Multi-step ahead wind power forecasting based on multi-feature wavelet decomposition and convolution-gated recurrent unit model

Electrical Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 12, 2025

Language: Английский

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Deep learning approaches for robust prediction of large-scale renewable energy generation: A comprehensive comparative study from a national context

Intelligent Data Analysis, Journal Year: 2025, Volume and Issue: unknown

Published: March 19, 2025

Precise forecasting of renewable energy generation is crucial for ensuring grid stability and enhancing the efficiency management systems. This research develops rigorously evaluates a range deep learning models—such as Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM) networks, Gated Units (GRUs), Bidirectional LSTM (BiLSTM) architectures—for predicting solar, wind, total production at national scale. These models are systematically benchmarked against traditional machine approaches gradient boosting methods to determine their predictive capabilities. The findings demonstrate that incorporating memory mechanisms consistently surpass conventional methods, with BiLSTM standing out most precise dependable model. Furthermore, study investigates fully connected artificial neural networks (ANNs) ConvLSTM2D models, reinforcing advantages memory-based architectures in modeling temporal relationships. By introducing robust framework large-scale forecasting, this represents considerable leap forward compared techniques. results highlight transformative potential improving accuracy, thereby facilitating more effective planning smooth integration into power grids.

Language: Английский

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Smart Forecasting With AI

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 165 - 184

Published: Feb. 7, 2025

The use of smart forecasting in artificial intelligence (AI) to transform energy storage and consumption is examined this chapter. Artificial revolutionizing the systems industry particularly areas grids management renewable by analysing large volumes data finding patterns. In order predict generation maintain grid stability maximize chapter explores crucial roles that AI machine learning play. Additionally, it emphasizes how big data, can be combined increase accuracy which has important ramifications for sources like solar wind. effective commodity market operations demonstrated real-world case studies. Chapter also addresses ethical social issues deployment focusing on cooperation with human expertise.

Language: Английский

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Integrated Optimal Energy Management of Multi-Microgrid Network Considering Energy Performance Index: Global Chance-Constrained Programming Framework

Published: Jan. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Language: Английский

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A Three-Step Weather Data Approach in Solar Energy Prediction Using Machine Learning

Renewable energy focus, Journal Year: 2024, Volume and Issue: 50, P. 100615 - 100615

Published: Aug. 23, 2024

Solar energy plays a critical part in lowering CO2 emissions and other greenhouse gases when integrated into the grid. Higher solar penetration is hindered by its intermittency leading to reliability issues. To forecast production, this study suggests three-step forecasting method that selects weather variables with moderate strong positive correlation radiation using Pearson coefficient analysis. Low-level data fusion used combine inputs from reliable local station an on-site station, significantly improving model's accuracy regardless of machine learning used. Weather was obtained Kisanhub Station located Cranfield University, UK meteorological Bedford, UK. In addition, PV power supply four plants. Using Regression Learner app MATLAB, proposed architecture tested on utility scale plant (1 MW), showing 6% 13% prediction improvement compared solely respectively. It further validated three residential rooftop systems (8 kW, 10.5 kW 15 kW), achieving root-mean square values 0.0984, 0.0885, 0.1425 The pre-processed both rescaling list-wise deletion methods. Training testing 1 MW divided 75% 25% respectively, while 100% plants for validation.

Language: Английский

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Sustainable Energy Consumption Analysis through Data Driven Insights

International Journal of Innovative Science and Research Technology (IJISRT), Journal Year: 2024, Volume and Issue: unknown, P. 2386 - 2401

Published: May 11, 2024

Energy is the backbone of our society, supporting daily activities and driving progress. It plays a crucial role in shaping modern way life. The future global energy consumption influenced by many factors, including demographics, economic dynamics, technological developments, political actions, environmental demands geopolitical considerations. As world's population continues to grow urbanize, demand for increasing. At same time, rapid innovations are landscape changing production, distribution patterns. In midst this development, it very important optimize consumption, accurately anticipate needs, curb climate change, limit emissions greenhouse gasses, fight against pollution promote sustainability. This study includes an in-depth analysis historical trends, assessing multiple benefits renewable integration, estimating carbon emissions, formulating practical policy recommendations providing empirically informed insights. work based on various data obtained from platforms such as Kaggle using advanced visualization techniques Power BI dashboards. provides invaluable perspectives penetration sources into mix, strategic needs achieve sustainable use.

Language: Английский

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Machine Learning Forecasting Model for Solar Energy Radiation

International Journal of Computer Theory and Engineering, Journal Year: 2024, Volume and Issue: 16(2), P. 66 - 75

Published: Jan. 1, 2024

Language: Английский

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Integrated Optimal Energy Management of Multi-Microgrid Network Considering Energy Performance Index: Global Chance-Constrained Programming Framework

Energies, Journal Year: 2024, Volume and Issue: 17(17), P. 4367 - 4367

Published: Sept. 1, 2024

Distributed generation (DG) sources play a special role in the operation of active energy networks. The microgrid (MG) is known as suitable substrate for development and installation DGs. However, future distribution networks will consist more interconnected complex MGs, called multi-microgrid (MMG) Therefore, management such an system major challenge network operators. This paper presents new method MMG presence battery storage, renewable sources, demand response (DR) programs. To show performance each connected MG’s inefficient utilization its available capacity, index unused power capacity (UPC) defined, which indicates availability individual MG. uncertainties associated with load output wind solar are handled by employing chance-constrained programming (CCP) optimization framework model. proposed CCP ensures safe at desired confidence level involving various problem while optimizing operating costs under Mixed-Integer Linear Programming (MILP). model assessed on sample concerning DC flow limitations. procured MG exchanges investigated discussed.

Language: Английский

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Role of AI and IoT in Advancing Renewable Energy Use in Agriculture

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 5984 - 5984

Published: Nov. 28, 2024

This paper discusses how integrating renewable energy, AI, and IoT becomes important in promoting climate-smart agriculture. Due to the changing climate, rise energy costs, ensuring food security, agriculture faces unprecedented challenges; therefore, development toward innovative technologies is emerging for its sustainability efficiency. review synthesizes existing literature systematically identify AI could optimize resource management, increase productivity, reduce greenhouse gas emissions within an agricultural context. Key findings pointed importance of managing resources sustainably, scalability technologies, and, finally, policy interventions ensure technology adoption. The further outlines trends global adoption smart solutions, indicating areas commonality difference emphasizing need focused policies capacity-building initiatives that will help, particularly developing world, benefits such innovations. Eventually, this research covers some gaps understanding IoT, jointly contribute driving towards a greener more resilient sector.

Language: Английский

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A Comprehensive Overview and Future Prospectives of Networked Microgrids for Emerging Power Systems

Smart Grids and Sustainable Energy, Journal Year: 2024, Volume and Issue: 9(2)

Published: Dec. 2, 2024

Functionally inter-working and physically interconnected groupings of microgrids are known as networked microgrids. Networked evolved a ideational function model for prospective distribution systems because the vast remarkable use smart grid innovations, fresh operations ideals, participation partners. Much labor is required to facilitate attain excellent coordination, besides physical, communication, operational coupling. The state-of-the-art approaches operating controlling microgrids' energy management described evaluated in this article. An assessment transactive using blockchain technology conducted. review discusses application machine learning techniques sheds light on demand-side within optimization applications reviewed. Criteria, networking rules, communication technologies appropriate microgrids, well both manners operation: isolated grid-connected, were recognized. prospects, difficulties, possible ways regarding enhancing resilience current utilization methods enhance power system presented.Additionally, study tackles cybersecurity challenges unique including various types cyberattacks strategies detection mitigation. After thorough review, paper proposes several recommendations further research development. These include advancing leading-edge control approaches, technology, prioritizing resilience, refining framework employing artificial intelligence implementation

Language: Английский

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