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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

Against the backdrop of increasingly severe global environmental changes, accurately predicting and meeting renewable energy demands has become a key challenge for sustainable business development. Traditional energy demand forecasting…

Machine Learning · Computer Science 2024-10-22 Te Li , Mengze Zhang , Yan Zhou

Accumulated precipitation forecasts are of high socioeconomic importance for agriculturally dominated societies in northern tropical Africa. In this study, we analyze the performance of nine operational global ensemble prediction systems…

Applications · Statistics 2017-08-16 Peter Vogel , Peter Knippertz , Andreas H. Fink , Andreas Schlueter , Tilmann Gneiting

Solar based electricity generations have experienced strong and impactful growth in recent years. The regulation, scheduling, dispatching, and unit commitment of intermittent solar power is dependent on the accuracy of the forecasting…

Systems and Control · Electrical Eng. & Systems 2020-03-30 Shaktinarayana Mishra , Lokanath Tripathy , Prachitara Satapathy , P. K. Dash , Nitasha Sahani

Driven by global climate change and the ongoing energy transition, the coupling between power supply capabilities and meteorological factors has become increasingly significant. Over the long term, accurately quantifying the power…

Machine Learning · Computer Science 2026-04-30 Xiaochong Dong , Jun Dan , Yingyun Sun , Yang Liu , Xuemin Zhang , Shengwei Mei

The Probabilistic Solar Particle Event foRecasting (PROSPER) model predicts the probability of occurrence and the expected peak flux of Solar Energetic Particle (SEP) events. Predictions are derived for a set of integral proton energies…

The advancement of distributed generation technologies in modern power systems has led to a widespread integration of renewable power generation at customer side. However, the intermittent nature of renewable energy poses new challenges to…

Machine Learning · Computer Science 2023-01-31 Devinder Kaur , Shama Naz Islam , Md. Apel Mahmud , Md. Enamul Haque , Adnan Anwar

Accurate and reliable forecasting of photovoltaic (PV) power generation is crucial for grid operations, electricity markets, and energy planning, as solar systems now contribute a significant share of the electricity supply in many…

Applications · Statistics 2025-08-22 Martin János Mayer , Ágnes Baran , Sebastian Lerch , Nina Horat , Dazhi Yang , Sándor Baran

In the process of decarbonization, the global energy mix is shifting from fossil fuels to renewables. To study decarbonization pathways, large-scale energy system models are utilized. These models require accurate data on renewable…

Physics and Society · Physics 2021-01-22 Alexander Kies , Bruno U. Schyska , Mariia Bilousova , Omar El Sayed , Jakub Jurasz , Horst Stöcker

The high variability of weather parameters is making photovoltaic energy generation intermittent and narrowly controllable. Threatened by the sudden discontinuity between the load and the grid, energy management for smart grid systems…

Signal Processing · Electrical Eng. & Systems 2019-10-23 Mohamed Massaoudi , Ines Chihi , Lilia Sidhom , Mohamed Trabelsi , Shady S. Refaat , Fakhreddine S. Oueslati

Rising penetration levels of (residential) photovoltaic (PV) power as distributed energy resource pose a number of challenges to the electricity infrastructure. High quality, general tools to provide accurate forecasts of power production…

Machine Learning · Computer Science 2020-10-16 Elizaveta Kharlova , Daniel May , Petr Musilek

Renewable energy forecasting is attaining greater importance due to its constant increase in contribution to the electrical power grids. Solar energy is one of the most significant contributors to renewable energy and is dependent on solar…

Machine Learning · Computer Science 2025-10-08 V. Gunasekaran , K. K. Kovi , S. Arja , R. Chimata

The increasing penetration of Renewable Energy Sources (RES) requires more Flexibility Resources (FR), generally thermal units and storages, must be kept in the system to accommodate the uncertainties from RES. The challenge is how the…

Optimization and Control · Mathematics 2015-12-31 Hongxing Ye , Jianhui Wang , Zuyi Li

Solar energy is one of the most promising renewable energy resources. Forecasting photovoltaic power generation is an important way to increase photovoltaic penetration. However, the difficulty in qualifying the uncertainty of PV power…

Machine Learning · Computer Science 2024-10-10 Xuan Yang , Yunxuan Dong , Lina Yang , Thomas Wu

To reach ambitious European CO$_2$ emission reduction targets, most scenarios of future European electricity systems rely on large shares of wind and solar photovoltaic power generation. We interpolate between two concepts for balancing the…

Physics and Society · Physics 2017-06-19 David P. Schlachtberger , Tom Brown , Stefan Schramm , Martin Greiner

In recent years, the energy-water nexus literature has recognized that the electricity and water infrastructure that enable the production, distribution, and consumption of these two commodities is fundamentally intertwined. Electric power…

Systems and Control · Electrical Eng. & Systems 2019-08-29 Steffi O. Muhanji , Amro M. Farid

Accurate renewable energy production forecasting has become a priority as the share of intermittent energy sources on the grid increases. Recent work has shown that convolutional deep learning models can successfully be applied to forecast…

Image and Video Processing · Electrical Eng. & Systems 2022-01-24 Sebastian Bosma , Negar Nazari

As renewable distributed energy resources (DERs) penetrate the power grid at an accelerating speed, it is essential for operators to have accurate solar photovoltaic (PV) energy forecasting for efficient operations and planning. Generally,…

Machine Learning · Statistics 2017-09-26 Hossein Sangrody , Morteza Sarailoo , Ning Zhou , Nhu Tran , Mahdi Motalleb , Elham Foruzan

Distribution system end users are transforming from passive to active participants, marked by the push towards widespread adoption of edge-level Distributed Energy Resources (DERs). This paper addresses the challenges in distribution system…

Systems and Control · Electrical Eng. & Systems 2025-10-28 Arun Kumar Karngala , Chanan Singh , Le Xie

Currently the UK Electric market is guided by load (demand) forecasts published every thirty minutes by the regulator. A key factor in predicting demand is weather conditions, with forecasts published every hour. We present HYENA: a hybrid…

Machine Learning · Computer Science 2022-05-24 Maria Eleni Athanasopoulou , Justina Deveikyte , Alan Mosca , Ilaria Peri , Alessandro Provetti