Resource-based view on the implementation of 6000 MW offshore wind power in the Netherlands

Resource-based view on the implementation of 6000MW oshore

wind power in the Netherlands

E.H.M. Mast

_{, G.A.M. van Kuik, M.B. Zaaijer}

Wind Energy Research Group, DUWIND, Technical University of Delft, the Netherlands

Abstract:

Political objectives and targets are often dened as a desirable and theoretically possible state, lacking a realistic view on the required resources to achieve this state. The availability of resources, and the time to change this availability, may however impede the im-plementation speed. In this paper, the preparations are described for such a resource-based view on the implementation of oshore wind power in the Nether-lands, in the Dutch part of the North Sea, to help investigate which issues will have to be addressed in the short and long term. The objective is to have a clearer view on the challenges in the availability of required resources for oshore wind farms.

1 Introduction

In the Netherlands, the governmental objective for o-shore wind power has been stated in the Energy Re-port of 2002 as an installed capacity of 6000 MW by 2020 [1]. This number was derived considering CO2

reduction targets and location studies in the North Sea showing the Dutch potential for oshore wind, but it therefore only states what is desirable as instal-lation of oshore power in the North Sea, not what is realisable. A social cost-benefit analysis has stated that a delayed implementation of 6000 MW by 2030 should be followed, in order to take advantage of cost reductions from the learning curves [2]. A recent gov-ernmental document on energy again supported large-scale oshore wind but also stresses these required cost reductions and mentioned a desired extra instal-lation of 450 MW by 2011 and 500 MW per year thereafter [3], making almost 6000 MW by 2020.

So the governmental target for oshore wind in the

_{Corresponding author: e.h.m.mast@tudelft.nl}

Netherlands by 2020 are considerable. However, in the Dutch part of the North Sea, expected installed capacity in 2008 is 228 MW, and subsequent parks are not expected before 2010. This means that to attain 6000 MW by 2020, more than 5500 MW will have to be built within ten years and, in practice, the time horizon of 2020 or even 2030 might prove unattainable if one takes into account the availability of resources required for achieving this target. Such required re-sources are for example vessels, turbines, harbours, labour, and nance. For a realistic view on the imple-mentation of a political target, the required resources have to be taken into account. This resource-based view on the implementation can indicate where the availability of a certain required resource proves a lim-iting factor, to know which challenges await in the short to long term in attaining large-scale implemen-tation. Therefore we want to look at the requirements for the implementation of 6000 MW using a resource-based view. The time to change of the availability of required resources is important, since an increase in resources such as vessels, grid or even human re-sources can take several years.

In this paper, the preparations are described for this resource based view. First the background is scribed shortly. Second, the model approach is de-scribed and the identication of roles and the gen-eral oshore wind farm time schedule for the model is explained. Third, preliminary simulations are made in which one can see the limiting factors of deploy-ment towards 6000 MW. Last, we will discuss how this model will be extended in the future.

2 Background

could speed up or slow down the implementation, or in other words which challenges (such as the possi-ble bottlenecks mentioned above) and opportunities could arise. Here, not only the technological perspec-tive is taken, but the co-evolution of technology and institutions is examined in line with work on transi-tion theory and socio-technical systems, described in for instance [4] and [5]. As a part of the quantita-tive part of the methodology, a model is developed and used to simulate the deployment of oshore wind power in time taking into account the availability of resources and time to increase these, as well as the ef-fects of the decision making and strategies of, and co-operation between, involved parties. This latter part of the model will not be discussed in this paper.

3 Methodology

Agent Based Modelling is used to model the develop-ment of oshore wind farms in the Dutch part of the North Sea. An agent is 'an encapsulated computer system situated in some environment that is capable of exible, autonomous action in that environment in order to meet its design objectives' [6]. An Agent Based Model (ABM) is a model consisting of several agents, as a computer representation of a complex system comprised of multiple, interacting actors (i.e. agents) [7]. By running an ABM, a complex system can therefore be simulated.

The agents are to represent the relevant actors in the field of oshore wind. The relevant actors are all actors that have an interest in oshore wind (in a pos-itive or negative manner) and have resources and/or instruments that can be used to (signicantly) slow down or speed up the implementation. The model is set up using a design dierentiating roles: all actions that have an eect on a farm during its life cycle. The agents represent the dierent roles of actors in the im-plementation of oshore wind, rather than their com-panies and organisations. Such a role can for example be a role in the supply chain such as turbine installa-tion and foundainstalla-tion manufacturing, but also outside it as for instance governmental permitting and social support. Although in reality an actor can have several roles (for instance a party that can install both tur-bines and foundations) here this approach is chosen for simplicity in separating the dierent work fields. An agent can have a high cooperation desire with a certain other agent, which could represent dierent

divisions of one company incorporating several roles. The agents have resources that they choose to de-ploy. With resources of the agents is meant the land, labour and capital goods of the agent, in economic terms the factors of production. Capital goods are -nancial resources and physical resources; by the latter we mean the hardware of the implementation: vessels, cranes etc. The implementation speed is dependent on the availability of these resources. At any time the actual capacity of the resources has to match demand to not impede the implementation speed.

Agents will however choose how to deploy their re-sources based on their strategies and their environ-ment. Risk attitudes will in uence their willingness to operate in this field and their willingness to increase resource capacity. The environment will in uence the willingness of agents to sell or buy services or goods from other agents, as for instance steel price will have an eect on turbine price.

The model therefore consists of three layers: the resource capacity, the behaviour and strategies of the agents in deployment of their resources, and the sur-rounding environment. In this paper, we shall focus on incorporation of the first part in the simulation. An identication is made of the required resources, up to a chosen level of detail. For this, the following steps are executed: identication of the relevant roles (see 3.1)and the time schedule of a farm (see 3.2). For the identication of the roles, the involved actors and their instruments/resources are examined. The time schedule of a farm will help dene a project time line of a farm, and the simulation of oshore deployment is made on a project basis1_.

3.1 Identification of relevant roles

In the life cycle of an oshore wind park, dierent phases can be identied, with dierent actors in-volved. Using available literature and interviews with stakeholders, six separate phases are identied to-gether with the main roles involved, see table 1.

In [8], David Bean describes eight dierent phases and the relevant actors in each phase. Here, these have been reduced to ve separate phases by incorpo-rating the nancial close as nal stage in the procure-ment phase and the grid connection as a part of the construction phase. A POWER study [9] describes

1_{The project basis of the simulations is only performed for}

Table 1: Roles represented by agents in model. Phase Main roles

Initiative & Consent Project developer, government consultants, main suppliers, society Procurement Project developer, main contractor

subcontractors for installation, transport and manufacturing of 3 main parts Construction Wind turbine manufacturer

subcontractors, harbour manager Operation & Maintenance Operator

O&M crews, harbour manager

Repowering Project developer, main contractor, government subcontractors

Decommissioning main contractor

the experiences of developers in several case-studies in two named phases of a project, the project planning phase and the installation & operation phase. In the CA-OWEE project [10] a study has been made into the installation phase and the dierent companies in the supply chain.

The phases are explained in further detail in the next section. For the identication of the main roles, we look at the roles directly involved in the supply chain and disregard the first and higher order sub-suppliers. The main contractor in table 1 refers to the contractor with a turnkey contract with the de-veloper, multi-contracting to the subcontractors. The subcontractors identied are the roles involved in the manufacturing, transport and installation of the three main parts: the cables, the turbine with tower, and the foundation. For the model, we will focus on these large parts of an oshore farm and the roles we con-sider most relevant to the realisation of the farm.

3.2 General project timeline

The ve phases identied in the previous section will be described here. For the construction phase and the identication of the supply chain especially use is made of the CA-OWEE study [10], Noordzeeloket [11], interviews and the POWER project, which examined the supply chain in North-Western Europe. Initiative: A project developer searches a location and places an initiative 2 _{Contact is made} 2_{Although the site selection is at present open to the}

devel-oper, in the simulation we take into account the possible future development that one or a number of areas could be designated

with consultants for an initial design of the park. An initial investment decision is made whether or not to continue to place a permit request, which includes an Environmental Impact Assessment (EIA). After placing a permit request, the regulators review it and the participation procedure or consultation process is started. Estimated time for the technical studies and the EIA is 12 to 30 months [8] and the consent procedure is said to take 6 months [11]. Total time for the initiative phase is 18 to 36 months.

Procurement phase: When a permit is given, the procurement phase starts. The project developer starts a tender procedure for the main contractor for the park3_{. A main contractor can respond to}

the call for tender, in which case he will contact subcontractors. A tender oer will include a time frame, technical details (eg. chosen turbine) and the total costs. Based on the oered tenders, the developer makes the investment decision to go to the construction of the park. The main contractor can choose to closely involve a wind turbine manufacturer in the tender. The procurement phase ends with the nancial close.

Total time for the procurement phase is 8 months or longer [8].

by the government.

3_{Note that if the developer chooses a multi-contracting}

Construction phase: The lead lies now with the main contractor, who will construct the park within the time frame and costs stated by his tender. The park is divided in three parts: the foundation, the turbine (including nacelle, blades and tower), and the cables for the internal eld and connection to high voltage station onshore. An oshore transformer station could be built in cooperation with other agents or by order of the government.

The run time of the construction phase is con-nected to the availability of resources and process time (e.g. manufacturing, transport, commissioning). For the run-through time-estimations, use is made of [8], information found on [11], [12] and interviews with stakeholders. Total time for the construction phase is 2 to 3 years, due to the limited weather window at the North Sea.

Operation phase: Current practice is to sign a maintenance contract turbine manufacturer for the first five years, and this choice is included in the oered tender. The total time for the operation phase is 20 years.

Repowering phase: After 20 years of operation, the towers and turbines can be replaced and the foundations and cables reused, extending the park life time for another 20 years.

Decommissioning phase: For the permit procedures, the project developer has to submit a decommissioning plan, explaining how to remove all of the installation up to the seabed. No oshore park has been decommissioned yet, but in general it is as-sumed to be similar to oshore oil and gas procedures.

4 Results

By adapting the resource capacity available to each role, the implementation speed of oshore wind farms is in uenced, as one expects. As an example of a simulation, two simple cases are run. The cases are simple cases, because we only look at one output (the implementation speed of installed capacity) and they have the following simple assumptions. Of all types of agents (developer, wind turbine manufacturers, etc.) only two are incorporated in the model; in later

sim-ulations, this will vary. None have strategies in how to deploy their resources, if they have the capacity, they will deploy their resources, adopting a 'first come first served' approach. The locations used now are 12 identical locations; however, these will be based on over 30 areas already identied by the developers in their initiatives (see [11]), excluding overlapping ar-eas. And nally, no learning curves or forecasts are incorporated in the model at this time; for instance the general turbine size is set to 3 MW in these simu-lations of the coming 15 years. These learning curves and forecasts will be implemented in the model later. In the rst case, all resources have large availabil-ity; all capacities are put to a high level. Developers choose their sites and a 'rst come, rst served' per-mit procedure is followed. The time for an EIA is random between 1 and 2.5 years, while waiting for a permit consent always takes 6 months. Two harbours are incorporated, also with large capacity. The result-ing implementation speed is given in gure 14_.

In the gure, the time steps are a quarter, so 4 time steps is a year. The delay in the beginning of the simulation is due to waiting for the EIA, the per-mit approval and the construction. As one can see, the rst park takes about 4 years to nish, seen as a jump in installed capacity at quarter-time step 16.

In the second case the harbour availability is lim-ited; the harbour capacity of the two included harbour manager agents is reduced. Less farms can therefore be built in the same year(s) because of the lack in har-bour space necessary for onshore storage and assem-bly5_{. The construction of wind farms therefore slows}

down, leading to the implementation speed shown in 2.

5 Discussion & Future research

For the correct representation of available resources, more data is needed on the current capacities and the growth possibilities and time to change. Gathering this data is expected to be time costly.

As mentioned above, the model will be extended with a second and third layer of the model. The agents will have their own objectives and interests and will behave accordingly; strategies for the deployment

4_{Since the EIA procedure time is random between 4 and 10}

time steps, the graph does jump up at a regular rate.

5_{It is presumed that each farm requires 1000 km}2_{of harbour}

Figure 1: Implementation speed for 10 locations

using large capacities Figure 2: Implementation speed for 10 locationsusing a smaller harbour capacity.

of their resources will be incorporated. Environmen-tal scenarios will be used to dene the environmenEnvironmen-tal conditions and input in a consistent way. This qual-itative work and quantqual-itative work will be combined to form transition paths to large-scale oshore wind deployment in the Netherlands.

6 Acknowledgements

This work is part of the project PhD@Sea, which is substantially funded under the BSIK-programme of the Dutch Government and supported by the consor-tium We@Sea, http://www.we-at-sea.org.

References

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[11] Noordzeeloket website. http://www.noordzeeloket.nl. last visit Novem-ber 2007.

[12] Horns Rev website. http: