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Genetic Optimization Techniques for Sizing and Management of Modern Power Systems explores the design and management of energy systems using a genetic algorithm as the primary optimization technique. Coverage ranges across topics related to resource estimation and energy systems simulation. Chapters address the integration of distributed generation, the management of electric vehicle charging, and microgrid dimensioning for resilience enhancement with detailed discussion and solutions using parallel genetic algorithms. The work is suitable for researchers and practitioners working in power…mehr

Produktbeschreibung
Genetic Optimization Techniques for Sizing and Management of Modern Power Systems explores the design and management of energy systems using a genetic algorithm as the primary optimization technique. Coverage ranges across topics related to resource estimation and energy systems simulation. Chapters address the integration of distributed generation, the management of electric vehicle charging, and microgrid dimensioning for resilience enhancement with detailed discussion and solutions using parallel genetic algorithms. The work is suitable for researchers and practitioners working in power systems optimization requiring information for systems planning purposes, seeking knowledge on mathematical models available for simulation and assessment, and relevant applications in energy policy.
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Autorenporträt
Juan Lujano-Rojas received the B.S. from the Simón Bolívar University, Venezuela, and the M.S. and Ph.D. degrees from the University of Zaragoza, Spain, in 2007, 2010, and 2012, respectively. From 2013 to 2015, he worked on the FP7 project entitled: Smart and Sustainable Insular Electricity Grids under Large-Scale Renewable Integration (SINGULAR). Between 2015 and 2018, Lujano worked in the Institute for Systems and Computer Engineering, Research and Development in Lisbon (INESC-ID). In 2018 he rejoined the University of Zaragoza, where he is currently working as a Professor.