Details
| Original language | English |
|---|---|
| Title of host publication | 2021 Winter Simulation Conference, WSC 2021 |
| Editors | S. Kim |
| Place of Publication | [Piscataway, NJ] |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Number of pages | 12 |
| ISBN (electronic) | 9781665433112 |
| ISBN (print) | 978-1-6654-3312-9 |
| Publication status | Published - 2021 |
| Event | 2021 Winter Simulation Conference, WSC 2021 - Phoenix, United States Duration: 12 Dec 2021 → 15 Dec 2021 |
Abstract
Offshore wind energy constitutes a promising technology to achieve the world's need for sustainable energy. However, offshore wind farm installations require sophisticated planning methods due to increasing resource demands and the processes' high dependence on viable weather conditions. Current literature provides several models that either provide strategic or tactical decision support using historical data or operative support using current measurements and forecasts. Unfortunately, models of the first type cannot support the operative level. In contrast, the second type provides decision support using local, short-term optimizations that do not consider these decisions' effect on the overall installation project. This article proposes a cascading online-simulation concept that optimizes local decisions using current data. However, it estimates the effects of each decision using nested simulation and aggregates of historical data. The results show that this approach achieves a good trade-off between the project's duration and cost-inducing delays at comparably low computational costs.
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Mathematics(all)
- Modelling and Simulation
- Computer Science(all)
- Computer Science Applications
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2021 Winter Simulation Conference, WSC 2021. ed. / S. Kim. [Piscataway, NJ]: Institute of Electrical and Electronics Engineers Inc., 2021.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A Cascading Online-Simulation Framework to Optimize Installation Cycles for Offshore Wind Farms
AU - Rippel, Daniel
AU - Lütjen, Michael
AU - Szczerbicka, Helena
AU - Freitag, Michael
N1 - Funding Information: The authors gratefully acknowledge the financial support by the DFG (German Research Foundation) for the Project ”OffshorePlan”, grant number (LU 2049/1-1 — SZ 51/33-1).
PY - 2021
Y1 - 2021
N2 - Offshore wind energy constitutes a promising technology to achieve the world's need for sustainable energy. However, offshore wind farm installations require sophisticated planning methods due to increasing resource demands and the processes' high dependence on viable weather conditions. Current literature provides several models that either provide strategic or tactical decision support using historical data or operative support using current measurements and forecasts. Unfortunately, models of the first type cannot support the operative level. In contrast, the second type provides decision support using local, short-term optimizations that do not consider these decisions' effect on the overall installation project. This article proposes a cascading online-simulation concept that optimizes local decisions using current data. However, it estimates the effects of each decision using nested simulation and aggregates of historical data. The results show that this approach achieves a good trade-off between the project's duration and cost-inducing delays at comparably low computational costs.
AB - Offshore wind energy constitutes a promising technology to achieve the world's need for sustainable energy. However, offshore wind farm installations require sophisticated planning methods due to increasing resource demands and the processes' high dependence on viable weather conditions. Current literature provides several models that either provide strategic or tactical decision support using historical data or operative support using current measurements and forecasts. Unfortunately, models of the first type cannot support the operative level. In contrast, the second type provides decision support using local, short-term optimizations that do not consider these decisions' effect on the overall installation project. This article proposes a cascading online-simulation concept that optimizes local decisions using current data. However, it estimates the effects of each decision using nested simulation and aggregates of historical data. The results show that this approach achieves a good trade-off between the project's duration and cost-inducing delays at comparably low computational costs.
UR - http://www.scopus.com/inward/record.url?scp=85126141251&partnerID=8YFLogxK
U2 - 10.1109/WSC52266.2021.9715285
DO - 10.1109/WSC52266.2021.9715285
M3 - Conference contribution
AN - SCOPUS:85126141251
SN - 978-1-6654-3312-9
BT - 2021 Winter Simulation Conference, WSC 2021
A2 - Kim, S.
PB - Institute of Electrical and Electronics Engineers Inc.
CY - [Piscataway, NJ]
T2 - 2021 Winter Simulation Conference, WSC 2021
Y2 - 12 December 2021 through 15 December 2021
ER -