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Electricity consumption forecasting has vital importance for the energy planning of a country. Of the enabling machine learning models, support vector regression (SVR) has been widely used to set up forecasting models due to its superior…

Neural and Evolutionary Computing · Computer Science 2022-09-16 Yukun Bao , Liang Shen , Xiaoyuan Zhang , Yanmei Huang , Changrui Deng

Load forecasting has always been a challenge for grid operators due to the growing complexity of power systems. The increase in extreme weather and the need for energy from customers has led to load forecasting sometimes failing. This…

Signal Processing · Electrical Eng. & Systems 2025-10-09 Nishant Gadde , Yoshua Alexander , Sarvesh Parthasarthy , Arman Allidina

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 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

In this paper, a short-term load forecasting approach based network reconfiguration is proposed in a parallel manner. Specifically, a support vector regression (SVR) based short-term load forecasting approach is designed to provide an…

Systems and Control · Computer Science 2017-11-30 Yi Gu , Huaiguang Jiang , Jun Jason Zhang , Yingchen Zhang , Eduard Muljadi , Francisco J. Solis

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…

Machine Learning · Computer Science 2023-06-21 Liping Zhang , Di Wu , Xin Luo

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

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…

To enhance the accuracy of power load forecasting in wind farms, this study introduces an advanced combined forecasting method that integrates Variational Mode Decomposition (VMD) with an Improved Particle Swarm Optimization (IPSO)…

Machine Learning · Computer Science 2024-12-17 Qiang Xie

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

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…

Systems and Control · Electrical Eng. & Systems 2020-07-02 Ming Dong , Jian Shi , QingXin Shi

Accurate day-ahead peak load forecasting is crucial not only for power dispatching but also has a great interest to investors and energy policy maker as well as government. Literature reveals that 1% error drop of forecast can reduce 10…

Machine Learning · Computer Science 2021-11-02 Yanmei Huang , Najmul Hasan , Changrui Deng , Yukun Bao

Accurate time series prediction over long future horizons is challenging and of great interest to both practitioners and academics. As a well-known intelligent algorithm, the standard formulation of Support Vector Regression (SVR) could be…

Machine Learning · Computer Science 2014-01-14 Yukun Bao , Tao Xiong , Zhongyi Hu

Short Term Load forecasting in this paper uses input data dependent on parameters such as load for current hour and previous two hours, temperature for current hour and previous two hours, wind for current hour and previous two hours, cloud…

Neural and Evolutionary Computing · Computer Science 2009-12-08 Mrs. J. P. Rothe , Dr. A. K. Wadhwani , Dr. Mrs. S. Wadhwani

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

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

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) 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 load forecasting is essential to the operation of modern electric power systems. Given the sensitivity of electricity demand to weather variability and temporal dynamics, capturing non-linear patterns is essential for long-term…

Machine Learning · Computer Science 2025-07-31 Abhiram Bhupatiraju , Sung Bum Ahn

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
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