Metaheuristic Optimization in Power Engineering Algorithms and power dispatch using MATLAB®-based software
A metaheuristic is a higher-level procedure designed to find, generate, or select a heuristic or partial search algorithm that may provide a sufficiently good solution to an optimization problem with incomplete or imperfect information or limited computation capacity. Metaheuristics can often find g...
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| Médium: | E-kniha |
| Jazyk: | English |
| Vydavateľské údaje: |
Stevenage
The Institution of Engineering and Technology
2024
Institution of Engineering and Technology |
| Vydanie: | 2 |
| Edícia: | Energy Engineering |
| Predmet: | |
| ISBN: | 1837241376, 9781837241378 |
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| Abstract | A metaheuristic is a higher-level procedure designed to find, generate, or select a heuristic or partial search algorithm that may provide a sufficiently good solution to an optimization problem with incomplete or imperfect information or limited computation capacity. Metaheuristics can often find good solutions with less computational effort than other algorithms. Modern and emerging power systems, with the growing complexity of distributed and intermittent generation and EV charging, are an application for such methods.
The new edition of Metaheuristic Optimization in Power Engineering in two volumes uses a MATLAB-based software package for testing and comparing methods, and includes several new and substantially revised and updated chapters.
Volume 1 covers principles and key algorithms, such as genetic and swarm algorithms, gravitational and metaheuristic algorithms, power flow and power dispatch under consideration of renewable generation.
Volume 2 focuses on power distribution networks, including power flow, voltage control and regulation, optimisation of generation placement and sizing, and state estimation analysis.
This reference for researchers and advanced students working on power system analysis and optimization offers an overview of metaheuristic optimization approaches to solving problems in modern power systems. |
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| AbstractList | A metaheuristic is a higher-level procedure designed to find, generate, or select a heuristic or partial search algorithm that may provide a sufficiently good solution to an optimization problem with incomplete or imperfect information or limited computation capacity. Metaheuristics can often find good solutions with less computational effort than other algorithms. Modern and emerging power systems, with the growing complexity of distributed and intermittent generation and EV charging, are an application for such methods.
The new edition of Metaheuristic Optimization in Power Engineering in two volumes uses a MATLAB-based software package for testing and comparing methods, and includes several new and substantially revised and updated chapters.
Volume 1 covers principles and key algorithms, such as genetic and swarm algorithms, gravitational and metaheuristic algorithms, power flow and power dispatch under consideration of renewable generation.
Volume 2 focuses on power distribution networks, including power flow, voltage control and regulation, optimisation of generation placement and sizing, and state estimation analysis.
This reference for researchers and advanced students working on power system analysis and optimization offers an overview of metaheuristic optimization approaches to solving problems in modern power systems. A metaheuristic is a higher-level procedure designed to find, generate, or select a heuristic or partial search algorithm that may provide a sufficiently good solution to an optimization problem with incomplete or imperfect information or limited computation capacity. Metaheuristics can often find good solutions with less computational effort than other algorithms. Modern and emerging power systems, with the growing complexity of distributed and intermittent generation and EV charging, are an application for such methods.The new edition of Metaheuristic Optimization in Power Engineering in two volumes uses a MATLAB-based software package for testing and comparing methods, and includes several new and substantially revised and updated chapters.Volume 1 covers principles and key algorithms, such as genetic and swarm algorithms, gravitational and metaheuristic algorithms, power flow and power dispatch under consideration of renewable generation.Volume 2 focuses on power distribution networks, including power flow, voltage control and regulation, optimisation of generation placement and sizing, and state estimation analysis.This reference for researchers and advanced students working on power system analysis and optimization offers an overview of metaheuristic optimization approaches to solving problems in modern power systems. |
| Author | Radosavljević, Jordan |
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| Keywords | gravitational algorithms power flow power system optimisation swarm algorithms clean energy genetic algorithms green energy renewable power renewable energy smart grids power dispatch power systems power system control distributed energy power grids metaheuristic algorithms |
| Language | English |
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| PublicationDate | 2024 2024-10-03 |
| PublicationDateYYYYMMDD | 2024-01-01 2024-10-03 |
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| PublicationDecade | 2020 |
| PublicationPlace | Stevenage |
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| PublicationSeriesTitle | Energy Engineering |
| PublicationYear | 2024 |
| Publisher | The Institution of Engineering and Technology Institution of Engineering and Technology |
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| Snippet | A metaheuristic is a higher-level procedure designed to find, generate, or select a heuristic or partial search algorithm that may provide a sufficiently good... |
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| SubjectTerms | Energy industries Engineering mathematics Mathematical optimization Power Resources TECHNOLOGY & ENGINEERING |
| Subtitle | Algorithms and power dispatch using MATLAB®-based software |
| TableOfContents | Chapter 1: Overview of metaheuristic optimization -- Chapter 2: Genetic algorithms -- Chapter 3: Particle swarm optimization -- Chapter 4: Gravitational search algorithm -- Chapter 5: Hybrid metaheuristic algorithms -- Chapter 6: Applications to power system problems - literature overview -- Chapter 7: Power flow calculation -- Chapter 8: Optimal power flow -- Chapter 9: Optimal power flow considering WT and PV generation -- Chapter 10: Optimal reactive power dispatch -- Chapter 11: Combined economic and emission dispatch -- Chapter 12: Dynamic economic dispatch |
| Title | Metaheuristic Optimization in Power Engineering |
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