Low-risk Processes, Customized for Operation of Offshore Wind Farms

Transcription

1 Low-risk Processes, Customized for Operation of Offshore Wind Farms S. Greiner, H. Albers, Hochschule Bremen, Germany T. Renz, IZP Dresden mbh, Germany S. Greiner External Article English Summary In addition to technological and logistical improvements, efficient operation and maintenance (O&M) processes will contribute to cost reductions of offshore wind farms (OWF). The optimization of these O&M-processes by lowering process risks is one methodical approach. It may lead to lower downtimes of wind turbines and less cost for resources. The detailed description of OWF in O&M phases from a processing point of view will be presented, along with the description of the risk analysis method Process-FMEA, which is adapted on OWF-requirements. Furthermore the combination of the process characterization and the results of risk analysis with a simulation tool, as a possibility to compare different process alternatives, will be described shortly. First optimization potentials will be shown. Introduction Studies show the energy turnaround in Germany can only be achieved with offshore wind energy. But the high costs of this technology have to be reduced to become competitive to fossil fuels and to counteract rising electricity costs. Not only multi-operator sea-based maintenance concepts and more efficient wind energy turbines offer a high potential to reduce the operation costs [1] but also more effective and efficient maintenance processes can contribute to the reduction [in accordance to [2]]. One key is the reduction of process risks [3], e.g. process delays of repair operations, which can lead to loss of energy revenues combined with additional expenses for maintenance processes. Another key is the target-oriented application of process key indicators. In view of the above this article reports about a method to optimize maintenance processes at offshore wind farms. It focuses on the example process repair of small components by using a personnel transfer vessel. Optimization potentials will be shown. O&M of Offshore Wind Farms - An Intercompany Structure Offshore wind farms (OWF) are complex systems with a high amount of different parties concerned, infrastructure elements, interactions between them and interfaces. Fig. 1 is an extract of the dependency diagram of the system offshore wind farm in the maintenance phase, particularly in repair status. The figure is divided into onshore and offshore sections. The icons are parties concerned and infrastructure elements. The arrows between them are interfaces on the 58 DEWI MAGAZIN NO. 44, FEBRUARY 2014

2 one hand and interactions on the other. The interactions are defined as staff, material, waste, finances and information flows. In accordance to DIN 31051:2006 the status maintenance of an OWF contains the four main processes inspection, maintenance, repair and improvement. All these main processes are further divided into the sub-processes determination of requirements, mission planning, preparation, execution, inclusive outward journey / residence, execution on-site and return journey as well as post processing. The process map of OWF maintenance (Fig. 2) shows the structure of maintenance sub-processes. The actual picture of sub-processes is based on the individual requirements and demand of work as well as different transport devices (blue boxes). The example Repair of small components process by using a personnel transfer vessel (PTV) and executed onsite by wind turbine manufacturer is displayed in deeper blue colored boxes (Fig. 2). The specific es are modeled in the process modeling language BPMN 2.0. Fig. 3 shows the model for return journey by personnel transfer vessel. Each party concerned is displayed in the pools (blue lanes). A deeper division of them in different departments or persons is also possible, such as captain and crew of sea haulier. The pools are commented with the tasks of the different companies. Each pool begins with a start event and finishes with an end event. Activities are running sequentially among them. The interactions are marked in defined colors for the different possible interactions of an OWF in maintenance, such as black for information flows. The detailed models are backed up by information about human and technical resources, time intervals and durations. This offshore wind farm characterization model consists of knowledge of parties concerned and their connections between them (dependency diagram), the maintenance process structure (main process and process map) and the detailed models of sub-processes as well as further resources and time information. The model is the foundation for an analysis of process risks, for process optimization and analysis of dynamic correlations. The risk identification and evaluation is based on the subdivision of OWF maintenance processes and process models of the sub-processes. Activities and interactions in the process models serve as a basis for risk events. Different process levels are used to determine effects. The simulation for the analysis of dynamic correlations between maintenance processes, weather conditions and reliability of wind turbines is based on the process models, meteorological and hydrographical scenarios as well as technical information about the wind turbines, used transport devices, time intervals and durations. Find out Risk-relevant Processes Risk-relevant processes have to be investigated by a risk analysis to find out significant process risks which may lead to time delays of processes, e.g. the early return journey from the OWF back to land (Fig. 3) because of changing weather conditions or forgotten material. The time delay of a process has to have a significant financial impact, e.g. loss of income because of a long standstill of an offshore wind turbine (OWT) and / or high logistic costs.with respect to the process description of an OWF there are processes with a high risk potential because of the high amount of parties concerned and interactions as well as responsibilities combined with a difficult environment. The risks which may be relevant can be defined by using the following criteria set: Key process, e.g. top level importance for process leading and availability of OWT Financial impact, e.g. significant impact on assets or income and expenses Complexity, e.g. complicated net of players, their activities and interactions Compliance, e.g. affected by internal regulations of parties concerned or legal rules, like work time regulation, particularly Endangerment, e.g. common high failure rate or particular time delay danger of sub-processes, like high dependence on the weather or human errors (i.e. people often make mistakes by ignoring relevant information) The establishment of the criteria complexity is difficult and could be supported with a mathematical formula: As a measure of the complexity the product of the process size n, the mean activity duration d and the degree v of cross-linking is used. The process size n is the number of all specified activities in the process. These activities comprise the activities inside the lanes as well as the links between the lanes which are interpreted as activities too (refer to Fig. 3). The mean activity duration d is the sum of all activity durations including the linking activities divided by the number n of activities. The degree v of cross linking is a weighted average of the lane specific cross linking degrees and the cross linking degree between the lanes. In general cross linking degrees are evaluated by counting the links divided by the maximum number of possible links. In order to get a comparable value for evaluating and choosing risk relevant processes, the criteria must be prioritized and quantified. Examples for risk-relevant sub-processes of the repair of small components are Mission Planning Mission planning covers the best combining of determined work assignments under current requirements and necessities, e.g. weather conditions and logistics. This process is the basis for successfully carried out work assignments on-site the wind farm. It has a great impact on expenses and incomes of the OWF also. Preparation Preparation covers the preparation of wind turbine technicians, material, spare parts and tools as well as logistics processes. Forgotten or damaged material leads to time delay or abort of a work assignment. Because of difficult weather conditions with narrow time slots for working and high logistic costs as well as restricted availability of special vessels the preparation has a great impact on expenses and incomes of the OWF also. The defined risk-relevant processes have to be analyzed in respect of their process risks. Optimization measures must be developed and realized. DEWI MAGAZIN NO. 44, FEBRUARY

3 Fig. 1: Extract of the system offshore wind farm in repair status Analysis of Process Risks The risk analysis method Process Failure Mode and Effects Analysis (Process-FMEA) is used for failure detection, risk assessment and analysis of processes. Empirical knowledge about failure correlations, circumstances and their influences on the efficiency of processes will be systematically and permanently documented. The Process-FMEA is able to identify critical components and weaknesses in the operation planning as well as in the operation and maintenance processes itself. Thus the connected risks and their costs respectively can be minimized and the costs of failure clearances can be reduced considerably [4]. The point of origin of a Process-FMEA is the possibility of more or less likely process failures, as for example the wrong execution of a repair task not in accordance to the documentation given. The following failure analysis is defining the cause of failure and effects for the process result, the process duration time and the process costs. The failure cause-effect linkage is delivering additional information: the severity of failure effects, the probability or frequency of failure causes and the probability of failure effects under the condition that the failure cause has occurred (problem of failure detection). Based upon these analyses, suitable measures for the avoidance and prevention of the failure or its reduction of effects can be deducted [5]. The execution of a Process-FMEA is strongly influenced by the definition of a cross-functional team of experts, in order to ensure that the experience and knowledge of all fields of expertise and sections of the operation and maintenance enter into the analysis [5]. The basis of the Process-FMEA is the complete system and process analysis for understanding the maintenance processes. The analysis of the maintenance processes incorporates the dependency diagram, the differentiation into sub-processes (Fig. 2) and the depiction in process models (Fig. 3) as well as the determination of risk-relevant processes. Based on this the failure analysis for each risk relevant sub-process is following, as for example the mission planning with the differentiation of combinations of work assignments under different circumstances, e.g. weather conditions or logistics. In the failure analysis types of failures are assigned and their causes determined. This is being done on the basis of the 5M (in German) parameters Human (Mensch), e.g. failures because of their activities and / or actions Hardware (Maschine), e.g. IT is under construction or crane is damaged Material (Material), e.g. damaged transport boxes or no information Method (Methode), e.g. way of doing work Environment (Mitwelt), e.g. stormy weather or noncompliance with a rule and their respective temporal effects on sub-processes (e.g. return journey) and the overall main process (e.g. repair of small components). The focus for identifying weaknesses lies on the activities, which are running in the sub-processes, as these are very fault-prone and can, in case of failure, lead to extensive time delays and thus to a reduced energy return through a late maintenance. Fig. 4 is displaying the system analysis, considering the failure Cannot connect access system with OWT because of deficient transitional system. On the basis of the failure analysis each failure is assigned a series of effects and their respective causes. The evaluation of the risks is conducted through the definition of parameters for the occurrence of the cause defined as a probability considering a special risk time or a failure frequency (O) and the severity of failures (S) compared with the probability of failure effects. The severity of failures includes the determination of process time delays connected with additional costs of the process, which are estimated with pos 60 DEWI MAGAZIN NO. 44, FEBRUARY 2014

4 Fig. 2: Process map of offshore wind farm maintenance with highlighted repair of small components process by using a PTV sible probabilities. Fig. 5 is displaying a risk evaluation for the failure Cannot connect access system with OWT because of deficient transitional system. The process time delay is divided into five time intervals based on project internal studies of delays in maintenance. The intervals of additional process costs reflect the costs of different transport devices in particular, like per helicopter flying hour or daily charter costs of more than per Jack up barge. The combination of low process time delay and high additional process costs as well as high process time delay and low additional costs (hatched area) will not arise. The sum of probabilities of failure effects must be 100%. The example Cannot connect access system with OWT because of deficient transitional system during the return journey by PTV can lead to a probabilities set of 20% that technicians and material are transferred back home by a helicopter on the same day 5% that technicians and material are transferred back home by a PTV onthe same day 60% respectively 75% that technicians are transferred back home by a helicopter on the same day, but the material can be transferred back home some days later by PTV or technicians and material have to stay 2 or more days at the wind turbine The severity of failure is the result of the weighted sum of the single evaluations of possible costs time delay combinations. = X i with X i = loss of income + additional costs of process *probability of failure effects For this the process delay has to be converted in loss of income. loss of income = power * equiv. full load hours * legal compensation On the basis of the quantified risk value (O*S) the implementation of detection, avoidance and risk reduction measures can be done. These measures are reflected in the process models, especially in failure-based events, compensation activities and process aborts. Moreover procedural rules and working instructions are also affected. Inter alia, the following measures for an optimized process Return journey by PTV were deduced: redundant or alternative systems for safe transfer of technicians and material systems check in the sub-process preparation based on checklists reliable weather prediction The results of the risk analysis are immediately transferable into the process models, which results, in combination with the simulation, in the evaluation of different process alternatives, as well as the process design and the defined key indicators. Especially the monetary evaluation enables the integration of the results in a cost-benefit equation. Simulation of Processes The simulation tool shows the effect of maintenance processes on the state of wind turbines under consideration of weather conditions. The tool is based on the capability of coupling process models with weather and wind farm models. The modeling of wind farms is carried out on three different levels, namely its turbines, their respective components and the aggregation to a wind farm. The turbine definition allows the depiction of the energy output of individual wind turbines or whole wind farms. Furthermore the OWF-model contains the occurrence probability of technical failure signals. These signals are the input signals for the process model determination of requirements. Another component of the simulation tool is the stochastic weather generator. On the basis of historical weather data DEWI MAGAZIN NO. 44, FEBRUARY

5 Fig. 3: Extract of the process model of Return Journey by Personnel Transfer Vessel Fig. 4: Failure analysis for the example Cannot connect access system with OWT process time delay <= 1 d 2 4 d 5 13 d d > 30 d Fig. 5: Risk evaluation of failures in maintenance processes of OWF on the example of Cannot connect access system with OWT because of deficient transitional system during return journey by PTV additional costs of processes <=1 T 2 5 T 20% probability of failure effects 6 21 T 5% 60% T 15% > 65 T 62 DEWI MAGAZIN NO. 44, FEBRUARY 2014

6 Advantages transparent structure which is ideally suited to offshore windfarms in maintenance and their maintenance processes running maintenance processes are identified and described, the development and planning of these processes can be done at an early stage process risks can be identified and handled in an OWF-adapted way different experts and parties concerned have to be involved Disadvantages the parties concerned have to give an insight into their requirements and activities, which are related to the OWF maintenance; this is not often granted in order to carry out the risk analysis, the maintenance processes with their sub-processes and activities as well as their parties concerned have to be determined completely risk analysis is a very substantial method, therefore only really risk relevant sub-processes should be investigated Tab. 1: Pros and cons of toolbox application of FINO I, the weather generator creates new sets of data in order to make realistic weather data available for the simulation. This is carried out by triggering the corresponding activities in the process models. It means in effect for the processes: if the weather conditions do not allow a work placement on high seas, processes have to be canceled, aborted and compensated. Furthermore, the tool is able to simulate the outcome of different approaches of maintenance processes. Questions like how to maintain offshore wind turbines, which transportation device to use, when to use it, how many people are needed, for how many days, can be answered. The simulation tool allows to compare different maintenance strategies over the operation and maintenance phase. [6] Low risk processes a chance for cost reduction The first results show that the toolbox introduced comprising the offshore wind farms characterization, the risk analysis and the simulation is a really suitable support to reduce costs in the operation phase and to get access to efficient and effective processes. But the most important issue for successful application of this toolbox is a good exchange of information and communication between the parties concerned. An overview of advantages and disadvantages of application of the toolbox are shown in Tab. 1. The maintenance processes, like repair of small components, preventive maintenance or replacement of large component parts, have similar process structure and parties concerned. Substantial differences can be found in the activities of sub-processes and their parameters. So, results of the risk analysis of repair of small components can be carried over to them. Examples for optimization measures for repair process by using a personnel transfer vessel (PTV) and executed on-site by wind turbine manufacturer are The combination of different work assignments and the respective parties responsible for more effectiveness and efficiency, e.g. several repairs of an OWT at the same time The need for redundant hardware offshore, e.g. alternative transitional system like boat landing Adequate assistance for technicians, e.g. operating procedures, checklists, as well as training courses, for qualified performance of the work Support for the operational management, e.g. shared software application for all parties involved or an adapted people- and vessel-tracking system, for a seamless management of data across all sub-processes Intelligent resource planning for more effectiveness and efficiency, e.g. choice of transport devices or staff qualification Furthermore, with this toolbox a planning and optimization tool for O&M processes is originated, which should also be considered in the OWF planning and design phase. Acknowledgement The results are originated from the research & development project SystOp Offshore Wind Development of a planning and optimization tool for system-related optimization of the offshore wind farm performance system s funded by the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety. SystOp Offshore Wind is a joint research project in cooperation with Hochschule Bremen, Universität Hamburg, IZP Dresden mbh and BTC AG. For more information follow Literature [1] Fichtner, Prognos (2013): Kostensenkungspotenziale der Offshore- Windenergie in Deutschland - Kurzfassung, im Auftrag der Stiftung Offshore-Windenergie [2] Fischermanns (2012): Praxishandbuch Prozessmanagement, ibo Schriftenreihe, Band 9, Verlag Dr. Götz Schmidt [3] Rieke (2009): Prozessorientiertes Risikomanagement Ein informationsmodellorientierter Ansatz, Dissertation, Advances in Information Systems and Management Science Band 38, Berlin: Logos Verlag, 2009 [4] Hering, E., Triemel, J., Blank, H.-P. (2003) Qualitätssicherung für Ingenieure, VDI-Verlag [5] DGQ (2012) FMEA - Fehlermöglichkeits- und Einflussanalyse; DGQ- Band 13-11; Deutsche Gesellschaft für Qualität e.v.; Beuth-Verlag [6] Joschko,P. et. al. (2013) Modeling and Simulation of Offshore Wind Farms including the Mapping and Analysis of relevant O&M Processes, 27th International Conference on Informatics for Environmental Protection (Enviro Info 2013), , Hamburg DEWI MAGAZIN NO. 44, FEBRUARY