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Port Glasgow, United Kingdom

Lazakis I.,University of Strathclyde | Turan O.,University of Strathclyde | Judah S.,SSE Renewables
3rd International Symposium on Ship Operations, Management and Economics 2011 | Year: 2011

Maintenance tasks and applications in the shipping industry have evolved significantly in the last few years. Particularly in the offshore industry, safety inboard, environmental protection and intensive operational activities necessitate the minimisation of down-time and the preservation of an excellent performance ratio. The research study herein presents a review of the maintenance standards and procedures together with an enhanced ship maintenance approach based on criticality and reliability assessment. Fault Tree Analysis (FTA) with time-dependant dynamic gates is used to represent the interrelation of the system's components. Moreover, the Birnbaum and Criticality reliability importance measures validate the results of the analysis. A case study of a diving support vessel will illustrate the application of this approach. Main outcomes are the identification of the critical items of each system as well as suggest measures which will enhance the operational availability and capability of the vessel. Source


Turan O.,University of Strathclyde | Lazakis I.,University of Strathclyde | Judah S.,SSE Renewables | Incecik A.,University of Strathclyde
Quality and Reliability Engineering International | Year: 2011

Maintenance tasks and their application in the shipping industry have evolved significantly in the recent years. Particularly in the offshore industry, safety onboard, environmental protection and intensive operational activities necessitate the minimization of down-time and the preservation of an excellent performance ratio. The first step of an innovative ship maintenance strategy, which is proposed by the authors and is based on criticality and reliability assessment, is presented herein using the FTA tool with time-dependant dynamic gates so as to represent in an accurate and comprehensive way the interrelation of the components of a system. The paper also presents a review of the maintenance standards and procedures, such as the ALARP concept, the Key Programme 3-Asset Integrity (KP3) initiative, the OREDA handbook as well as the RCM and RBI principles. As part of the reliability assessment, the Birnbaum and Criticality reliability importance measures are utilized to validate the results of the analysis. A case study of a diving support vessel (DSV) illustrates the application of this strategy. The main systems examined are: the vessel's power plant, propulsion, water system, lifting, hauling and anchoring, diving and finally the safety system. The reliability of the main systems and subsystems as well as of their critical components is identified and suggestions of how to improve the overall reliability of the various systems both at a component, system and managerial level are also proposed. © 2011 John Wiley & Sons, Ltd. Source


News Article | January 29, 2016
Site: http://cleantechnica.com

Siemens has received two orders for onshore wind projects in Ireland, together totaling 172 MW. According to an announcement made by the German multinational today on its website, Siemens received two orders for onshore wind projects in Ireland. Siemens will provide 36 SWT-3.0-101 D3 direct drive wind turbines to the Cloosh Valley Wind Farm — also known as Galway Wind Park Phase 2 — which will add 108 MW to the project and Ireland’s renewable energy capacity. The Galway Wind Park is part of SSE Renewables’ development of a wind farm cluster in the region, which was preceded by Phase 1, for which Siemens provided 22 SWT-3.0-101 wind turbines. The Cloosh Valley project is the second phase of the cluster. In addition, a second order for 20 SWT-3.2-101 wind turbines will be delivered to the Irish Sliabh Bawn Wind Farm in County Roscommon, which will add 64 MW. The Sliabh Bawn Wind Farm project is being built on Sliabh Bawn Mountain, south east of Strokestown, and will provide the equivalent amount of clean energy of approximately 41,000 local households. “With 2,400 MW of installed capacity, wind energy in the Republic of Ireland is not only a growing sector but also an industry creating jobs and benefiting communities,” said Thomas Richterich, CEO Onshore of Siemens’ Wind Power and Renewables Division. “In this context the projects with our customers SSE Renewables, Bord na Mona, and Coillte are of special significance to us. With a total capacity of 172 megawatts, the Cloosh Valley and Sliabh Bawn wind farms will contribute significantly to the Irish Government’s renewable goals.” Siemens expects that commissioning for both projects will take place in 2017, and both orders include Siemens 15 year service agreement.    Get CleanTechnica’s 1st (completely free) electric car report → “Electric Cars: What Early Adopters & First Followers Want.”   Come attend CleanTechnica’s 1st “Cleantech Revolution Tour” event → in Berlin, Germany, April 9–10.   Keep up to date with all the hottest cleantech news by subscribing to our (free) cleantech newsletter, or keep an eye on sector-specific news by getting our (also free) solar energy newsletter, electric vehicle newsletter, or wind energy newsletter.  


Theunissen R.,University of Bristol | Housley P.,SSE Renewables | Allen C.B.,University of Bristol | Carey C.,SSE Renewables
Wind Energy | Year: 2015

The optimization of wind farms with respect to spatial layout is addressed experimentally. Wake effects within wind turbine farms are well known to be deleterious in terms of power generation and structural loading, which is corroborated in this study. Computational models are the predominant tools in the prediction of turbine-induced flow fields. However, for wind farms comprising hundreds of turbines, reliability of the obtained numerical data becomes a growing concern with potentially costly consequences. This study pursues a systematic complementary theoretical, experimental and numerical study of variations in generated power with turbine layout of an 80 turbine large wind farm. Wake effects within offshore wind turbine arrays are emulated using porous discs mounted on a flat plate in a wind tunnel. The adopted approach to reproduce experimentally individual turbine wake characteristics is presented, and drag measurements are argued to correctly capture the variation in power generation with turbine layout. Experimental data are juxtaposed with power predictions using ANSYS WindModeller simulation suite. Although comparison with available wind farm power output data has been limited, it is demonstrated nonetheless that this approach has potential for the validation of numerical models of power loss due to wake effects or even to make a direct physical prediction. The approach has even indicated useful data for the improvement of the physics within numerical models. Copyright © 2014 John Wiley & Sons, Ltd. Source


Montavon C.,ANSYS Inc. | Rodaway C.,SSE Renewables | Housley P.,SSE Renewables | Jones I.,ANSYS Inc.
European Wind Energy Association Conference and Exhibition 2014, EWEA 2014 | Year: 2014

Site complexity, both in terms of terrain and forestry, determines the speed, turbulence intensity (TI) and shear exponent factor (SEF) of the wind flow that will be experienced by turbines located on the site. Atmospheric stability conditions, and in particular diurnal cycles affecting the site, play a significant role in modulating these parameters. Understanding how the stability conditions affect the wind flow is important for turbine suitability and energy yield assessments. When modelling is based on the assumption of a neutral atmosphere, these assessments may not capture key site-specific wind flow characteristics. This contribution investigates the sensitivity of the TI and SEF to surface stability conditions for a site of moderate terrain complexity with complex forestry. A CFD analysis of the site is performed for varying stability conditions, the results of which are compared to data from masts on site. Finally the simulation results are aggregated with site wind speed data and mesoscale hindcast data to derive the sensitivity of the predicted wind speed distribution on site to the assumptions in the simulation conditions. Source

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