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Record Nr. |
UNINA9910366594503321 |
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Autore |
Dhiman Harsh S |
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Titolo |
Decision and Control in Hybrid Wind Farms / / by Harsh S. Dhiman, Dipankar Deb |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XXII, 140 p. 64 illus., 62 illus. in color.) |
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Collana |
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Studies in Systems, Decision and Control, , 2198-4182 ; ; 253 |
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Disciplina |
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Soggetti |
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Vibration |
Dynamics |
Energy consumption |
Energy systems |
Algorithms |
Energy harvesting |
Vibration, Dynamical Systems, Control |
Energy Efficiency |
Energy Systems |
Energy Harvesting |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Fundamentals of Wind Turbine and Wind Farm Control Systems -- Multi-Criteria Decision Making: An Overview -- Decision Making in Hybrid Wind Farms -- Fuzzy based Decision Making in Hybrid Wind Farms -- Control Applications in Hybrid Wind Farms -- BESS Life Enhancement for Hybrid Wind Farms. |
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Sommario/riassunto |
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This book focuses on two of the most important aspects of wind farm operation: decisions and control. The first part of the book deals with decision-making processes, and explains that hybrid wind farm operation is governed by a set of alternatives that the wind farm operator must choose from in order to achieve optimal delivery of wind power to the utility grid. This decision-making is accompanied by accurate forecasts of wind speed, which must be known beforehand. Errors in wind forecasting can be compensated for by pumping power |
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from a reserve capacity to the grid using a battery energy storage system (BESS). Alternatives based on penalty cost are assessed using certain criteria, and MCDM methods are used to evaluate the best choice. Further, considering the randomness in the dynamic phenomenon in wind farms, a fuzzy MCDM approach is applied during the decision-making process to evaluate the best alternative for hybrid wind farm operation. Case studies from wind farms in the USA are presented, together with numerical solutions to the problem. In turn, the second part deals with the control aspect, and especially with yaw angle control, which facilitates power maximization at wind farms. A novel transfer function-based methodology is presented that controls the wake center of the upstream turbine(s); lidar-based numerical simulation is carried out for wind farm layouts; and an adaptive control strategy is implemented to achieve the desired yaw angle for upstream turbines. The proposed methodology is tested for two wind farm layouts. Wake management is also implemented for hybrid wind farms where BESS life enhancement is studied. The effect of yaw angle on the operational cost of BESS is assessed, and case studies for wind farm datasets from the USA and Denmark are discussed. Overall, the book provides a comprehensive guide to decision and control aspects for hybrid wind farms, which are particularly important from an industrial standpoint. |
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