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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

Distribution feeder long-term load forecast (LTLF) is a critical task many electric utility companies perform on an annual basis. The goal of this task is to forecast the annual load of distribution feeders. The previous top-down and…

Machine Learning · Computer Science 2020-07-02 Ming Dong , L. S. Grumbach

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

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…

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…

With the evolution of power systems as it is becoming more intelligent and interactive system while increasing in flexibility with a larger penetration of renewable energy sources, demand prediction on a short-term resolution will…

Machine Learning · Computer Science 2022-12-20 Saad Emshagin , Wayes Koroni Halim , Rasha Kashef

Accurate household electricity short-term load forecasting (STLF) is key to future and sustainable energy systems. While various studies have analyzed statistical, machine learning, or deep learning approaches for household electricity…

Computational Engineering, Finance, and Science · Computer Science 2026-01-09 Marcel Meyer , David Zapata , Sascha Kaltenpoth , Oliver Müller

Ensuring sustainability demands more efficient energy management with minimized energy wastage. Therefore, the power grid of the future should provide an unprecedented level of flexibility in energy management. To that end, intelligent…

Neural and Evolutionary Computing · Computer Science 2018-11-29 Daniel L. Marino , Kasun Amarasinghe , Milos Manic

Demand forecasting in power sector has become an important part of modern demand management and response systems with the rise of smart metering enabled grids. Long Short-Term Memory (LSTM) shows promising results in predicting time series…

Machine Learning · Computer Science 2021-07-30 Koushik Roy , Abtahi Ishmam , Kazi Abu Taher

Short-term load forecasting is one of the crucial sections in smart grid. Precise forecasting enables system operators to make reliable unit commitment and power dispatching decisions. With the advent of big data, a number of artificial…

Signal Processing · Electrical Eng. & Systems 2018-09-27 Tiantian Li , Bo Wang , Min Zhou , Junzo Watada

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

With the growing prevalence of smart grid technology, short-term load forecasting (STLF) becomes particularly important in power system operations. There is a large collection of methods developed for STLF, but selecting a suitable method…

Machine Learning · Computer Science 2018-11-06 Cong Feng , Jie Zhang

Accurate electrical load forecasting is crucial for optimizing power system operations, planning, and management. As power systems become increasingly complex, traditional forecasting methods may fail to capture the intricate patterns and…

Systems and Control · Electrical Eng. & Systems 2024-11-26 Elias Raffoul , Mingjian Tuo , Cunzhi Zhao , Tianxia Zhao , Meng Ling , Xingpeng Li

Accurate electrical load forecasting is of great importance for the efficient operation and control of modern power systems. In this work, a hybrid long short-term memory (LSTM)-based model with online correction is developed for day-ahead…

Systems and Control · Electrical Eng. & Systems 2024-03-07 Nan Lu , Quan Ouyang , Yang Li , Changfu Zou

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

Short-term load forecasting (STLF) is vital for the effective and economic operation of power grids and energy markets. However, the non-linearity and non-stationarity of electricity demand as well as its dependency on various external…

Short-term industrial enterprises power system forecasting is an important issue for both load control and machine protection. Scientists focus on load forecasting but ignore other valuable electric-meters which should provide guidance of…

Machine Learning · Computer Science 2024-06-04 Xiaoqiao Chen

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

Electric energy is difficult to store, requiring stricter control over its generation, transmission, and distribution. A persistent challenge in power systems is maintaining real-time equilibrium between electricity demand and supply.…

Signal Processing · Electrical Eng. & Systems 2025-05-27 Aurausp Maneshni
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