Fernandez , Sergio Potenciano Menci

Short-Term Electricity-Load Forecasting (STELF) refers to the prediction of the immediate demand (in the next few hours to several days) for the power system. Various external factors, such as weather changes and the emergence of new…

Machine Learning · Computer Science 2025-05-20 Qi Dong , Rubing Huang , Chenhui Cui , Dave Towey , Ling Zhou , Jinyu Tian , Jianzhou Wang

Short-term load forecasting (STLF) is crucial for the daily operation of power grids. However, the non-linearity, non-stationarity, and randomness characterizing electricity demand time series renders STLF a challenging task. Various…

Electrical utilities depend on short-term demand forecasting to proactively adjust production and distribution in anticipation of major variations. This systematic review analyzes 240 works published in scholarly journals between 2000 and…

Machine Learning · Computer Science 2022-01-04 Ali Bou Nassif , Bassel Soudan , Mohammad Azzeh , Imtinan Attilli , Omar AlMulla

As the energy landscape changes quickly, grid operators face several challenges, especially when integrating renewable energy sources with the grid. The most important challenge is to balance supply and demand because the solar and wind…

Machine Learning · Computer Science 2025-01-24 Kamal Sarkar

In power grids, short-term load forecasting (STLF) is crucial as it contributes to the optimization of their reliability, emissions, and costs, while it enables the participation of energy companies in the energy market. STLF is a…

Electricity load consumption may be extremely complex in terms of profile patterns, as it depends on a wide range of human factors, and it is often correlated with several exogenous factors, such as the availability of renewable energy and…

Machine Learning · Computer Science 2025-02-03 Aleksei Kychkin , Georgios C. Chasparis

Recent research shows large-scale AI-centric data centers could experience rapid fluctuations in power demand due to varying computation loads, such as sudden spikes from inference or interruption of training large language models (LLMs).…

Signal Processing · Electrical Eng. & Systems 2025-03-12 Mariam Mughees , Yuzhuo Li , Yize Chen , Yunwei Ryan Li

With the rise of time-of-use and tiered electricity pricing, energy consumers are encouraged to adopt peak-shifting strategies by automatically controlling high-power appliances. These help lower energy costs while enhancing the power…

Machine Learning · Computer Science 2026-04-29 Yunhao Yao , Jinwei Fang , Puhan Luo , Zhiqiang Wang , Jiahui Hou , Xiang-Yang Li

Electricity is a volatile power source that requires great planning and resource management for both short and long term. More specifically, in the short-term, accurate instant energy consumption forecasting contributes greatly to improve…

Artificial Intelligence · Computer Science 2022-07-05 Nuno Oliveira , Norberto Sousa , Isabel Praça

Electricity forecasting has been a recurring research topic, as it is key to finding the right balance between production and consumption. While most papers are focused on the national or regional scale, few are interested in the household…

The rising integration of variable renewable energy sources (RES), like solar and wind power, introduces considerable uncertainty in grid operations and energy management. Effective forecasting models are essential for grid operators to…

Systems and Control · Electrical Eng. & Systems 2024-08-02 Jesus Silva-Rodriguez , Elias Raffoul , Xingpeng Li

Integrating renewable energy sources into the power grid is becoming increasingly important as the world moves towards a more sustainable energy future in line with SDG 7. However, the intermittent nature of renewable energy sources can…

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