Intelligent Optimization Modelling In Energy Forecasting
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Intelligent Optimization Modelling In Energy Forecasting
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Author : Wei-Chiang Hong
language : en
Publisher: MDPI
Release Date : 2020-04-01
Intelligent Optimization Modelling In Energy Forecasting written by Wei-Chiang Hong and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-01 with Computers categories.
Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent decades, many energy forecasting models have been continuously proposed to improve forecasting accuracy, including traditional statistical models (e.g., ARIMA, SARIMA, ARMAX, multi-variate regression, exponential smoothing models, Kalman filtering, Bayesian estimation models, etc.) and artificial intelligence models (e.g., artificial neural networks (ANNs), knowledge-based expert systems, evolutionary computation models, support vector regression, etc.). Recently, due to the great development of optimization modeling methods (e.g., quadratic programming method, differential empirical mode method, evolutionary algorithms, meta-heuristic algorithms, etc.) and intelligent computing mechanisms (e.g., quantum computing, chaotic mapping, cloud mapping, seasonal mechanism, etc.), many novel hybrid models or models combined with the above-mentioned intelligent-optimization-based models have also been proposed to achieve satisfactory forecasting accuracy levels. It is important to explore the tendency and development of intelligent-optimization-based modeling methodologies and to enrich their practical performances, particularly for marine renewable energy forecasting.
Intelligent Optimization Modelling In Energy Forecasting
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Author : Wei-Chiang Hong
language : en
Publisher:
Release Date : 2020
Intelligent Optimization Modelling In Energy Forecasting written by Wei-Chiang Hong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Electronic computers. Computer science categories.
Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent decades, many energy forecasting models have been continuously proposed to improve forecasting accuracy, including traditional statistical models (e.g., ARIMA, SARIMA, ARMAX, multi-variate regression, exponential smoothing models, Kalman filtering, Bayesian estimation models, etc.) and artificial intelligence models (e.g., artificial neural networks (ANNs), knowledge-based expert systems, evolutionary computation models, support vector regression, etc.). Recently, due to the great development of optimization modeling methods (e.g., quadratic programming method, differential empirical mode method, evolutionary algorithms, meta-heuristic algorithms, etc.) and intelligent computing mechanisms (e.g., quantum computing, chaotic mapping, cloud mapping, seasonal mechanism, etc.), many novel hybrid models or models combined with the above-mentioned intelligent-optimization-based models have also been proposed to achieve satisfactory forecasting accuracy levels. It is important to explore the tendency and development of intelligent-optimization-based modeling methodologies and to enrich their practical performances, particularly for marine renewable energy forecasting.
Hybrid Intelligent Technologies In Energy Demand Forecasting
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Author : Wei-Chiang Hong
language : en
Publisher: Springer
Release Date : 2021-01-02
Hybrid Intelligent Technologies In Energy Demand Forecasting written by Wei-Chiang Hong and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-02 with Business & Economics categories.
This book is written for researchers and postgraduates who are interested in developing high-accurate energy demand forecasting models that outperform traditional models by hybridizing intelligent technologies. It covers meta-heuristic algorithms, chaotic mapping mechanism, quantum computing mechanism, recurrent mechanisms, phase space reconstruction, and recurrence plot theory. The book clearly illustrates how these intelligent technologies could be hybridized with those traditional forecasting models. This book provides many figures to deonstrate how these hybrid intelligent technologies are being applied to exceed the limitations of existing models.
Intelligent Data Driven Modelling And Optimization In Power And Energy Applications
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Author : B Rajanarayan Prusty
language : en
Publisher: CRC Press
Release Date : 2024-05-09
Intelligent Data Driven Modelling And Optimization In Power And Energy Applications written by B Rajanarayan Prusty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-09 with Technology & Engineering categories.
This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include: an exclusive section on essential preprocessing approaches for the data-driven model a detailed overview of data-driven model applications to power system planning and operational activities specific focus on developing forecasting models for renewable generations such as solar PV and wind power, and showcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworks This book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel.
Energy Efficiency Analysis And Intelligent Optimization Of Process Industry
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Author : Zhiqiang Geng
language : en
Publisher: Frontiers Media SA
Release Date : 2023-10-09
Energy Efficiency Analysis And Intelligent Optimization Of Process Industry written by Zhiqiang Geng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-09 with Technology & Engineering categories.
Practical Examples Of Energy Optimization Models
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Author : Samsul Ariffin Abdul Karim
language : en
Publisher: Springer Nature
Release Date : 2020-01-02
Practical Examples Of Energy Optimization Models written by Samsul Ariffin Abdul Karim and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-02 with Technology & Engineering categories.
This book highlights state-of-the-art research on renewable energy integration technology and suitable and efficient power generation, discussing smart grids, renewable energy grid integration, prediction control models, and econometric models for predicting the global solar radiation and factors that affect solar radiation, performance evaluation of photovoltaic systems, and improved energy consumption prediction models. It discusses several methods, algorithms, environmental data-based performance analyses, and experimental results to help readers gain a detailed understanding of the pros and cons of technologies in this rapidly growing area. Accordingly, it offers a valuable resource for students and researchers working on renewable energy optimization models.
Applications Of Date Driven Artificial Intelligence In Integrated Energy Systems
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Author : Qiuye Sun
language : en
Publisher: Frontiers Media SA
Release Date : 2023-01-27
Applications Of Date Driven Artificial Intelligence In Integrated Energy Systems written by Qiuye Sun and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-27 with Technology & Engineering categories.
Artificial Intelligence Based Forecasting And Analytic Techniques For Environment And Economics Management
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Author : Wendong Yang
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-09
Artificial Intelligence Based Forecasting And Analytic Techniques For Environment And Economics Management written by Wendong Yang and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-09 with Science categories.
Computer Vision And Machine Intelligence For Renewable Energy Systems
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Author : Ashutosh Kumar Dubey
language : en
Publisher: Elsevier
Release Date : 2024-09-20
Computer Vision And Machine Intelligence For Renewable Energy Systems written by Ashutosh Kumar Dubey and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-20 with Technology & Engineering categories.
Computer Vision and Machine Intelligence for Renewable Energy Systems offers a practical, systemic guide to the use of computer vision as an innovative tool to support renewable energy integration.This book equips readers with a variety of essential tools and applications: Part I outlines the fundamentals of computer vision and its unique benefits in renewable energy system models compared to traditional machine intelligence: minimal computing power needs, speed, and accuracy even with partial data. Part II breaks down specific techniques, including those for predictive modeling, performance prediction, market models, and mitigation measures. Part III offers case studies and applications to a wide range of renewable energy sources, and finally the future possibilities of the technology are considered. The very first book in Elsevier's cutting-edge new series Advances in Intelligent Energy Systems, Computer Vision and Machine Intelligence for Renewable Energy Systems provides engineers and renewable energy researchers with a holistic, clear introduction to this promising strategy for control and reliability in renewable energy grids. - Provides a sorely needed primer on the opportunities of computer vision techniques for renewable energy systems - Builds knowledge and tools in a systematic manner, from fundamentals to advanced applications - Includes dedicated chapters with case studies and applications for each sustainable energy source
Artificial Neural Networks For Renewable Energy Systems And Real World Applications
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Author : Ammar Hamed Elsheikh
language : en
Publisher: Academic Press
Release Date : 2022-09-08
Artificial Neural Networks For Renewable Energy Systems And Real World Applications written by Ammar Hamed Elsheikh and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-08 with Technology & Engineering categories.
Artificial Neural Networks for Renewable Energy Systems and Real-World Applications presents current trends for the solution of complex engineering problems in the application, modeling, analysis, and optimization of different energy systems and manufacturing processes. With growing research catering to the applications of neural networks in specific industrial applications, this reference provides a single resource catering to a broader perspective of ANN in renewable energy systems and manufacturing processes. ANN-based methods have attracted the attention of scientists and researchers in different engineering and industrial disciplines, making this book a useful reference for all researchers and engineers interested in artificial networks, renewable energy systems, and manufacturing process analysis. - Includes illustrative examples on the design and development of ANNS for renewable and manufacturing applications - Features computer-aided simulations presented as algorithms, pseudocodes and flowcharts - Covers ANN theory for easy reference in subsequent technology specific sections