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The paper introduces a new methodology for assessing on-line the prediction risk of short-term wind power forecasts. The first part of this methodology consists in computing confidence intervals with a confidence level defined by the…

Data Analysis, Statistics and Probability · Physics 2023-10-05 Georges Kariniotakis , Pierre Pinson

Wind power is playing an increasingly important role in electricity markets. However, it's inherent variability and uncertainty cause operational challenges and costs as more operating reserves are needed to maintain system reliability.…

Optimization and Control · Mathematics 2016-03-01 Yishen Wang , Zhi Zhou , Cong Liu , Audun Botterud

Accurate cyclone forecasting is essential for minimizing loss of life, infrastructure damage, and economic disruption. Traditional numerical weather prediction models, though effective, are computationally intensive and prone to error due…

Machine Learning · Computer Science 2025-09-30 Ethan Zachary Lo , Dan Chie-Tien Lo

Renewable energy generation is of utmost importance for global decarbonization. Forecasting renewable energies, particularly wind energy, is challenging due to the inherent uncertainty in wind energy generation, which depends on weather…

Machine Learning · Computer Science 2025-09-22 Lucas English , Mahdi Abolghasemi

Climate change is one of the most concerning issues of this century. Emission from electric power generation is a crucial factor that drives the concern to the next level. Renewable energy sources are widespread and available globally,…

Machine Learning · Computer Science 2020-05-27 Md Amimul Ehsan , Amir Shahirinia , Nian Zhang , Timothy Oladunni

As the energy landscape changes quickly, grid operators face several challenges, especially when integrating renewable energy sources with the grid. The most important challenge is to balance supply and demand because the solar and wind…

Machine Learning · Computer Science 2025-01-24 Kamal Sarkar

This article presents a novel hybrid approach using statistics and machine learning to forecast the national demand of electricity. As investment and operation of future energy systems require long-term electricity demand forecasts with…

Machine Learning · Computer Science 2023-04-12 Tatiana Gonzalez Grandon , Johannes Schwenzer , Thomas Steens , Julia Breuing

Successful implementation of California's Renewable Portfolio Standard (RPS) mandating 33 percent renewable energy generation by 2020 requires inclusion of a robust strategy to mitigate increased risk of energy deficits (blackouts) due to…

Applications · Statistics 2016-09-08 Sam O. George , H. Bola George , Scott V. Nguyen

Since the depletion of fossil fuels, the world has started to rely heavily on renewable sources of energy. With every passing year, our dependency on the renewable sources of energy is increasing exponentially. As a result, complex and…

Machine Learning · Computer Science 2021-04-27 Yasir Saleem Afridi , Kashif Ahmad , Laiq Hassan

Wind and solar generation constitute an increasing share of electricity supply globally. We find that this leads to shifts in the operational dynamics of thermal power plants. Using fixed effects panel regression across seven major U.S.…

Applications · Statistics 2025-01-07 Dhruv Suri , Jacques de Chalendar , Ines Azevedo

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

Accurate short-term solar and wind power predictions play an important role in the planning and operation of power systems. However, the short-term power prediction of renewable energy has always been considered a complex regression…

Systems and Control · Electrical Eng. & Systems 2022-02-08 Wenlong Liao , Birgitte Bak-Jensen , Jayakrishnan Radhakrishna Pillai , Zhe Yang , Kuangpu Liu

Wind energy is becoming an increasingly crucial component of a sustainable grid, but its inherent variability and limited predictability present challenges for grid operators. The energy sector needs novel forecasting techniques that can…

Applications · Statistics 2023-12-05 Zheng Dong , Hanyu Zhang , Shixiang Zhu , Yao Xie , Pascal Van Hentenryck

This study delves into the shift from centralized to decentralized approaches in the electricity industry, with a particular focus on how machine learning (ML) advancements play a crucial role in empowering renewable energy sources and…

Machine Learning · Computer Science 2023-10-25 Mohammad Mohammadi , Ali Mohammadi

With the increasing frequency of natural disasters, operators must prioritize improvements in the existing electric power grid infrastructure to enhance the resilience of the grid. Resilience to extreme weather events necessitates lowering…

Systems and Control · Electrical Eng. & Systems 2023-11-28 Abodh Poudyal , Shishir Lamichhane , Anamika Dubey , Josue Campos do Prado

Accurate projections of wind energy potential under climate change are critical for effective long-term energy planning. While previous studies have highlighted the value of multi-model ensembles, they often fall short in capturing the full…

Atmospheric and Oceanic Physics · Physics 2025-06-02 Andrea Lira-Loarca , Francesco Ferrari , Andrea Mazzino

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 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

Renewable energy is essential for energy security and global warming mitigation. However, power generation from renewable energy sources is uncertain due to volatile weather conditions and complex equipment operations. To improve…

Methodology · Statistics 2020-07-09 Yuchen Shi , Nan Chen

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