Astolfi Davide (28 results)

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  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

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  • Language: English

    Published by Mdpi AG 5/27/2020, 2020

    3039289330 / 9783039289332

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    Hardback or Cased Book. Condition: New. Wind Turbine Power Optimization Technology. Book.

  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

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  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

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  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover

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    Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover

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  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover

    Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK

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  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

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    Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections

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    Condition: New. In English.

  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

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    Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover

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    Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

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  • Language: English

    Published by The Institution of Engineering and Technology, 2026

    1837246947 / 9781837246946

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    Seller: California Books, Miami, FL, U.S.A.California Books

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  • Language: English

    Published by MDPI AG, 2020

    3039289330 / 9783039289332

    • Hardcover

    Seller: Buchpark, Trebbin, GermanyBuchpark

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    Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

  • Language: English

    Published by Institution of Engineering and Technology, 2026

    1837246947 / 9781837246946

    • Hardcover

    Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK

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    HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

  • Language: English

    Published by Institution of Engineering and Technology, 2026

    1837246947 / 9781837246946

    • Hardcover

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    HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

  • Language: English

    Published by Institution of Engineering and Technology, 2026

    1837246947 / 9781837246946

    • Hardcover

    Seller: Revaluation Books, Exeter, United KingdomRevaluation Books

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    Hardcover. Condition: Brand New. 250 pages. 6.14x2.00x9.21 inches. In Stock.

  • Language: English

    Published by Institution Of Engineering & Technology Sep 2026, 2026

    1837246947 / 9781837246946

    • Hardcover

    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Buch. Condition: Neu. Neuware - Wind power is unanimously recognized as one of the major drivers of the energy transition. Increasing renewable power generation introduces significant challenges for both the operation and planning of power systems, driven by the intrinsic uncertainty of stochastic renewable resources and by the growing spatial distribution of generation assets. Wind power presents a distinctive set of challenges in this context. Wind turbines are complex machines operating under highly non-stationary conditions and are composed of tightly coupled mechanical, electrical, and electronic subsystems. In order to ensure reliable power system operation and to minimize the levelized cost of energy, it is essential to continuously monitor the health status of wind turbines, and to improve the efficiency of wind energy conversion as much as possible. Artificial intelligence has the potential to help address these challenges. The objective of this book is to address the gap between domain expertise in wind energy and the rapid proliferation of machine learning techniques. While advanced data-driven models offer unprecedented flexibility and predictive capabilities, their increasing complexity can come at the cost of transparency, physical interpretability, and engineering insight. Bridging this gap demands a critical understanding of the problem at hand, a clear definition of the operational objective, and a conscious selection of the most appropriate techniques compatible with the available data sources. Offering concise but thorough coverage of the topic, AI for Wind Turbine Performance and Condition Monitoring explores data sources from turbines and fleets, reviews the fundamentals of ML, then covers AI-based wind turbine performance analysis, AI-based detection of static misalignment and sensor errors, and condition monitoring for wind turbine maintenance. Wind power researchers in academia and industry, grid operators, and maintenance managers will find this book offers a valuable overview and analysis of AI-based methodologies for wind generators.…

  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover
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    HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover
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    HRD. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover
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    Seller: Majestic Books, Hounslow, United KingdomMajestic Books

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  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover
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  • Language: English

    Published by Mdpi AG, 2020

    3039289330 / 9783039289332

    • Hardcover
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    Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios

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  • Language: English

    Published by MDPI AG, 2020

    3039289330 / 9783039289332

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    Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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    Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Wind turbines are one of the most promising renewable energy technologies, and this motivates fertile research activity about developments in power optimization. This topic covers a wide range of aspects, from the research on aerodynamics and control design to the industrial applications about on-site wind turbine performance control and monitoring. This Special Issue collects seven research papers about several innovative aspects of the multi-faceted topic of wind turbine power optimization technology. The seven research papers deal respectively with the aerodynamic optimization of wind turbine blades through Gurney flaps; optimization of blade design for large offshore wind turbines; control design optimization of large wind turbines through the analysis of the competing objectives of energy yield maximization and fatigue loads minimization; design optimization of a tension leg platform for floating wind turbines; innovative methods for the assessment of wind turbine optimization technologies operating on site; optimization of multiple wake interactions modeling through the introduction of a mixing coefficient in the energy balance method; and optimization of the dynamic stall control of vertical-axis wind turbines through plasma actuators. This Special Issue presents remarkable research activities in the timely subject of wind turbine power optimization technology, covering various aspects. The collection is believed to be beneficial to readers and contribute to the wind power industry.…

  • Language: English

    Published by MDPI AG, 2020

    3039289330 / 9783039289332

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    Seller: moluna, Greven, Germanymoluna

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    Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnWind turbines are one of the most promising renewable energy technologies, and this motivates fertile research activity about developments in power optimization. This topic covers a wide range of aspects, from the research on aero. …

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    Language: English

    Published by MDPI AG, 2020

    3039289330 / 9783039289332

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    Seller: preigu, Osnabrück, Germanypreigu

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    Buch. Condition: Neu. Wind Turbine Power Optimization Technology | Buch | Gebunden | Englisch | 2020 | MDPI AG | EAN 9783039289332 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

  • Language: English

    Published by Institution of Engineering and Technology, Stevenage, 2026

    1837246947 / 9781837246946

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    Hardcover. Condition: new. Hardcover. Wind power is unanimously recognized as one of the major drivers of the energy transition. Increasing renewable power generation introduces significant challenges for both the operation and planning of power systems, driven by the intrinsic uncertainty of stochastic renewable resources and by the growing spatial distribution of generation assets. Wind power presents a distinctive set of challenges in this context.Wind turbines are complex machines operating under highly non-stationary conditions and are composed of tightly coupled mechanical, electrical, and electronic subsystems. In order to ensure reliable power system operation and to minimize the levelized cost of energy, it is essential to continuously monitor the health status of wind turbines, and to improve the efficiency of wind energy conversion as much as possible. Artificial intelligence has the potential to help address these challenges.The objective of this book is to address the gap between domain expertise in wind energy and the rapid proliferation of machine learning techniques. While advanced data-driven models offer unprecedented flexibility and predictive capabilities, their increasing complexity can come at the cost of transparency, physical interpretability, and engineering insight. Bridging this gap demands a critical understanding of the problem at hand, a clear definition of the operational objective, and a conscious selection of the most appropriate techniques compatible with the available data sources.Offering concise but thorough coverage of the topic, AI for Wind Turbine Performance and Condition Monitoring explores data sources from turbines and fleets, reviews the fundamentals of ML, then covers AI-based wind turbine performance analysis, AI-based detection of static misalignment and sensor errors, and condition monitoring for wind turbine maintenance.Wind power researchers in academia and industry, grid operators, and maintenance managers will find this book offers a valuable overview and analysis of AI-based methodologies for wind generators. A concise reference on using AI for monitoring and performance improvements for wind power turbines, which covers data sources, AI-based performance analysis and alignment detection, sensor errors, and condition monitoring. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

  • Language: English

    Published by The Institution of Engineering and Technology, 2026

    1837246947 / 9781837246946

    • Hardcover
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    Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE

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    Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

  • Language: English

    Published by Institution of Engineering and Technology, Stevenage, 2026

    1837246947 / 9781837246946

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    Seller: CitiRetail, Stevenage, United KingdomCitiRetail

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    Hardcover. Condition: new. Hardcover. Wind power is unanimously recognized as one of the major drivers of the energy transition. Increasing renewable power generation introduces significant challenges for both the operation and planning of power systems, driven by the intrinsic uncertainty of stochastic renewable resources and by the growing spatial distribution of generation assets. Wind power presents a distinctive set of challenges in this context.Wind turbines are complex machines operating under highly non-stationary conditions and are composed of tightly coupled mechanical, electrical, and electronic subsystems. In order to ensure reliable power system operation and to minimize the levelized cost of energy, it is essential to continuously monitor the health status of wind turbines, and to improve the efficiency of wind energy conversion as much as possible. Artificial intelligence has the potential to help address these challenges.The objective of this book is to address the gap between domain expertise in wind energy and the rapid proliferation of machine learning techniques. While advanced data-driven models offer unprecedented flexibility and predictive capabilities, their increasing complexity can come at the cost of transparency, physical interpretability, and engineering insight. Bridging this gap demands a critical understanding of the problem at hand, a clear definition of the operational objective, and a conscious selection of the most appropriate techniques compatible with the available data sources.Offering concise but thorough coverage of the topic, AI for Wind Turbine Performance and Condition Monitoring explores data sources from turbines and fleets, reviews the fundamentals of ML, then covers AI-based wind turbine performance analysis, AI-based detection of static misalignment and sensor errors, and condition monitoring for wind turbine maintenance.Wind power researchers in academia and industry, grid operators, and maintenance managers will find this book offers a valuable overview and analysis of AI-based methodologies for wind generators. A concise reference on using AI for monitoring and performance improvements for wind power turbines, which covers data sources, AI-based performance analysis and alignment detection, sensor errors, and condition monitoring. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…