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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…

Machine Learning · Computer Science 2019-03-27 Qicheng Chang , Yishen Wang , Xiao Lu , Di Shi , Haifeng Li , Jiajun Duan , Zhiwei Wang

Energy (load, wind, photovoltaic) forecasting is significant in the power industry as it can provide a reference for subsequent tasks such as power grid dispatch, thus bringing huge economic benefits. However, there are many differences…

Machine Learning · Computer Science 2024-10-07 Zhixian Wang , Qingsong Wen , Chaoli Zhang , Liang Sun , Leandro Von Krannichfeldt , Shirui Pan , Yi Wang

Accurate load forecasting is critical for efficient and reliable operations of the electric power system. A large part of electricity consumption is affected by weather conditions, making weather information an important determinant of…

Machine Learning · Computer Science 2023-10-16 Jonathan Yang , Mingjian Tuo , Jin Lu , Xingpeng Li

Load forecasts have become an integral part of energy security. Due to the various influencing factors that can be considered in such a forecast, there is also a wide range of models that attempt to integrate these parameters into a system…

Machine Learning · Computer Science 2022-10-19 Philipp Giese

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

Time series forecasting is a critical task across domains such as energy, finance, and meteorology, where accurate predictions enable informed decision-making. While transformer-based and large-parameter models have recently achieved…

Machine Learning · Computer Science 2026-02-11 Julien Guité-Vinet , Alexandre Blondin Massé , Éric Beaudry

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

Generation and load balance is required in the economic scheduling of generating units in the smart grid. Variable energy generations, particularly from wind and solar energy resources, are witnessing a rapid boost, and, it is anticipated…

Machine Learning · Computer Science 2017-04-07 Mohamed Abuella , Badrul Chowdhury

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

In this paper, a stochastic model with regime switching is developed for solar photo-voltaic (PV) power in order to provide short-term probabilistic forecasts. The proposed model for solar PV power is physics inspired and explicitly…

Applications · Statistics 2017-09-19 Raksha Ramakrishna , Anna Scaglione , Vijay Vittal

Solar power becomes one of the most promising renewable energy resources in recent years. However, the weather is continuously changing, and this causes a discontinuity of energy generation. PV Power forecasting is a suitable solution to…

Signal Processing · Electrical Eng. & Systems 2019-10-22 Mohamed Massaoudi , Ines Chihi , Lilia Sidhom , Mohamed Trabelsi , Shady S. Refaat , Fakhreddine S. Oueslati

Electricity is difficult to store, except at prohibitive cost, and therefore the balance between generation and load must be maintained at all times. Electricity is traditionally managed by anticipating demand and intermittent production…

Machine Learning · Computer Science 2024-09-26 Julie Keisler , Margaux Bregere

This paper presents a method for probabilistic wind power forecasting that quantifies and integrates uncertainties from weather forecasts and weather-to-power conversion. By addressing both uncertainty sources, the method achieves…

Applications · Statistics 2025-02-18 Gabriel Dantas , Jethro Browell

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

Short term load forecasting has an essential medium for the reliable, economical and efficient operation of the power system. Most of the existing forecasting approaches utilize fixed statistical models with large historical data for…

Signal Processing · Electrical Eng. & Systems 2019-05-21 Irfan Ahmad Khan , Adnan Akber , Yinliang Xu

Accurate forecasts of the impact of spatial weather and pan-European socio-economic and political risks on hourly electricity demand for the mid-term horizon are crucial for strategic decision-making amidst the inherent uncertainty. Most…

Applications · Statistics 2024-12-06 Monika Zimmermann , Florian Ziel

Meteorological factors (MF) are crucial in day-ahead load forecasting as they significantly influence the electricity consumption behaviors of consumers. Numerous studies have incorporated MF into the load forecasting model to achieve…

Machine Learning · Computer Science 2025-01-07 Yangze Zhou , Guoxin Lin , Gonghao Zhang , Yi Wang

Due to the stochastic nature of photovoltaic (PV) power generation, there is high demand for forecasting PV output to better integrate PV generation into power grids. Systematic knowledge regarding the factors influencing forecast accuracy…

Applications · Statistics 2021-11-04 Thi Ngoc Nguyen , Felix Müsgens

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

Recent studies indicate that the effects of inter-annual climate-based variability in power system planning are significant and that long samples of demand & weather data (spanning multiple decades) should be considered. At the same time,…

Applications · Statistics 2019-05-30 Adriaan P Hilbers , David J Brayshaw , Axel Gandy
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