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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,…

机器学习 · 计算机科学 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…

机器学习 · 计算机科学 2021-11-24 Yuqi Zhou , Arun Sukumaran Nair , David Ganger , Abhinandan Tripathi , Chaitanya Baone , Hao Zhu

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…

机器学习 · 计算机科学 2025-06-06 Asier Diaz-Iglesias , Xabier Belaunzaran , Ane M. Florez-Tapia

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…

最优化与控制 · 数学 2017-02-28 The-Hien Dang-Ha , Filippo Maria Bianchi , Roland Olsson

Mid-term electricity load forecasting (LF) plays a critical role in power system planning and operation. To address the issue of error accumulation and transfer during the operation of existing LF models, a novel model called error…

机器学习 · 计算机科学 2023-06-21 Liping Zhang , Di Wu , Xin Luo

Recent developments related to the energy transition pose particular challenges for distribution grids. Hence, precise load forecasts become more and more important for effective grid management. Novel modeling approaches such as the…

机器学习 · 计算机科学 2023-05-19 Elena Giacomazzi , Felix Haag , Konstantin Hopf

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…

信号处理 · 电气工程与系统科学 2022-05-17 Haris Mansoor , Sarwan Ali , Imdadullah Khan , Naveed Arshad , Muhammad Asad Khan , Safiullah Faizullah

Long-term load forecast (LTLF) for area distribution feeders is one of the most critical tasks frequently performed in electric distribution utility companies. For a specific planning area, cost-effective system upgrades can only be planned…

系统与控制 · 电气工程与系统科学 2020-07-02 Ming Dong , Jian Shi , QingXin Shi

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…

机器学习 · 计算机科学 2022-01-04 Ali Bou Nassif , Bassel Soudan , Mohammad Azzeh , Imtinan Attilli , Omar AlMulla

The scheduling and operation of power system becomes prominently complex and uncertain, especially with the penetration of distributed power. Load forecasting matters to the effective operation of power system. This paper proposes a novel…

计算工程、金融与科学 · 计算机科学 2019-05-10 Tinghui Ouyang , Yusen He , Huajin Li , Zhiyu Sun , Stephen Baek

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…

机器学习 · 计算机科学 2025-02-19 Quoc Viet Nguyen , Joaquin Delgado Fernandez , Sergio Potenciano Menci

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…

应用统计 · 统计学 2021-10-20 Junjie Hu , Brenda López Cabrera , Awdesch Melzer

Short-term load forecasting is a critical element of power systems energy management systems. In recent years, probabilistic load forecasting (PLF) has gained increased attention for its ability to provide uncertainty information that helps…

机器学习 · 计算机科学 2019-03-27 Qicheng Chang , Yishen Wang , Xiao Lu , Di Shi , Haifeng Li , Jiajun Duan , Zhiwei Wang

Short-term load forecasting is of paramount importance in the efficient operation and planning of power systems, given its inherent non-linear and dynamic nature. Recent strides in deep learning have shown promise in addressing this…

机器学习 · 计算机科学 2023-09-20 Paapa Kwesi Quansah , Edwin Kwesi Ansah Tenkorang

Short-term forecasts of energy consumption are invaluable for the operation of energy systems, including low voltage electricity networks. However, network loads are challenging to predict when highly desegregated to small numbers of…

应用统计 · 统计学 2023-01-10 Ciaran Gilbert , Jethro Browell , Bruce Stephen

Load points are one of the most vital parts of power systems. Due to the new load forms and programs introduced in the demand side, the load-serving entities (LSEs) no longer deal with lump loads, but rather with more dynamic, rational and…

系统与控制 · 电气工程与系统科学 2021-10-13 Ahmed S. Alahmed , Muhammed M. Almuhaini

Accurate load forecasting is critical for reliable and efficient planning and operation of electric power grids. In this paper, we propose a unifying deep learning framework for load forecasting, which includes time-varying feature…

机器学习 · 计算机科学 2023-05-10 Jing Xiong , Yu Zhang

Accurate household short-term energy consumption forecasting (STECF) is crucial for home energy management, but it is technically challenging, due to highly random behaviors of individual residential users. To improve the accuracy of STECF…

信号处理 · 电气工程与系统科学 2024-02-16 Heyang Yu , Yuxi Sun , Yintao Liu , Guangchao Geng , Quanyuan Jiang

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…

In this paper, the modeling of building end-use energy profile is comprehensively investigated. Top-down and Bottom-up approaches are discussed with a focus on the latter for better integration with occupant information. Compared to the…

应用统计 · 统计学 2016-11-17 Zhaoyi Kang , Ming Jin , Costas J. Spanos
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