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INDUSTRY INFOSHEET: Renewable Energy Generate clean energy more efficiently with powerful data analytics Design more robust and better performing equipment using experimental design and multivariate analysis > Reduce costly unscheduled maintenance and machinery downtime with powerful multivariate prediction models > Optimize equipment and machinery use by understanding process and environmental factors affecting them > CAMO > Renewable Energy Generate sustainable energy more efficiently and cost effectively Advanced data analysis tools can help renewable energy companies operate more efficiently, from R&D - such as developing more efficient solar panels and more robust wind turbine blades - to solving common problems such as predicting turbine breakdowns and optimizing the use of equipment depending on local conditions and demand. Multivariate data analysis is used extensively in industries such as pharmaceuticals, chemicals, biotechnology, semi-conductors and agriculture to understand large, complex data sets that traditional statistics are inefficient or unable to handle. Now, these powerful but relatively easy to use tools are being applied by the energy sector to help improve their product and process performance. CAMO Software’s solutions can be integrated with existing control systems, accepting proprietary data formats from sensors, industrial databases (ODBC and OSI PI) and process instruments, using protocols such as Modbus, Profibus, TCP/IP and now OPC (DA, HDA and UA capabilities). The graphical outputs make interpretation simple and can be customized for all user levels, from expert to operator. REAL BUSINESS BENEFITS Our solutions can be used across the renewable energy generation value chain from product development to process and equipment monitoring. Product development Process monitoring Equipment monitoring > Use Design of Experiments and multivariate data analysis to design more efficient solar cells > Avoid production shutdowns with early event detection using multivariate predictive models > Understand the impact of environmental conditions to increase the lifetime of equipment > Develop more robust turbines or blades using advanced materials > Implement preventative maintenance programmes based on powerful regression models > Get an overview if a process is in control or requires intervention What is Multivariate Data Analysis? Multivariate data analysis is the investigation of many variables, simultaneously, in order to understand the relationships that exist between them. While traditional (univariate) statistical approaches such as mean, median, standard deviation etc serve their purposes for investigating and understanding simple systems, when the relationships between variables are complex a single variable cannot adequately describe the system. Exploratory data analysis (data mining), clustering, regression and predictive analysis are typical multivariate tools. > Bring data to life > camo.com DOWNLOAD FREE E-BOOK CAMO > Renewable Energy case studies and example applications Case study: Wind turbine monitoring A major European renewable energy firm operates wind farms with several hundred turbines in each. In one particular farm of 226 turbines, 28 had faults resulting in breakdowns. The client wanted to be able to predict which turbines were likely to malfunction in the future. Each turbine had a number of sensors mounted on them so they could measure vibrations, temperature, pressure, load etc. In addition, each turbine had associated historical data including the number of hours of operation, total amount of energy produced and the location. Case study: Product development for wind turbine blades A global wind turbine manufacturing client used multivariate data analysis and designed experiments (DoE) to develop turbine blades constructed from advanced materials. Using DoE they were able to determine the optimal design parameters to produce more reliable, durable blades while analyzing quality parameters with multivariate analysis. To begin the project, all the data from the sensors over a certain period of time was collected together with the historic data and analyzed using multivariate methods, from which a multivariate predictive model was developed. Then, using statistical methods, we were able to define for the client when production was ‘normal’ i.e. within the sweet spot of optimal operating parameters. Next, new observations (sensor data) could be projected onto the multivariate model developed earlier to identify deviation from normal situations. In situations where data did go outside normal parameters, operators were able to see which variable (e.g. load) had changed. The resulting model was able to identify 100% of the wind turbines with failures and this could be applied to realtime monitoring of turbines and even the entire wind farm. Example application: Predictive maintenance in a hydro-electric facility A major European hydro-electric company had persistent problems with a turbine breaking down resulting in long periods of downtime and expensive maintenance. Multivariate analysis could be used to analyze historic data to determine the conditions leading to breakdown. After instrumenting the turbine, this model could be refined with additional data points from sensor readings over time to make a more accurate model. This enables systems to be put in place to alert operators in real-time when a breakdown is imminent, thereby allowing them to implement preventative maintenance before failure occurred. DON’T WASTE YOUR VALUABLE DATA Most energy manufacturers collect an enormous amount of data from sensors, yet the majority do not exploit its full potential due to the perceived difficulty and lack of statistical knowledge. However, today’s data mining and analytical tools are much simpler to use and even more powerful, enabling industry leaders to get valuable insights from their data which are driving significant business improvements. > Bring data to life > camo.com CAMO SOFTWARE PRODUCTS & SERVICES Get deeper insights from your data with our range of powerful, yet easy to use and affordable data mining and predictive analysis solutions. The Unscrambler® X Unscrambler® X Process Pulse Leading multivariate analysis software used by thousands of data analysts around the world every day. Includes powerful regression, classification and exploratory data analysis tools. TRIAL VERSION READ MORE Real-time process monitoring software that lets you predict, identify and correct deviations in a process before they become problems. Affordable, easy to set up and use. TRIAL VERSION READ MORE Training Our Partners Consultancy and Data Analysis Services Our experienced, professional trainers can help your team use multivariate analysis to get more value from your data. Classroom, online or tailored in-house training courses from beginner to expert levels available. READ MORE CONTACT US CAMO Software works with a wide range of instrument and system vendors. For more information please contact your regional CAMO Software office or visit www.camo.com/partners Do you have a lot of data and information but don’t have resources in house or time to analyze it? Our consultants offer world-leading data analysis skills combined with hands-on industry expertise. READ MORE CONTACT US Unscrambler® X Prediction Engine & Classification Engine Software integrated directly into analytical or scientific instruments for real-time predictions and classifications directly from the instruments using multivariate models from The Unscrambler® X. TRIAL VERSION READ MORE Find out more For more information please contact your regional CAMO office or email [email protected] www.camo.com NORWAY Nedre Vollgate 8, N-0158 Oslo Tel: (+47) 223 963 00 Fax: (+47) 223 963 22 USA One Woodbridge Center Suite 319, Woodbridge NJ 07095 Tel: (+1) 732 726 9200 Fax: (+1) 973 556 1229 INDIA 14 & 15, Krishna Reddy Colony, Domlur Layout Bangalore - 560 071 Tel: (+91) 80 4125 4242 Fax: (+91) 80 4125 4181 JAPAN Shibuya 3-chome Square Bldg 2F 3-5-16 Shibuya Shibuya-ku Tokyo, 150-0002 Tel: (+81) 3 6868 7669 Fax: (+81) 3 6730 9539 AUSTRALIA PO Box 97 St Peters NSW, 2044 Tel: (+61) 4 0888 2007