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.
Les mer
1. Introduction to Optimization techniques for sizing and management of integrated power systems
2. Genetic Algorithms and Other Heuristic Techniques in power systems optimization
3. Estimation of Natural Resources for Renewable Energy Systems
4. Renewable Generation and Energy Storage Systems
5. Forecasting of Electricity Prices, Demand, and Renewable Resources
6. Optimization of Renewable Energy Systems by Genetic Algorithms
7. Creating Energy Systems Policy using genetic optimization techniques
Les mer
Demonstrates pathways to implement efficient genetic optimization algorithms for solving tasks within a hybrid power system with distributed and renewable generators
Presents a range of essential techniques for using genetic algorithms in power system analysis, including
economic dispatch, forecasting, and optimal power fl ow, among other topics.
Addresses relevant optimization problems, such as neural network training and clustering analysis, using
genetic algorithms.
Discusses clearly and straightforwardly the implementation of genetic algorithms and its combination with
other heuristic techniques.
Describes the iHOGA® and MHOGA® commercial tools, which utilize genetic algorithms for designing
and managing energy systems based on renewable energies.
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Produktdetaljer
ISBN
9780128238899
Publisert
2022-09-29
Utgiver
Vendor
Elsevier Science Publishing Co Inc
Vekt
450 gr
Høyde
229 mm
Bredde
152 mm
Aldersnivå
P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
350
Forfatter