IFAC PapersOnLine 52-13 (2019) 1337–1342
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Peer review under responsibility of International Federation of Automatic Control.
10.1016/j.ifacol.2019.11.384
1. INTRODUCTION
Wind energy provides one of the most promising tech-
nologies to produce renewable and sustainable energy.
Currently, a large amount of renewable energy is generated
using on- and offshore wind farms, as the technology has
achieved a high level of maturity (Dolores et al., 2010).
In 2017, new wind farms producing approximately 52 Gi-
gawatts were constructed worldwide, increasing the total
amount of energy produced by wind turbines by approxi-
mately 11% to a total of 539 Gigawatts (REN21, 2018).
In particular, offshore wind farms (OWF) are capable
to generate large amounts of energy, due to high wind
speeds and -availability at sea (Breton and Moe, 2009),
(Sun et al., 2012). Over the last decade, an exponential
increase in energy generated by OWFs can be observed,
resulting in an increase of 4.4 Gigawatts to a total of 18.8
Gigawatts of wind energy worldwide generated in 2017
(REN21, 2018). Despite the advantages of offshore wind
farms, the construction and operation of these farms poses
particular challenges compared to onshore wind farms, due
to their increased dimensions and weight. Higher costs for
founding structures, network connection and for resources,
like vessels and storage spaces, require a detailed planning,
to ensure an efficient construction of OWFs (Junginger
et al., 2004). In contrast, dynamic weather conditions at
sea interfere with long-term plans, which sometimes cover
horizons of several years. Consequently mechanisms for
short-term control and dynamic adjustments are required,
which can react in matters of days and even hours, e.g. if
weather forecasts change. In general, about 15% to 20% of
the costs for OWFs can be attributed to logistics during
the construction process, demonstrating high potentials
for optimization (Lange et al., 2012), (Dewan et al., 2015),
(Muhabie et al., 2018). Over the next years, more high-
powered wind turbines with capacities over 10 Megawatts
will be built, e.g. see (European Council, 2018). These
turbines are usually constructed in deeper water with
a depth starting at 30m. Such locations are commonly
located at distances further than 50km off the shoreline
(Muhabie et al., 2018), complicating the pexecution of
operations.
This article aims to identify requirements towards a de-
cision support tool for the installation process of OWFs.
It presents a review of existing literature to summarize
the problem (section 2) and shows current approaches in
this field (section 3). Section 4 provides a decomposition
of the planning problem into smaller tasks and closes with
a discussion of suitable methods for these tasks.
2. CONSTRUCTION OF OFFSHORE WIND FARMS
This section describes the overall process for the construc-
tion of OWFs and presents a review of existing literature
focusing on the installation process.
2.1 Installation Process
According to Quandt et al. (2017), there is no standardized
process for the installation of OWFs. Each project differs
Keywords: Hierarchical decision making, Simulation, Optimization, Wind energy, Installation
of offshore wind farms
Abstract: Offshore wind farms provide a promising technology to produce renewable and
sustainable energy. Nevertheless, the installation and operation of offshore wind farms pose a
particular challenge to the planning and execution of operations. This article aims to identify
requirements towards a decision support tool for the installation planning. Therefore, it provides
a review of existing research in planning approaches and summarizes the overall planning
problem. Afterwards this problem is decomposed into single tasks, according to their planning
horizons. This decomposition shows a high level of interconnection between tasks across all levels.
Higher levels provide constraints for the tasks on lower levels, while the results of these tasks
are incorporated at higher levels. Finally, the article discusses the advantages and disadvantages
of different approaches to solve these tasks. Copyright ǚ 2019 IFAC
*
BIBA - Bremer Institut f¨ ur Produktion und Logistik GmbH at the
University of Bremen, Bremen, Germany (e-mail: [rip, jat,
ltj]@biba.uni-bremen.de).
**
Leibnitz University Hannover, Hannover, Germany (e-mail: [xmb,
hsz]@sim.uni-hannover.de)
***
University of Bremen, Bremen, Germany, (e-mail:
fre@biba.uni-bremen.de)
Daniel Rippel
*
Nicolas Jathe
*
Matthias Becker
**
Michael L¨ utjen
*
Helena Szczerbicka
**
Michael Freitag
*,***
A Review on the Planning Problem for the
Installation of Offshore Wind Farms
© 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.