The Energy Blog
Kristina Dotzauer 16/05/2017
With an ability to aggregate and then assess an almost infinite set of factors influencing oil prices, experts in the field get particular respect from Middle East correspondent Ward Pincus.
Like most people, I used to think of oil as just this smelly flammable liquid that you pump into your gas tank. But then I read Daniel Yergin’s “The Prize: The Epic Quest for Oil, Money & Power.” This book is rightfully regarded as the definitive history of hydrocarbons. Written in an engaging style full of anecdotes, “The Prize” helped me to see that oil is not just another commodity.
Instead, it’s something that impacts - and is impacted by - almost everything in the modern world. From the economy to the environment, from politics to plastics, oil and its price plays a central role.
In fact, my big takeaway from the book was that during World War II, Germany faced a significant strategic disadvantage – as compared to the United States – because within its own borders it didn’t have the oil resources it needed to fuel its military’s tanks, trucks and aircraft.
As Dubai-based oil expert Robin Mills said when interviewing him for this article on what’s next for global oil prices, hydrocarbons are an extremely efficient fuel for transportation. He made this point while talking about how increased use of renewables would impact future oil and gas demand in areas such as electricity production. But he said that when it comes to powering cars, trucks and planes, renewables still have some ways to go.
His point reinforces the notion that oil and gas touch almost every aspect of our world, and it highlights why interviewing oil industry experts is so interesting.
The Oracles of Oil
To only slightly exaggerate, you can think of such a specialist as a modern day Oracle of Delphi, standing over the oil wells, sniffing the vapors and telling us our future. Of course, one big difference – and why it’s such a boon to interview them – is that they not only tell you whether prices will rise or fall, but they also provide as much detailed explanation as you’d like to hear.
Because of the interplay between oil and almost everything else, these experts tend to be fluent across a broad range of topics, since understand prices means understanding not only economics and politics, but also fields such as history, geology, engineering and psychology.
Then, they have to consider each of these data points, weight how much it will impact the price in comparison to every other influencing factor, and then divine a price – or, more often, a price range.
Time flies by
This encyclopedic view of the world that they offer – as well as a graciousness in fully explaining each point – is my excuse for spending at least twice as long interviewing Paul Markwell, Vice President of Global Upstream Oil & Gas Research & Consulting at IHS Markit, for the oil price article as was scheduled.
My other excuse? The Vice Chairman of IHS Markit is “The Prize” author Daniel Yergin. That interview is probably as close to this famous oracle as I’m likely to get.
Ward Pincus, based in Dubai, is a Middle East expert on science, technology, health, and business issues for various publications in North America, Europe, and the Middle East. He has repeatedly written about the oil price and innovations in the industry.
Denis Imamovic 09/05/2017
In this blog post we want to talk about our newest innovation - the Mobile Factory Concept. With the innovation of our so-called ‘Mobile Factory’ (MF) we target to implement a highly automated welding and laying installation process for gas-insulated lines (GIL). The new system will replace the previously required project-specific assembly tent and is thus a time and cost-saving solution, which makes the GIL more competitive in long distance underground transmission.
Significant cost reduction for long distances:
The longer the installation distance the more efficient the Mobile Factory concept. Through its faster laying and welding process, the GIL becomes more favorable and competitive for underground transmission. Several Mobile Factories can work in parallel on different sections of the same transmission line, to intensify the work and to handle very long distances.
Flexible and autonomous working system:
The MF can either lay the GIL directly buried in the ground or in tunnels. Through its modular design, consisting of a so-called technology module and the tube magazine with its associated welding unit, the MF could be moved to nearly any desired location. Driven by four hydraulic engines, it can move independently on its crawler track with a speed of 4 km/h to the next position on site. Thereby it can overcome a gradient of up to 8 %. The Mobile Factory has its own energy supply and is therefore completely self-sufficient.
Operating principle for a direct buried GIL:
After finishing the excavation works, the Mobile Factory is positioned on the desired place on site. Now the tube storage system will be loaded by crane with the pre-assembled GIL. The tubes are thereafter automatically handled in the magazine with a maximum capacity of 8 tubes. A special aligning wagon lifts the tubes from the magazine and brings them to the welding place. There the tubes are pressed and welded together. After welding, a winch can pull the tube into the trench.
After laying the GIL, the trench is backfilled with soil. To install very long routes in a limited time, a large number of work operations can be conducted in parallel using several mobile factories. Time advantages can be leveraged using this modular, parallelized method of construction.
This article was written by Denis Imamovic, Director of Power Transmission Lines at Siemens. Take a look at his previous pieces here!
Kristina Dotzauer 03/05/2017
Energy consumption, energy supply, energy efficiency – the topic of energy is relevant for nearly every industry. In an age of increasing digitalization, new energy technologies and systems are the key to achieving optimized production. Thus, energy is becoming an economic factor. To support our customers during this development, we presented a wide range of energy-related products and services at this year’s Hannover Messe. These were our highlights.
“The throng of people showed just how important the topic of energy has become across industries.” Thomas Linack and his colleagues were in charge of the Energy for Industry showcase, and he looks back on a tiring but successful week. The showcase was certainly one of the highlights at Hannover Messe 2017. “After all, electrical energy is the most important requirement for digitalization,” explains Linack. For efficient production, companies need a reliable power supply with a consistent quality at affordable prices. “That makes energy a competitive factor,” affirms Linack. “After all, energy accounts for as much as 40 percent of the production costs, especially in energy-intensive industries such as the steel industry.”
Linack reflects on the week: “Our visitors were particularly interested in the changes in the energy landscape that have occurred as a result of digitalization.” New technologies and resources are paving the way for higher efficiency, safety, and availability. At the same time, the development of renewable energy resources and decentralization are influencing the supply quality. In this regard, state-of-the-art control technology and storage technologies play key roles. They manage energy to ensure that changes in the supply will not lead to production problems.
Solutions for every need
Yet what is the most intelligent and efficient way to do this? “With our Totally Integrated Power (TIP) portfolio, we are pursuing a holistic approach,” explains marketing manager Ottmar Lehmann. “It is about tailoring the supply to meet the different individual requirements. That is what our visitors are interested in.”
TIP products are modular and can be integrated into any system. This ensures a reliable, safe, and efficient power supply with software and hardware products and solutions for all voltage levels. In addition to transformers and switchgear, the portfolio includes turnkey high-voltage substations and low-voltage and medium-voltage switchgear. Furthermore, we supply safe and cost-effective solutions from a single source: from the process-oriented planning of power supply systems to system design to a comprehensive range of services and system operation. This facilitates an infrastructure that is energy-efficient, cost-effective, and environmentally friendly.
From consumers to prosumers
The fundamental requirement for an optimal energy management and the monitoring of consumption costs is the energy system. A change is taking place, a shift to a prosumer system that permits energy flows in several directions. Energy is no longer linear and supplied under limited market conditions; instead, it is supplied in a variety of ways. “There is a strong demand for distributed energy solutions in particular,” says DES sales consultant Max Starke. “These solutions can be designed and coordinated in such a way that the customers can tailor local energy generation and consumption based on current prices. This is the most efficient way for customers to reduce overall energy costs and enables them to help achieve Germany’s climate targets.” At our booth at Hannover Messe, we used a microgrid table – an interactive trade fair model – to show how power grids change as a result of different players.
This change in the energy systems is based on the new opportunities coming about through intelligent technologies, the growing share of renewable energy sources, and the political objectives of reducing emissions and improving access to energy. Not only industrial companies but also homeowners are becoming “prosumers” who do not just take energy from the grid but can also feed energy into it. One advantage of distributed energy systems (DES) is that they are extremely versatile and can therefore benefit several different applications.
The comprehensive energy consultation service was topped off by expert presentations on new technologies, practical applications, and new trends such as electrification meets automation.
In our blog, you will find further information about TIP in different industries.
Sprawling across the mountainous Andean coast, the El Arrayán Wind Farm provides up to two hundred thousand homes with electricity. Chile’s largest wind farm with a total capacity of 115 MW, the Siemens-managed farm offsets approximately 320 million tons of CO2 emissions per year. The formerly sleepy pace of development in Chile’s wind power market is now teeming with potential. Siemens’ data-driven approach to maximizing turbine efficiency and availability enables farms to use big data to their advantage. This not only unlocks greater production at lower lifecycle costs, it opens the door to new opportunities for growth and competitive sustainability.
Siemens is helping wind energy companies develop innovative business models specifically designed to create additional business value by extracting, refining and ultimately capitalizing on data. Data-driven businesses have been demonstrated to have an output and productivity that is five to six percent higher than similar organizations who are not utilizing data-driven processes. In the wind industry, these boosts could mean the difference of millions in recovered revenue. More importantly, big data empowers wind energy companies to produce secure and viable energy decades into the future. Through condition-based maintenance, more efficient resource deployment, and improved fleet management, Siemens is using big data to help customers transform wind into a profitable asset for a sustainable future—harnessing insight today to generate smarter wind power for tomorrow.
The big data era ushers in the age of the customer. Business models are changing from static and reactive to dynamic and proactive. Siemens condition-based monitoring allows timely maintenance before failure occurs to avoid consequential failure escalation and prepare necessary resources, such as spare parts, cranes, and time slot. At the same time this means increased availability and reduced lifecycle costs. High availability is crucial for the economies of any wind farm. Each time a technician makes a site visit, the turbine must be stopped, thereby reducing availability and reducing output for that time, whether it’s for hours or, in case of major components exchanges, days, or even weeks. When it comes to placing a value on a wind turbine asset, there is a direct relationship between availability and financial performance, with the extent of the influence that availability has on the return on equity for a wind investment often being higher than many realize. In practical terms, any increase in availability represents a pure financial benefit.
“The new business models are moving away from pay as you go. In the future, there will be no scheduled visits. Turbines are checked remotely and then data and customer input decide when service is needed,” says Elizabeth Salerno, Head of Strategy at Siemens Wind Power Service. Operation and maintenance (O&M) costs constitute a sizeable share of the total annual cost of a wind turbine. By implementing a business model that reduces maintenance while simultaneously improving performance, companies can optimize their return on investment.
Siemens provides the foundation for digital transformation that consists of a flexible product and service portfolio and digital solutions that enable customers to adjust operations on a short- and long-term basis. By moving away from regularly scheduled service visits, customers can align maintenance to production schemes. For example, maintenance can be adjusted to periods of low wind, thereby keeping turbines spinning during high winds. On another level, this flexible portfolio positions both Siemens and customers to adapt and respond better to changing market demands.
From vibration diagnostics to the case management application, Siemens uses interconnected digital technology to enhance its own workflows. “The most notable changes will be the massive decreases in costs from automation of physical and cognitive processes. Digitalization will change our business model in ways we have not foreseen yet,” says Allan Larsen, Project Manager at Siemens Wind Power. Already, Siemens is using more smart technologies, such as iPads in the field, to simplify technicians’ daily business. Before, maintenance could be held up by extensive paper traffic. Now every document is accessible online—and much easier to handle for technicians working in tight spaces. What’s more, various teams can document their work, email questions, troubleshoot, and give feedback from wherever they are, quickly, and directly—without losing precious time. By streamlining its own workflows, Siemens is able to offer higher quality services at better prices.
Digital services have to be built upon domain expertise. Without the deep understanding of products and processes that characterizes Siemens’ approach, a purely IT-based focus on service wouldn’t be able to generate the added value that Siemens guarantees. If a customer’s market experiences an upsurge in power prices, he or she has the option of running turbines at maximum output with no downtime. Conversely, if a customer’s turbine needs maintenance, he or she can decide when and how the turbine is serviced, as it fits into the site-specific plan. “The flexibility in how we can deliver data will leapfrog our current models and allow us to partner with our customers in new ways. Digitalization will keep us ahead of the curve in what our customers expect in the future,” adds Larsen.
The opportunity of big data is immeasurable to business growth within the wind industry. By collecting and analyzing nearly every factor of operation, from turbine sensor data to optimal maintenance time to product development, Siemens is creating unprecedented transparency of wind farm management. These advanced analytics can be used in the future to identify emerging markets, new sites and regions, and create plans tailored to individual site conditions and customer objects. Big data will revolutionize the wind industry’s business model.
From the Butendiek Offshore Wind Farm in Germany to the Huay Bong Farm in central Thailand, from the massive turbines in the North American wind corridor to the coastal Santa Isabel wind farm in Puerto Rico, to the Chile’s largest wind farm, El Arrayán, Siemens is transforming the wind industry with the power of big data. Higher outputs, lower costs, and sustainable production define the future of wind energy, and Siemens is harnessing powerful insight today to generate smarter wind power for generations to come.
Find out about how big data helps harness powerful insight today and generate smarter wind power for tomorrow at the AWEA WINDPOWER event.
In the heart of the picturesque Caribbean Sea, 44 Siemens turbines sit on a stretch of farmland along the southern coast of Puerto Rico. The Santa Isabel Wind Farm is the island’s first commercial-scale project. Installed in 2012, the farm was slated to produce 101MW of power. Today, without having to erect a single additional turbine, the facility now injects another 20MW, or an additional 15 percent, of clean energy into Puerto Rico’s power grid.
The boost in Santa Isabel’s output is the result of an aftermarket add-on known as Siemens’ patented Power Curve Upgrade. Using turbine sensor data collected and analyzed at the Remote Diagnostic Center, Siemens’ Research and Development team designed a three-part package enabling turbines to better utilize the wind. These add-on components are strategically placed along the blade length to expand the blade profile near the root, improve the trailing edge flow characteristics, and improve the flow along the blade surface. The upgrade enables the turbine to get more energy out of the same infrastructure.
Operational data senses opportunities
Through data-driven engineering, Siemens creates innovative new products that respond to specific turbine and customer needs. At Santa Isabel, where steady coastal winds push in from the sea, operational data sensed an opportunity for higher turbine yield. Data analysts then modeled a digital twin to calculate the potential increase if the Power Curve upgrade was implemented, and the subsequent virtual boost in the annual energy production (AEP) led to its actual installation at the wind farm in 2014. This is just another way Siemens uses big data to deliver real value, harnessing insight today for smarter wind power tomorrow.
Innovation in wind energy technologies is accelerating at an exponential pace. This is largely due to the sheer amount of big data being collected on a daily basis, affording greater transparency in operations and management. As part of their service portfolio, Siemens brings to the forefront some of the most advanced data-driven products in the industry. For example, Siemens High Wind Ride Through (HWRT) functionality, which is an intelligent solution for both onshore and offshore wind turbines that enables more stable energy production. When the wind speed is higher than 25 meters per second, wind turbines typically shut down to avoid overload. Equipped with the HWRT system, the wind turbine will moderate power output instead of shutting down completely. The wind turbine becomes more grid-compatible, wear and tear is reduced, and overall production increases. At the West Wind Farm in New Zealand, this upgrade was installed on all 62 wind turbines at the site, and has resulted in a marked improvement of two percent in annual energy generation and a reduction in high-wind speed losses of 80 percent.
Similarly, the Siemens extreme cold weather product, called Operation With Ice (OWI), enables stable energy output in even the coldest environments when a shutdown would normally occur. With OWI, power is remotely and intentionally reduced through dynamic speed control and blade pitch strategies to maintain and optimize the turbine’s output. By doing so, OWI maximizes performance by minimizing the downtime due to ice buildup on the blades, thereby increasing availability and overall AEP in extremely cold climate conditions.
Standalone data-driven products
Yet, Siemens understands the impracticality of installing new turbines every time a significant upgrade is available. That is why 80% of all Siemens’ data-driven products are standalone. “Siemens Research and Development team wants to improve products—not sell products,” states Jimm Feldborg, the Head of Product Life Cycle Management. “Product development starts with customer value. It must provide a direct cost benefit or capacity/monetary benefit.”
Still, these benefits can be offered on turbines that are as little as four or five years old, which was the case at the Santa Isabel Wind Farm. Through advanced data analysis, Siemens is able to know when it is best for customers to entertain the idea of implementing modernizations and upgrades. Feldborg explains it through an iceberg analogy: “A one percent production increase offsets a ten percent cost decrease, so Siemens considers both performance gains and cost reductions. But those are just the tip of the iceberg. The biggest value is the enormous opportunities that digitalization affords below the surface.” By installing data-driven upgrades, customers benefit from long-term optimization and lifecycle extension. As previously mentioned, with the right products and services, Siemens turbines can operate smarter and more efficiently.
The bottom line is that no matter the product - Power Curve Upgrade, High Wind Ride Through, or the Operation With Ice de-icing system - Siemens works with customers to do anything they can to customize and optimize the turbines that are already installed in the field. When proven technologies meet industry-leading innovations, the entire energy value chain reaps the rewards. Siemens’ data-driven products ensure efficient and reliable wind turbine service and keep lowering costs. With over 200 gigabytes of new turbine data flooding the Remote Diagnostic Center every day, Siemens will continue to innovate unprecedented solutions for unprecedented challenges, harnessing powerful insight to generate smarter wind power for generations to come.
Find out about how big data helps harness powerful insight today and generate smarter wind power for tomorrow at the AWEA WINDPOWER event.
On the western edge of the Great Plains, strings of turbines stretch across the horizon. The massive blades sit atop aerial towers, taking advantage of the stronger wind at higher altitudes. This is the North American wind corridor, home to some of the best sites for wind farms in the United States. A team of Siemens technicians stands at the base of Turbine 81. Three weeks ago, the experts at the Remote Diagnostic Center were alerted to a heat sensor that needed to be exchanged—a noncritical service order. The repair was entered into a diagnostic Monitoring Operations and Registration System (MORS) case and added to the upcoming scheduled routine maintenance visit. Almost simultaneously, through the MORS system, the farm’s site team received a report outlining the issue, the needed parts, and instructions for the task.
Now in the field, the technicians access the MORS report through an iPad application. They now have access to diagnostics, weather forecasts, data-driven solutions, and even a portal for real-time communication with the Remote Diagnostic Center. The technicians are able to complete the task without compromising the turbine’s availability, but the true work has just begun. Data used to complete this order will not only be used to teach technicians how to better service turbines, but also to teach turbines how to better service themselves - an intelligent approach to harnessing insight today for smarter wind power tomorrow.
Big data for digital insights
At the Remote Diagnostic Center, Siemens uses big data to add digital insight to intuition. Through the application of advanced analytics, turbines learn to operate smarter and more efficiently, and owners benefit from instantaneous performance optimization. The process is simple, but immensely effective. For every turbine event that occurs, whether reactive or proactive, a diagnostic Monitoring Operations and Registration System (MORS) case is recorded. Each case provides advice on remote immediate handing of the turbine by analyzing data from previous cases. It is also used for continuous tuning of diagnostic models for efficient troubleshooting across the global Siemens fleet. In July 2015, the Remote Diagnostic Center reached a milestone of two million MORS cases. This enables analysts and technicians to study what happened and be able to provide advice for trouble shooting even better next time. “If I detect a fault, I can look it up in the database and seek trouble shooting advice,” states Christopher Garlinghouse, a Siemens Service Site Lead. “With knowledge from two million cases, the MORS database is a massive knowledge bank. It is invaluable to our work.”
The MORS case handling database works in conjunction with the 24/7, 365 days a year monitoring completed by the Remote Diagnostic Center. Here, experts monitor turbines 24/7 365 days a year. With 300 million measurements received each week for 24 million parameters, with 3,200 individual values for over 10,000 turbines, Siemens has over 300TB (3 x 1014) of situational data. With a database this diverse, Siemens can resolve 85% of all alarms received within 10 minutes. “Being able to monitor a fleet of more than 10,000 turbines is truly amazing,” says Ulrik Henriksen, Head of Diagnostics at Siemens Wind Power. “We have so many talented employees who strive towards improving the way we operate every day. It is utterly fascinating to see the results of combining wind turbine domain experts with academic computer scientists. Together we create magic.”
Understanding data is key
Indeed, the magic of Siemens stems from their highly skilled personnel. Unlike other competitors who focus solely on data collection, Siemens leverages domain expertise as the Original Equipment Manufacturer to not just fix impending issues, but understand why they are occurring and prevent them from future development. “We have multiple specialist teams to ensure we make the right decisions and offer the best actions. The specialists span a variety of focuses, including turbine alarms, site security, user management, software updates, and SCADA configuration,” adds Henriksen.
The interface of human and technology intelligence is how Siemens gives wind customers a competitive advantage. MORS compiles service tickets, service history, instructional orders, part ordering, and early warnings of maintenance. “The system automatically notifies the analyst, the technician, and the customer. However, a human reviews the notification before everyone receives the notification,” states Henriksen. For example, if turbines are due for a gearbox oil-filter exchange, MORS notifies the site manager. Or, if a turbine stops because of a minor reason, such as a fleeting wind tunnel, the site manager receives an alarm notification through MORS explaining the issue and how it can be solved. Further, MORS enables plant managers to tend to the technical needs of the turbines at all times. “If I didn’t have MORS and the diagnostic team - resetting turbines overnight, resetting turbines on the weekends, and letting technicians know when a turbine fault hits - our availability would be much lower. In that aspect, MORS is really invaluable to the business and to keeping turbines up and running as long as can,” adds Garlinghouse.
The impact of Siemens remote monitoring and diagnostics will only be amplified as more data is collected and more insight derived. By focusing on smart data, instead of just big data, Siemens can “smartly” combine product know-how and process expertise with data analytics to help customers improve operational efficiency. And, going one step further than leveraging digital technologies to improve turbine performance, Siemens is using big data to develop new software and hardware products and construct business models to revolutionize the role of digitalization within the wind industry. With Siemens, wind turbines will operate smarter over longer periods of time to deliver cleaner, more efficient power for generations to come.
Find out about how big data helps harness powerful insight today and generate smarter wind power for tomorrow at the AWEA WINDPOWER event.
Kristina Dotzauer 28/03/2017
Along the rolling hillside of the Korat Province in Thailand, the Huay Bong wind farm is the first and largest of its kind in Southern Asia, boasting 90 SWT 2.3-101 Siemens turbines—the ideal turbine for moderate wind conditions. This is important because Thailand’s overall wind speed is quite low, with an average speed of 6.4 meters per second. Yet, Siemens, who manufactured, installed, and serviced the Huay Bong turbines, is able to wring 1GWh of annual power from the farm—producing a significant amount of energy from such a conservative site. The question then becomes, how is Siemens able to generate consistent power with less wind? And the answer is futuristic—relatively speaking.
There are actually two Huay Bong wind farms, except they are separated by time and space. Whereas one farm physically operates in real-time, the other operates digitally for days, weeks, months, even years, into the future. This is known as the digital twin. By constantly collecting big data - weather, component information, service reports and performance of similar models in the Siemens fleet - a predictive model is built and data turned into actionable insights. With the digital twin, the need to service turbines can be determined in advance. This predictive capability reduces unplanned maintenance, which cuts down costs; more importantly, however, it helps owners avoid extended periods of downtime, often adding weeks of productive operation that would have been lost. At the same time, an accurate diagnostic report tells the service crew exactly what to expect.
Feeding the digital twin
In the future, a wind farm’s success may hinge on how skillfully its digital twin has been designed, how successfully operational data can be fed into it, and how well the resulting data can forecast its future. At Huay Bong, data analysis and modeling maximized site-wide availability by predicting and preventing maintenance - just another example of how Siemens harnesses powerful insight today to generate smarter wind power tomorrow.
The first company to install condition-based monitoring systems in their turbines as standard equipment, Siemens has been collecting data since 1998 and maintains the industry’s largest amount of historical data - a database that grows daily with data collection from over 10,000 turbines worldwide. Inside each turbine, there are more than 300 sensors that continuously transmit data to the Remote Diagnostic Center in Brande, Denmark. Here, 100 analytic experts turn raw data into insights, using advanced data-processing methods and decades of experience to compile all that data, analyze it with intelligent models, and determine the best approach to service and maintenance. Based on historical as well as operational data, Siemens experts can tailor O&M for maximum efficiency and customer benefit.
Unique fingerprints for each turbine
One of the multiple proactive aspects is vibration diagnostics, where each turbine’s unique “vibration fingerprint” is compared with its actual vibration patterns to detect irregularities that can indicate the potential risk for fast- or slow-developing damage. More than 34,000 data analyses are currently performed each year that can predict more than 98 percent of all gear-tooth cracks as well as damage to the gearbox, generator, or main bearings, which are among the most prevalent serious component failures of a wind turbine that can lead to weeks of costly downtime.
The Remote Diagnostic Center also monitors turbine software configurations closely. Siemens’ unique position as the Original Equipment Manufacturer, extends a deep domain know-how that creates the right tools to deliver real added value. The newest analysis platform, Pythia, is inspired by the concept of the Big Data paradigm and has access to around 60 terabytes of vibrational data. Pythia allows Siemens experts to aggregate all of that data and apply a wide range of state-of-the-art machine learning and processing algorithms, which enables early and robust detection of failure modes. Any major alarms set off an immediate response, with notifications to both the customer and the site crew.
Recommendations and comments are fed into regular reports, which are accessible to customers through the Wind Dialogue customer portal, offering a complete picture of how Siemens evaluates the current state of the turbine in term of vibration irregularities. For fast-developing damage, such as a cracked gearwheel, which can cause serious harm within days, data and analytics help determine exactly when damage occurs so service technicians will have a clear picture of what needs to be done before arriving on site. This saves a tremendous amount of time and costs. In contrast, slow-developing damage leaves enough time to make a risk assessment on when the exchange of the defective part will become necessary. Thus, a turbine standstill while preparing for the exchange of the part can be prevented; service work may be postponed until the low-wind season. “Predictive analytics and diagnostics is where Siemens has a competitive advantage,” says Ulrik Henriksen, Head of Diagnostics at Siemens Wind Power. “We can detect a major failure four to six weeks out, saving downtime and parts. The advantage is in the savings and the planning. Parts can be ordered well in advance of the failure, so everything is ready.”
With increasing investments in wind farm development, preventive maintenance is vital in ensuring the reliability and cost-effectiveness of this energy business. A catastrophic failure of the turbine generator would lead to a complete shut down of the turbine for several days, or even weeks in high wind seasons, resulting in expensive repairs and lost revenue. Achieving maximum availability helps a company wring as much power - and dollars - as possible from its wind power assets.
The key to optimizing wind power lies in the future. At the Huay Bong wind farm, the next prediction has already been made: the government aims to use the wind farm to generate 1,200MW of power within eight years. And the solution quickly followed: Siemens will provide service and maintenance for an additional 13 years - the first long-term wind service extension in Thailand. The scale of the wind industry is now at the point where predictive maintenance is a reality, and Siemens is opening up new possibilities in the way wind farms are managed to deliver cleaner, more efficient power for generations to come.
Kristina Dotzauer 27/03/2017
Thirty-two kilometers off the coast of Sylt, Germany’s northern most island, the Butendiek Offshore Wind Farm operates in solitude. A site swept with extreme weather conditions, 80 towering turbines stand like sentinels over the rough white-cap waters of the North Sea. Yet, they are never alone. For inside each turbine, a dynamic team of Siemens technicians, digital scientists, engineers and business analysts are constantly connected, unlocking the opportunities of big data to harness powerful insight today and generate smarter wind power tomorrow.
A pioneer of wind energy for over 30 years, Siemens was the first company in the world to install data sensors in its offshore and onshore wind turbines as standard procedure. These sensors today deliver more than 200 gigabytes of data per day to Siemens’ state-of-the-art remote diagnostic center in Brande, Denmark, where advanced analytics and around-the-clock human monitoring ensure optimal performance of over 10,000 turbines worldwide. This means that in the age of digitalization, where data is the first-class ticket to action, Siemens provides a unique two-pronged advantage of combining the industry’s largest archive of operational data with their OEM domain know-how and experienced personnel.
Big data, big ideas
In today’s digital world, every action translates into a data footprint, fueling a vast expansion of metadata ripe for mining the meanings within. In fact, the digital universe is approaching the physical universe in its size and complexity. According to data storage vendor EMC, by 2020 there will be nearly as many digital bits in existence as there are stars in the universe, with the data we create and copy annually reaching 44 zettabytes, or 44 trillion gigabytes. And the wind industry is no different - perhaps even a hyper-example - because the sector’s stability and longevity depends on continuous digitalization.
Looking forward, the wind industry must drive down the cost of wind power while boosting efficiency. The digital transformation promises to do just that; however, the path to sustainable energy cannot be steered by technology alone. Data, on its own, is practically useless. It’s just a huge set of numbers with no context. Its potential is only realized when the right people convert it into value that matters. This is how Siemens is able to lower production costs and ramp up output of overall wind energy.
The experts at the Brande Remote Diagnostic Center convert raw data into smart data. Through the use of advanced analytics, Siemens’ experts are able to monitor turbine performance, fleet operations, weather conditions, and much more - and turn this information into meaningful insights. Big data is a great opportunity for both customers and for Siemens. With so much expertise in one place, Siemens is able to constantly redefine their service and produce bold new ways to secure their customer investments.
Whereas other companies focus on a purely IT-approach, Siemens uses the strength of its personnel and OEM experience to not just “see” what is happening, but understand why it is happening. This enables Siemens to predict and prevent unscheduled downtime, transition wind farms to condition-based monitoring service plans, and substantially extend the lifecycle of each turbine. These smart, forward-thinking applications are optimizing renewable energy and yielding hundreds of thousands of dollars in cost-savings.
Making wind energy more affordable
But the impacts don’t stop at the grid. Siemens is using smart data to develop new products, both digital and mechanical, to enhance wind turbine technology. This in turn will make wind energy more affordable, reaching wider economic markets and stabilizing the cost of power generation. Siemens is also using smart data to actualize visions, set strategies and deploy prescriptive practices to create revolutionary business models that capitalize on unforeseen ventures. Jobs will be created, entirely new fields will emerge, and companies will cultivate interconnected partnerships.
Yet, this is only the tip of the iceberg. The massive potential of digitalization and big data lies below the surface, where Siemens experts are harnessing more and more data everyday. From the turbine sensors in the North Sea to the analysts at the Remote Diagnostic Center to the millions of homes powered by wind energy, big data is transforming how renewable energy is produced and propagated. And Siemens is leading this journey of digitalization. In the articles to follow, you will learn how Siemens is utilizing big data to transform how the wind industry operates, optimizes, and unlock new opportunities - harnessing powerful insight today to generate smarter wind power for tomorrow.