In recent years, a variety of wind forecasting models have been developed, prompting necessity to review the abundant methods to gain insights of the state-of-the-art development status. However, existing literature reviews only focus on a subclass of methods, such as multi-objective optimization and machine learning methods while lacking the full particulars of wind forecasting field. Furthermore, the classification of wind forecasting methods is unclear and incomplete, especially considering the rapid development of this field. Therefore, this article aims to provide a systematic review of the existing deterministic and probabilistic wind forecasting methods, from the perspectives of data source, model evaluation framework, technical background, theoretical basis, and model performance. It is expected that this work will provide junior researchers with broad and detailed information on wind forecasting for their future development of more accurate and practical wind forecasting models.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823194PMC
http://dx.doi.org/10.1016/j.isci.2022.105804DOI Listing

Publication Analysis

Top Keywords

wind forecasting
24
forecasting methods
12
deterministic probabilistic
8
forecasting models
8
forecasting
7
wind
7
methods
6
overview deterministic
4
probabilistic forecasting
4
methods wind
4

Similar Publications

In this paper, a robust fuzzy multi-objective framework is performed to optimize the dispersed and hybrid renewable photovoltaic-wind energy resources in a radial distribution network considering uncertainties of renewable generation and network demand. A novel multi-objective improved gradient-based optimizer (MOIGBO) enhanced with Rosenbrock's direct rotational technique to overcome premature convergence is proposed to determine the problem optimal decision variables. The deterministic optimization framework without uncertainty minimizes active energy loss, unmet customer energy, and renewable generation costs.

View Article and Find Full Text PDF

Regional patterns and climatic predictors of viruses in honey bee (Apis mellifera) colonies over time.

Sci Rep

January 2025

Department of Biochemistry and Molecular Biology, Michael Smith Laboratories, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada.

Honey bee viruses are serious pathogens that can cause poor colony health and productivity. We analyzed a multi-year longitudinal dataset of abundances of nine honey bee viruses (deformed wing virus A, deformed wing virus B, black queen cell virus, sacbrood virus, Lake Sinai virus, Kashmir bee virus, acute bee paralysis virus, chronic bee paralysis virus, and Israeli acute paralysis virus) in colonies located across Canada to describe broad trends in virus intensity and occurrence among regions and years. We also tested climatic variables (temperature, wind speed, and precipitation) as predictors in an effort to understand possible drivers underlying seasonal patterns in viral prevalence.

View Article and Find Full Text PDF

This study presents an in-depth analysis and evaluation of the performance of a standard 200 W solar cell, focusing on the energy and exergy aspects. A significant research gap exists in the comprehensive integration of numerical models with advanced machine-learning approaches, specifically emotional artificial neural networks (EANN), to simulate and optimize the electrical characteristics and efficiency of solar panels. To address this gap, a numerical model alongside a novel EANN was employed to simulate the system's electrical characteristics, including open-circuit voltage, short-circuit current, system resistances, maximum power point characteristics, and characteristic curves.

View Article and Find Full Text PDF

Solar energy generated from photovoltaic panel is an important energy source that brings many benefits to people and the environment. This is a growing trend globally and plays an increasingly important role in the future of the energy industry. However, it intermittent nature and potential for distributed system use require accurate forecasting to balance supply and demand, optimize energy storage, and manage grid stability.

View Article and Find Full Text PDF

Coordinated charging of EV fleets in community parking lots to maximize benefits using a three-stage energy management system.

Sci Rep

December 2024

Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine.

The rapid global adoption of electric vehicles (EVs) necessitates the development of advanced EV charging infrastructure to meet rising energy demands. In particular, community parking lots (CPLs) offer significant opportunities for coordinating EVs' charging. By integrating energy storage systems (ESSs), renewable energy sources (RESs), and building prosumers, substantial reductions in peak load and electricity costs can be achieved, while simultaneously promoting environmental sustainability.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!