https://shop.theiet.org:443/author/jordan-radosavljevicJordan Radosavljevićhttps://shop.theiet.org:443/metaheuristic-optimization-in-power-engineering-2nd-edition-2<p xmlns="http://ns.editeur.org/onix/3.0/reference">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.</p> <p xmlns="http://ns.editeur.org/onix/3.0/reference">The new edition of <i>Metaheuristic Optimization in Power Engineering</i> in two volumes uses a MATLAB-based software package for testing and comparing methods, and includes several new and substantially revised and updated chapters.</p> <p xmlns="http://ns.editeur.org/onix/3.0/reference"><i>Volume 1</i> 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.</p> <p xmlns="http://ns.editeur.org/onix/3.0/reference"><i>Volume 2</i> focuses on power distribution networks, including power flow, voltage control and regulation, optimisation of generation placement and sizing, and state estimation analysis.</p> <p xmlns="http://ns.editeur.org/onix/3.0/reference">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.</p>Mon, 08 Jul 2024 12:13:35 GMThttps://shop.theiet.org:443/metaheuristic-optimization-in-power-engineering-2nd-edition-2https://shop.theiet.org:443/metaheuristic-optimization-in-power-engineering-2nd-edition<p xmlns="http://ns.editeur.org/onix/3.0/reference">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.</p> <p xmlns="http://ns.editeur.org/onix/3.0/reference">The new edition of <i>Metaheuristic Optimization in Power Engineering</i> in two volumes uses a MATLAB-based software package for testing and comparing methods, and includes several new and substantially revised and updated chapters.</p> <p xmlns="http://ns.editeur.org/onix/3.0/reference"><i>Volume 1</i> 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.</p> <p xmlns="http://ns.editeur.org/onix/3.0/reference"><i>Volume 2</i> focuses on power distribution networks, including power flow, voltage control and regulation, optimisation of generation placement and sizing, and state estimation analysis.</p> <p xmlns="http://ns.editeur.org/onix/3.0/reference">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.</p>Mon, 08 Jul 2024 12:12:42 GMThttps://shop.theiet.org:443/metaheuristic-optimization-in-power-engineering-2nd-editionhttps://shop.theiet.org:443/metal-optimiz-power-1e<p xmlns="http://ns.editeur.org/onix/3.0/reference">A metaheuristic is a consistent set of ideas, concepts, and operators to design a heuristic optimization algorithm, that can provide a sufficiently good solution to an optimization problem with incomplete or imperfect information. Modern and emerging power systems, with the growing complexity of distributed and intermittent generation, are an important application for such methods.</p><p xmlns="http://ns.editeur.org/onix/3.0/reference">This book describes the principles of solving various problems in power engineering via the application of selected metaheuristic optimization methods including genetic algorithms, particle swarm optimization, and the gravitational search algorithm. Applications covered include power flow calculation; optimal power flow in transmission networks; optimal reactive power dispatch in transmission networks; combined economic and emission dispatch; optimal power flow in distribution networks; optimal volt/var control in distribution networks; optimal placement and sizing of distributed generation in distribution networks; optimal energy and operation management of microgrids; optimal coordination of directional overcurrent relays; and steady-state analysis of self-excited induction generators.</p>Mon, 11 Jun 2018 23:37:15 GMThttps://shop.theiet.org:443/metal-optimiz-power-1e