English
Related papers

Related papers: Two-Stage Hybrid Day-Ahead Solar Forecasting

200 papers

This paper considers a typical solar installations scenario with limited sensing resources. In the literature, there exist either day-ahead solar generation prediction methods with limited accuracy, or high accuracy short timescale methods…

Applications · Statistics 2015-08-12 Yubo Wang , Bin Wang , Rui Huang , Chi-Cheng Chu , Hemanshu R. Pota , Rajit Gadh

The growing proliferation in solar deployment, especially at distribution level, has made the case for power system operators to develop more accurate solar forecasting models. This paper proposes a solar photovoltaic (PV) generation…

Computational Engineering, Finance, and Science · Computer Science 2017-10-12 Mohana Alanazi , Mohsen Mahoor , Amin Khodaei

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

The ability to accurately forecast power generation from renewable sources is nowadays recognised as a fundamental skill to improve the operation of power systems. Despite the general interest of the power community in this topic, it is not…

Estimation of the generated power of renewable energy resources is in general important for planning operations as well as demand balance and power quality. This paper addresses the problem of the estimation of the short-term (3-hour ahead)…

Systems and Control · Electrical Eng. & Systems 2020-11-20 L. A. Dao , L. Ferrarini , D. La Carrubba

Solar power harbors immense potential in mitigating climate change by substantially reducing CO$_{2}$ emissions. Nonetheless, the inherent variability of solar irradiance poses a significant challenge for seamlessly integrating solar power…

Machine Learning · Computer Science 2023-10-24 Oussama Boussif , Ghait Boukachab , Dan Assouline , Stefano Massaroli , Tianle Yuan , Loubna Benabbou , Yoshua Bengio

Regional solar power forecasting, which involves predicting the total power generation from all rooftop photovoltaic systems in a region holds significant importance for various stakeholders in the energy sector. However, the vast amount of…

Machine Learning · Computer Science 2024-03-05 Maneesha Perera , Julian De Hoog , Kasun Bandara , Damith Senanayake , Saman Halgamuge

This paper addresses a central challenge of jointly considering shorter-term (e.g. hourly) and longer-term (e.g. yearly) uncertainties in power system planning with increasing penetration of renewable and storage resources. In conventional…

Systems and Control · Electrical Eng. & Systems 2021-09-13 Chao Yan , Xinbo Geng , Zhaohong Bie , Le Xie

Due to the rise in the use of renewable energies as an alternative to traditional ones, and especially solar energy, there is increasing interest in studying how to address photovoltaic forecasting in the face of the challenge of…

Computer Vision and Pattern Recognition · Computer Science 2026-02-18 Ines Montoya-Espinagosa , Antonio Agudo

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

Using solar power in the process industry can reduce greenhouse gas emissions and make the production process more sustainable. However, the intermittent nature of solar power renders its usage challenging. Building a model to predict…

Systems and Control · Electrical Eng. & Systems 2022-05-17 Yu Yang , Jia Mao , Richard Nguyen , Annas Tohmeh , Hen-Geul Yeh

Accurate forecasts for day-ahead photovoltaic (PV) power generation are crucial to support a high PV penetration rate in the local electricity grid and to assure stability in the grid. We use state-of-the-art tree-based machine learning…

Machine Learning · Computer Science 2023-12-04 Nick Berlanger , Noah van Ophoven , Tim Verdonck , Ines Wilms

There has been an increasing trend in the electric power system from a centralized generation-driven grid to a more reliable, environmental friendly, and customer-driven grid. One of the most important issues which the designers of smart…

Systems and Control · Computer Science 2015-02-03 Kianoosh G. Boroojeni , Shekoufeh Mokhtari , M. H. Amini , S. S. Iyengar

The output of solar power generation is significantly dependent on the available solar radiation. Thus, with the proliferation of PV generation in the modern power grid, forecasting of solar irradiance is vital for proper operation of the…

Applications · Statistics 2022-09-05 Kwasi Opoku , Svetlana Lucemo , Qun Zhou Sun , Aleksandar Dimitrovski

In two-stage electricity markets, renewable power producers enter the day-ahead market with a forecast of future power generation and then reconcile any forecast deviation in the real-time market at a penalty. The choice of the forecast…

Systems and Control · Electrical Eng. & Systems 2025-01-15 Vladimir Dvorkin

This paper presents a parametric model approach to address the problem of photovoltaic generation forecasting in a scenario where measurements of meteorological variables, i.e., solar irradiance and temperature, are not available at the…

Systems and Control · Electrical Eng. & Systems 2024-12-20 Daniele Pepe , Gianni Bianchini , Antonio Vicino

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

Photovoltaic systems have been widely deployed in recent times to meet the increased electricity demand as an environmental-friendly energy source. The major challenge for integrating photovoltaic systems in power systems is the…

Machine Learning · Statistics 2018-02-13 Reza Zafarani , Sara Eftekharnejad , Urvi Patel

Electricity generated from renewable energy sources has been established as an efficient remedy for both energy shortages and the environmental pollution stemming from conventional energy production methods. Solar and wind power are two of…

Machine Learning · Computer Science 2025-01-06 Charalampos Symeonidis , Nikos Nikolaidis

By the end of 2021, the renewable energy share of the global electricity capacity reached 38.3% and the new installations are dominated by wind and solar energy, showing global increases of 12.7% and 18.5%, respectively. However, both wind…

Machine Learning · Statistics 2024-09-18 Ágnes Baran , Sándor Baran
‹ Prev 1 2 3 10 Next ›