Dedicated offshore maintenance support tools for XEMC DarWinD wind turbines

Transcription

1 Dedicated offshore maintenance support tools for XEMC DarWinD wind turbines The research project was conducted in close collaboration between ECN and emerging offshore wind turbine manufacturer XEMC Darwind under the embrella. It summarizes main results of a 5 MW offshore wind turbine design effort. Technical risk assessments and an O&M modelling tool developed by ECN were both employed for the project. In addition, a support tool aimed at the operational phase of an offshore wind farm with a main focus at advanced maintenance planning and including recent accumulated field records (OMCE) is presented. XEMC DarWinD technology thereby serves as an exemplary case focused at developing best practice tools for the offshore wind industry. Civil engineering Offshore wind farms generally involve higher capital costs compared to their onshore equivalents, largely due to expensive support structures and for instance installing the power export cables buried into the seabed. Moreover, offshore wind turbine access can be difficult especially during winter, whereby accessibility primarily depends on weather conditions and access system employed. The number of unplanned visits due to turbine failure and planned maintenance visits should therefore ideally be reduced to an average of about one annual visit per installation. XEMC DarWinD aims at commercially introducung its new 5 MW wind turbine concept designed for optimised system reliability, maintainability and availability and indeed one annual service visit. This DD115 is an up scaled and optimised version of the former 2 MW Zephyros turbine, developed in the Netherlands early this century. Conceptually both sister products share several main design features: A Direct-Drive Permanent Magnet generator; Functional integration of generator and rotor bearing, a single rotor bearing concept, and the application of circular stiffeners; Partial passive generator cooling; Cooling, controls, transformer, and power converter placed in lower tower section; 3kV generator (XEMC DarWinD only) for efficient power transmission from nacelle to the lower tower; No additional shell needed for nacelle and hub, castings provide housing. XEMC DarWinD s design approach `Less-is-More` focuses at fewer components, but each with increased robustness aimed at reducing the number of failure incidents and to minimise overall O&M requirement. Even though the turbine concept featuring a permanent magnet type generator is potentially well suited regarding offshore operational reliability, maintainability and availability, marine application optimisation and subsystems redesign remain to be essential preconditions. That latter process is mainly driven by failure mode analysis, whereas in order to reach an envisaged single annual O&M visit target, dedicated offshore maintenance

2 support tools are required too. Within this context ECN develops a dedicated software instrument for optimising operational offshore wind farm maintenance aspects. As part of this software development a structured methodology has been formulated that focuses at allocating the most favourable maintenance strategy for further optimising specific wind turbine designs. Ultimate target is to achieve the highest possible offshore availability at optimised lifecycle costs. Objectives As part of the collaboration between ECN and XEMC DarWinD the latter provides specific technical input, whereby the DD115 serves as a case study example. Project objectives include: 1. Conducting a technical risk inventory with the aid of a Failure Mode and Effect Analysis or FMEA that includes proposals for remedying modifications by addressing these risks. A design process requires a substantial number of choices to be made, whereas process main outcomes need to be reviewed with respect to reliability and maintenance aspects; 2. Design optimisation aimed at minimising expected kwh-costs by employing the ECN O&M Tool. Some design alternatives necessitate additional analysis methods to be applied to for further evaluating (potential) optimising solutions. A cost model for maintenance cost prediction serves as support tool during the optimisation process. 3. Development of an offshore maintenance support tool OMCE dedicated towards repair and service planning during a wind farm operational phase. Optimised and cost-effective offshore wind farm maintenance requires a planning tool that preferably utilises historic wind turbine data. Equally important is to make available a complete maintenance data set covering full turbine lifetime, which in turn serves as a main planning input tool. However, accumulating that kind of dedicated database for existing onshore and offshore equipment is a well-known bottleneck. For an emerging turbine manufacturer amidst a prototype development phase this poses an even bigger challenge. Operational experience accumulated with offshore wind farms is still limited. From the early 1990 s a first generation kw wind turbines appeared, followed from 2000 by larger size installations and several major offshore wind farms. Unfortunately, in a number of reported cases significant technical failures occurred soon after wind farm commissioning, sometimes resulting in main components replacement especially affecting transformers, generators, and gearboxes. Weather window According to wind industry sources, elongated offshore installation downtime is directly linked to poor accessibility at times when remedying actions are most needed. Waiting for a sufficient operational weather window often

3 proves a critical parameter negatively affecting installation downtime. Timely barge/vessel availability is another constraint, since heavy lifting equipment like jack-up s required for component replacement jobs, might already be employed elsewhere. In almost all cases, targeted turbine availability was estimated higher than actual figures achieved. This mismatch can easily result into unexpected yield and thus revenue loss, underlining the significance of estimating O&M parameters as accurately as possible. Given actual offshore-specific O&M characteristics, accurate offshore wind farm O&M cost estimations cannot be obtained with direct calculation methods. To overcome this shortcoming several dedicated models have been developed. These usually calculate main parameters especially availability, O&M costs and downtime associated to component and/or systems failures. Currently available software tools include: ECN O&M Tool applied for calculating offshore wind farm O&M costs during planning phase; Modeling Windfarm Capex & Opex (MWCOST) incorporating Sloop Technology. This development by BMT Fluid Mechanics Limited includes an extension of SLOOP software package applied for determining offshore oil & gas installation O&M parameters; A model developed by partners Frans de Jong and Mecal targets at estimating onshore wind farm O&M costs; CONTOFAX software tool (1996) developed at the Delft University of Technology (NL) by Christian Schöntag and Gerard van Bussel. The tool is applied for estimating offshore wind farm O&M parameters by means of Monte-Carlo simulations. However, the above tools are being applied exclusively for estimating wind farm availability and O&M costs during their planning phase. The OMCE tool instead focuses at the operational wind farm phase. Risk Priority Number XEMC DarWinD has applied a risk assessment program during the DD115 design phase. Main target was to develop a highly reliable and easy to maintain offshore wind turbine capable to operate 20 years with at least 95% availability. This prompted a necessity to identify and reduce technical risks, by applying a Failure Mode and Effect Analysis (FMEA) tool that already proved its worth in multiple industries including automotive and aerospace. FMEA can be applied during the design phase, as part of a process or systems development, and within supplier partnerships. XEMC DarWinD initiates FMEA to identify technical risks at several project stages. Subdivided into systems, design, and/or process FMEA s, possible failures are identified and ranked by severity, occurrence and detect ability. Each failure is given a `score` based upon these characteristics, known as Risk Priority Number (RPN). Failures with the highest RPN qualify for a follow up, which can either involve a redesign, a planned test to determine failure probability, or an improved method to detect a failure at an early stage.

4 The assessment process commenced with a system FMEA involving the entire wind turbine. It aims at obtaining a clear picture on high-risk areas and failure modes within the overall system and exposes interfaces between individual subsystems and highlights turbine interactions with the offshore environment. A design FMEA usually commences with a brainstorm session involving engineers and field experts. With this group of professionals a particular design aspect is discussed, whereby technical risks are identified. During a follow-up ranking session engineers and field experts involved determine each failure RPN by estimating severity, occurrence and detect ability according to a scorecard. Such a scorecard contains scales running from 1 (no effect) to 10 (catastrophic) and provides guidelines for determining failure impact. A scorecard enables for instance determining the impact of specific failures to humans and/or the environment, to wind turbine functioning, damage caused (costs), loss of earnings (kwh), or repair actions needed (time/costs). XEMC DarWinD has initiated a supplier partnership program aimed at creating awareness on consequences linked to operating a supplier s product in the harsh marine environment. Key is establishing long-term relationships with main suppliers. That in turn as an envisaged prime benefit should ultimately result in optimised components and subsystems offered by each individual supplier, instead of having to relay on off-the-shelf products. The core of this supplier partnership program is a supplier FMEA, with an individual supplier product design being analysis topic. Identifying potential failures External field experts and suppliers together with XEMC DarWinD engineers and other specialists discuss design functionality and interfaces at systems level thereby identifying potential failures. To be effective, a session on a specific topic involving a brainstorm needs to be thoroughly prepared, and should only be executed after completing the internal design FMEA. After a supplier session, feedback to all participants is crucial for building necessary awareness on a specific offshore wind turbine component design. Process Failure Mode and Effect Analysis (PFMEA) as a method is capable to analyse each step or phase in a physical process (production, transportation, assembly, or installation). It specifically aims at identifying potential failure causes that might negatively impact product quality. A PFMEA should be performed just after completing the first assembly process design stage. It also needs to be conducted in such a manner that any improvements to a given product, process, or quality system can be implemented preferably before a prototype is actually being assembled. PFMEA s have been performed on three main components/sub-systems: nacelle and rotor assembly, and the bottom tower section accommodating a majority of the power electronic systems. In total about 1100 possible failure modes were identified, but most of these are unlikely to occur due too DarWinD design choices and/or production tool(s). Furthermore, detail quality checks during assembly can prevent several potential failures to actually occur.

5 In total about 60 possible failures with unacceptable risk were assessed. Of these, approximately 50 failures relate to the drive train concept and might negatively affect yield potential. However, it is remarkable indeed that about 40% of these possible failures are directly linked to component damages inflicted during assembly. PFMEA results will be brought into the assembly process as an optimising measure. Once final design details are known a PFMEA will be performed again, this time with a focus at the latest assembly process steps. Example: FMEA on main bearing and lubrication system A DD115 multi-row roller type main bearing features a continuous oil lubrication system and has been subjected to a design as well as supplier FMEA. During a main bearing lubrication unit design FMEA, about 70 potential failure modes were identified. Many of these issues are related to insufficient oil flow that can in time cause severe bearing damage. A combination of high severity, medium occurrence, and low detect ability resulted in a high RPN. Several causes were identified, including grid outage, clogged hoses, hose leakage, oil pump failure, and alterations in oil properties due to for instance changing environmental conditions. These findings resulted into a design modification suggestion, which involves adding a flow sensor to the system enabling a continuous oil flow monitoring resulting in improved detect ability. In case oil volume flow is reduced for whatever reason, the installation will be switched off automatically before serious damage does occur. However, during the supplier FMEA session objections were made to the suggested remedying solution arguing that a flow sensor is generally known to trigger unnecessary alarms. A recommended alternative solution was to integrate a simple oil pressure sensor at a carefully selected spot within the flow loop, which as a controls component enjoys a favourable 1.0 x 10-6 failures rate per hour. The latter solution, provided it is carefully positioned within the flow loop, will address all failure modes identified without affecting overall turbine reliability. Offshore design optimisation with ECN O&M Tool Any design choice (i.e. drive and control system) and offshore turbine upkeep strategies affect electricity-generating costs. All design and turbine upkeep variables should be optimised in order to maximise lifetime benefits of the wind farm owner/operator. A Levelised Production Cost (LPC) method originating from the International Energy Agency (IEA) has been adopted as main economic assessment parameter for quantifying many of these latter aspects. LPC is defined as present value of all costs divided by the discounted electricity production value, and represents average lifetime cost for producing one unit (1 kwh) of electric power. An LPC includes all wind farm lifecycle aspects from manufacturing and installation to operation and dismantling.

6 When considering alternative design optimising options, both initial investment and lifetime O&M expenses need to be taken into account. However, calculating especially offshore wind farm maintenance costs involves several stochastic parameters, which include site accessibility limitations due to adverse weather conditions and vessel availability. For that reason, XEMC DarWinD applies the ECN O&M Tool that has proven to be capable of generating O&M cost estimates for offshore wind farms (and not individual wind turbine level) before a designs has been finalised. After a baseline model has been defined, a fresh calculation can performed almost instantly. When considering different maintenance strategies it is crucial that only a limited number of parameters are adjusted simultaneously, enabling a clear root cause identification process revealing both potential cost increase or decrease (trends). A sensitivity analysis can thereby prove useful as an instrument providing additional project insight. However, since the ECN O&M Tool is a model, it should be noted that all results must be carefully examined in order to make certain that they correspond to realistic values. Despite this call for caution it was found that dedicated design optimisation measures by quantifying costs effects, offer the potential to reduce both O&M costs and revenue losses by 1-5%. Most of these measures are either focused at easing maintenance and/or options to postpone repairs until a next scheduled maintenance visit, and as such do not require extended reengineering effort. Installation upkeep One of the other objectives of this We@Sea funded project is to provide a kick-off for developing the Operation & Maintenance Cost Estimator or OMCE software tool. Once fully tested and optimised this tool is aimed to become a commercial product available to any offshore wind turbine manufacturer. The instrument should further facilitate a choice of upkeep strategies for the medium to long term. Finally, the risk assessment program aimed at identifying, prioritising and addressing technical risks proved fruitful. The large number of issues found underlines that generally even a strong existing wind turbine concept needs re-evaluation for offshore purposes. Several design improvements could be realised at relatively low costs, resulting in increased availability. The system-, design-, process- and supplier FMEA brainstorm sessions thereby resulted into a substantially expanded offshore wind turbine design knowledge base. Since XEMC Darwind actively involves suppliers in FMEA sessions, this fresh knowledge was shared with many wind industry partners raising awareness on reliability and maintainability issues under demanding offshore conditions. FMEA timing is thereby crucial and the assessments should be performed at an early design path stage after finishing the conceptual phase, but well before completing detail design.