Online Decision Support for Offshore Wind Farm Installations
暫譯: 離岸風電場安裝的線上決策支援
Rippel, Daniel
- 出版商: Springer Vieweg
- 出版日期: 2026-01-03
- 售價: $4,530
- 貴賓價: 9.5 折 $4,304
- 語言: 英文
- 頁數: 211
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3658499117
- ISBN-13: 9783658499112
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相關分類:
Machine Learning
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相關主題
商品描述
Offshore wind farms are major contributors to sustainable energy generation. However, their installation is highly weather-dependent, making the planning of costly resources, like jack-up vessels or port spaces, challenging. While existing models support strategic and tactical planning, there is a lack of effective decision support at the operational level.
To close this gap, this book presents an innovative online scheduling methodology based on a Model Predictive Control scheme. This approach combines Mixed-Integer scheduling models with control theory and a novel probabilistic method for integrating forecast uncertainty into operational planning. The resulting decision support system doesn't only enable reactive and weather-informed operational planning but also supports tactical and strategic decisions based on historical data. Simulation studies demonstrate significant potential: a reduction in variable costs of up to 9% and clear advantages over existing robust or control-based approaches in terms of planning reliability, cost efficiency, and responsiveness.
商品描述(中文翻譯)
離岸風電場是可持續能源發電的重要貢獻者。然而,它們的安裝高度依賴天氣,這使得規劃昂貴資源(如升起式船舶或港口空間)變得具有挑戰性。雖然現有模型支持戰略和戰術規劃,但在操作層面上缺乏有效的決策支持。
為了填補這一空白,本書提出了一種基於模型預測控制(Model Predictive Control)方案的創新在線排程方法。這種方法將混合整數排程模型與控制理論相結合,並採用一種新穎的概率方法將預測不確定性整合到操作規劃中。所產生的決策支持系統不僅能夠實現反應性和基於天氣的操作規劃,還支持基於歷史數據的戰術和戰略決策。模擬研究顯示出顯著的潛力:可變成本降低高達9%,並在規劃可靠性、成本效率和反應能力方面明顯優於現有的穩健或基於控制的方法。
作者簡介
Daniel Rippel is a research associate at BIBA - Bremer Institut für Produktion und Logistik GmbH at the University of Bremen. He holds a Diploma degree in Computer Sciences from the University of Bremen, Germany. His research interests include modeling and simulation of logistic systems, the development of domain-specific modeling methods, as well as the application of prediction techniques from statistics and machine learning.
作者簡介(中文翻譯)
丹尼爾·里佩爾是不來梅大學BIBA - 不來梅生產與物流研究所的研究助理。他擁有德國不來梅大學的計算機科學學位。其研究興趣包括物流系統的建模與模擬、特定領域建模方法的開發,以及統計學和機器學習中的預測技術的應用。