9783030828509 - energy forecasting and control methods for energy storage systems in distribution networks: predictive modelling and control techniques: 85 (lecture notes in energy) de holderbaum, william; alasali, feras; sinha, ayush (17 resultados)

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Taschenbuch. Condición: Neu. Energy Forecasting and Control Methods for Energy Storage Systems in Distribution Networks | Predictive Modelling and Control Techniques | William Holderbaum (u. a.) | Taschenbuch | xvi | Englisch | 2024 | Springer Nature Switzerland | EAN 9783030828509 | Verantwortliche Person für die EU: Springer V…erlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book describes the stochastic and predictive control modelling of electrical systems that can meet the challenge of forecasting energy requirements under volatile conditions.The global electrical grid is expected to face significant en…ergy and environmental challenges such as greenhouse emissions and rising energy consumption due to the electrification of heating and transport. Today, the distribution network includes energy sources with volatile demand behaviour, and intermittent renewable generation. This has made it increasingly important to understand low voltage demand behaviour and requirements for optimal energy management systems to increase energy savings, reduce peak loads, and reduce gas emissions.Electrical load forecasting is a key tool for understanding and anticipating the highly stochastic behaviour of electricity demand, and for developing optimal energy management systems. Load forecasts, especially of the probabilistic variety, can support moreinformed planning and management decisions, which will be essential for future low carbon distribution networks. For storage devices, forecasts can optimise the appropriate state of control for the battery. There are limited books on load forecasts for low voltage distribution networks and even fewer demonstrations of how such forecasts can be integrated into the control of storage.This book presents material in load forecasting, control algorithms, and energy saving and provides practical guidance for practitioners using two real life examples: residential networks and cranes at a port terminal.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes the stochastic and predictive control modelling of electrical systems that can meet the challenge of forecasting energy requirements under volatile conditions.The global electrical grid is expected to face significant energy and… environmental challenges such as greenhouse emissions and rising energy consumption due to the electrification of heating and transport. Today, the distribution network includes energy sources with volatile demand behaviour, and intermittent renewable generation. This has made it increasingly important to understand low voltage demand behaviour and requirements for optimal energy management systems to increase energy savings, reduce peak loads, and reduce gas emissions.Electrical load forecasting is a key tool for understanding and anticipating the highly stochastic behaviour of electricity demand, and for developing optimal energy management systems. Load forecasts, especially of the probabilistic variety, can support moreinformed planning and management decisions, which will be essential for future low carbon distribution networks. For storage devices, forecasts can optimise the appropriate state of control for the battery. There are limited books on load forecasts for low voltage distribution networks and even fewer demonstrations of how such forecasts can be integrated into the control of storage.This book presents material in load forecasting, control algorithms, and energy saving and provides practical guidance for practitioners using two real life examples: residential networks and cranes at a port terminal.

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Paperback. Condición: Brand New. 220 pages. 9.26x6.11x0.50 inches. In Stock.

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Softcover. Condición: gut. 2024. Energy Forecasting and Control Methods for Energy Storage Systems in Distribution Networks In deutscher Sprache. pages.

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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces electrical load forecasting and its useDescribes stochastic and predictive control modellingProvides a basis for further research and spursProfessor William Holderbaum has been work…ing at the University of Gla.

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes the stochastic and predictive control modelling of electrical systems that can meet the challenge of forecasting energy requirements under volatile conditions.The global electrical grid is expected to face signif…icant energy and environmental challenges such as greenhouse emissions and rising energy consumption due to the electrification of heating and transport. Today, the distribution network includes energy sources with volatile demand behaviour, and intermittent renewable generation. This has made it increasingly important to understand low voltage demand behaviour and requirements for optimal energy management systems to increase energy savings, reduce peak loads, and reduce gas emissions.Electrical load forecasting is a key tool for understanding and anticipating the highly stochastic behaviour of electricity demand, and for developing optimal energy management systems. Load forecasts, especially of the probabilistic variety, can support moreinformed planning and management decisions, which will be essential for future low carbon distribution networks. For storage devices, forecasts can optimise the appropriate state of control for the battery. There are limited books on load forecasts for low voltage distribution networks and even fewer demonstrations of how such forecasts can be integrated into the control of storage.This book presents material in load forecasting, control algorithms, and energy saving and provides practical guidance for practitioners using two real life examples: residential networks and cranes at a port terminal. 220 pp. Englisch.

Idioma: Inglés
Editorial: Springer International Publishing, Springer Nature Switzerland Jan 2024, 2024
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book describes the stochastic and predictive control modelling of electrical systems that can meet the challenge of forecasting energy requirements under volatile conditions.The global electrical grid is expected to face significan…t energy and environmental challenges such as greenhouse emissions and rising energy consumption due to the electrification of heating and transport. Today, the distribution network includes energy sources with volatile demand behaviour, and intermittent renewable generation. This has made it increasingly important to understand low voltage demand behaviour and requirements for optimal energy management systems to increase energy savings, reduce peak loads, and reduce gas emissions.Electrical load forecasting is a key tool for understanding and anticipating the highly stochastic behaviour of electricity demand, and for developing optimal energy management systems. Load forecasts, especially of the probabilistic variety, can support moreinformed planning and management decisions, which will be essential for future low carbon distribution networks. For storage devices, forecasts can optimise the appropriate state of control for the battery. There are limited books on load forecasts for low voltage distribution networks and even fewer demonstrations of how such forecasts can be integrated into the control of storage.This book presents material in load forecasting, control algorithms, and energy saving and provides practical guidance for practitioners using two real life examples: residential networks and cranes at a port terminal.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 220 pp. Englisch.

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