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Case Study: Wind Turbine Farm, USA

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DataHub Scripting solution calms the conflict of bats vs. blades

Required by law to protect a rare species of bat, a major wind power generation company finds a solution using the Cogent DataHub®.

A rapid expansion of wind farms across the Eastern and Central United States has been checked in the past couple of years due to growing concerns for wildlife. An endangered bat species lives in that area, and is protected by law. Fears that the whirring blades of wind turbines could be harmful to this species of bat were sufficient to halt construction of a wind farm in West Virginia in 2009, and the discovery of a dead bat near a wind turbine in Pennsylvania in 2011 caused the power company to shut down the whole 35-turbine system for several weeks.

Although wind turbines are known to cause a few fatalities among common tree-dwelling bats, the endangered bat was thought to be largely safe, as it lives in caves, hibernates for more than half the year, and is seldom found in the vicinity of wind turbines. However, in the fall these bats migrate from their feeding grounds to their home caves for the winter. During this time, the chances of them passing through a wind farm are greatly increased.

In March a few years ago a major power company in the USA was informed by the US Fish & Wildlife Service that a number of turbines on the bat migration routes would need to be shut down while the bats are migrating. This caused quite a stir. The migration period for the bats is two months long―from mid-August to mid-October. Shutting down the whole system for that length of time would be very costly, not to mention the loss of clean energy which would need to be replaced by fossil fuels.

To maximize uptime, the company gained permission to let the turbines run during the times that the bats were not flying – all daylight hours, and in the night time when air temperatures drop below a specific temperature setpoint, or when the wind is fairly strong. The challenge was to implement a complete solution. A single bat fatality could mean full shut-down, legal penalties, and even lawsuits.

Top management at the company immediately took action, contacting the wind turbine manufacturer, who also provides the control systems. After several months of emails and meetings, it became apparent that the manufacturer would not have anything ready in time for the mid-August deadline.

“With three weeks to go, they told us there was no solution in sight,” said the SCADA engineer responsible for the project, “and we would need to go to manual operation, and reconfigure the cut-in speed on every turbine, twice a day.”

Most wind turbines are designed to “cut in”, or start turning to produce energy, when the wind is blowing at a certain speed. For these turbines, the normal cut-in speed is 3.5 meters per second. As the bats are active in low to moderate wind speeds, the company would need to raise that to 7 meters per second each night, and then drop it back down to 3.5 the following morning. This would mean manually reconfiguring the PLCs for 100 turbines, twice a day.

A better way

“I thought there must be a better way,” the project manager continued. “We’d been using the DataHub for years, and knew the potential was there to leverage this asset further. I gave Skkynet a call, and told them what we were up against. They delivered by helping us to develop a very efficient program using the native scripting language of the DataHub. The code ran right on the SCADA interface of the OEM system – so it’s as reliable as you can get.”

“Working together with Skkynet, we came up with a DataHub script that doesn’t change the cut-in speed of the turbines at all. We just blocked them from starting. The script tells each turbine to stay off, and keeps measuring wind speed. When it picks up to 7 meters per second, the script releases the turbine to start, and it ramps right up to the operating state. At the end of the day, we have a complete audit trail of every turbine controlled, including a history of critical parameters, such as rotational and wind speeds, and energy curtailed.”

“The script also has a temperature component. On cool nights in September and October, when the temperature drops below the dew point, it uses the same algorithm for starting and stopping the wind turbines.”

By the first week of August a test script was written, and after a few days of testing and last-minute tweaks, it was ready. The system went live on August 15th, and is meeting all expectations. Every night, whenever the air temperature is above the setpoint and the wind speed falls below 7 meters per second, the wind turbines stop, allowing the endangered bats to return safely to their caves for a long winter hibernation.

“I call the DataHub the Canadian Swiss Army Knife,” said the project manager. “We are able to accomplish a host of required functions with a single product solution. The ability to provide sophisticated logic and control algorithms with the built-in functionality of this product is the game changer. Being able to securely deliver real-time data between a site and the control center system allows the dispatch team to monitor the control process and maximize the production of clean, renewable, energy sources. Talk about a smart grid – who would have thought we’d be doing this type of thing in real time?”

Case Study: University of California, Berkeley, USA

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DataHub software integrates data for distributed control of unmanned aerial vehicles

For the past several years, students and faculty at the Vehicle Dynamics Lab (VDL) of the University of California, Berkeley, have been developing a system of coordinated distributed control, communications, and vision-based control among a group of several unmanned aircraft. A single user can control the fleet of aircraft, and command it to carry out complex missions such as patrolling a border, following a highway, or visiting a specified location. Each airplane carries a video camera and an on-board computer, and communicates with the ground station and the other aircraft in the formation. The control algorithms are so sophisticated that the fleet can carry out certain missions completely autonomously—without any operator intervention.

The control system for each aircraft runs on a PC 104 computer with a QNX6 operating system. Control is divided into three kinds of processes: communication, image processing, and task control. All of these processes interact through the DataHub software running in QNX. Each DataHub® instance is a memory-resident, real-time database that allows multiple processes to share data on a publish-subscribe basis. For this application, each process writes its data to the DataHub instance, and subscribes to the data of each other process on a read-only basis. In this way, each process gains access to the data it needs from the other processes, while avoiding problems associated with multi-processing data management.

For example, the communication software comprises three separate processes: The Piccolo process controls the aircraft, the Payload process communicates with users on the ground, and the Orinoco process handles communications with the other aircraft. Needless to say, each of these three programs needs information from the other two, as well as from the video and task control packages. All of this data is transferred seamlessly through the DataHub instance.

“DataHub software has contributed a great deal to our system integration,” said Brandon Basso, one of the VDL team members. “Its ability to restrict write privileges to each shared variable of the owner processes avoids many of the difficulties associated with multi-process management.”

For task control, there are two primary software packages: Waypoint controls visits to specified locations, while Orbit handles the orbiting “patrol” of a group of locations. These processes are monitored by a third, supervisory process called Switchboard. In addition to coordinating these processes, decisions must be made by the different aircraft as to which plane will take on which task. The complex calculations needed for this decentralized task allocation are mediated through the DataHub instance.

Waypoint and Orbit use input from the vision control and vision process. Prior to takeoff, certain algorithms are applied to previously recorded videos, to create a visual profile of the area, which is maintained by the vision control. In the air, this data must be compared to what the plane is currently flying over. A camera on the wing of the plane feeds data to the vision process, which analyzes the content and generates meaningful information about objects on the ground, such as waypoints on a river or road. This live content, along with the stored visual profile in the vision control, is fed through the DataHub software to Waypoint and Orbit.

According to the paper, A Modular Software Infrastructure for Distributed Control of Collaborating UAVs, published by the University of California Berkeley which describes it in detail, this project marks “a major milestone in UAV cooperation: decentralized task allocation for a dynamically changing mission, via onboard computation and direct aircraft-to-aircraft communication.” Skkynet is pleased that DataHub technology has played an important role in the success of this endeavour.

Case Study: KuibyshevAzot Chemical Plant, Russia

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Russian chemicals giant KuibyshevAzot uses DataHub software to link Yokogawa DCS to proprietary system in QNX

Deep in the heart of Russia, on the banks of the Volga River, stands one of the country’s most successful chemical plants: KuibyshevAzot. Founded in 1966, the company produces over 1.5 million tons of chemicals per year, with sales volumes averaging around ½ billion dollars. Through constant technology upgrades, the plant maintains the highest efficiency levels in all of Russia for ammonia production—and higher than average efficiency levels for nitrogen fertilizer production.

One of the goals at KuibyshevAzot is to update and re-equip the plant to optimize the consumption of raw materials and energy. To meet this goal they recently installed a Yokogawa CENTUM CS3000 Distributed Control System to control their ammonia production process. They were satisfied with the performance of this state-of-the-art system, but there was one question – how to interface with their Plant Information System Server?

The Plant Information System Server is KuibyshevAzot’s proprietary system that collects live process data, calculates technical and economic performance indicators, and generates reports—processing more than 900 variables simultaneously in real time. Due to its mission-critical status, the system runs on the QNX real-time operating system. Getting the data from the Yokogawa control system into the Plant Information System was vital to the overall success of the project.

To create the data link, KuibyshevAzot chose the Windows and QNX versions of DataHub® software from Cogent Real-Time Systems.

Each of these DataHub instances is an off-the-shelf middleware program that collects and distributes real-time data. The DataHub instance that runs in Windows can connect to any OPC server, such as the Yokogawa ExaOPC Server used in the project. On the QNX side, the QNX version of DataHub software was connected to the Plant Information System server. Once connected to their respective systems, the two DataHub instances establish a TCP tunnel/mirroring connection across the network to create a Windows – QNX real-time data link.

“This connection has saved us a lot of money in development time,” said a company spokesperson. “The major requirement was to continue using our existing information system. The deployment of DataHub software saved us time and money because there was no need to purchase, develop, or configure a new information system. The update process was seamless. We kept our existing information display consoles and report forms. All we had to do was add more report forms and update the information displays.”

“KuibyshevAzot needed something robust, something they could trust with their vital data,” said Leonid Agafanov, Managing Director of SWD Software, Cogent’s local distributor who was involved in the project. “Linking the DataHub software in QNX to DataHub software in Windows combined the strengths of both systems.”

Case Study: Renewable Wind Power, Turkey

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Using the WebView application to monitor wind farm data

The country of Turkey is emerging as a growing economic and industrial power, with an estimated 6% annual increase in demand for electricity over the next 20 years, according to the Turkish Electricity Transmission Company. Investments in the energy sector will be well above 100 billion USD during that same period. Meriting special attention is wind power. Turkey has the highest growth rate of installed systems worldwide, leaping from 1,700 MW to 20,000 MW in just over a decade.

Riding this wave, a prominent electrical power production company in Istanbul invested heavily in renewable and alternative sources for power generation. They erected two new wind farms, with a third one and a thermal energy power plant on the way. As the construction phase neared completion, the company began looking at ways to monitor their wind farms and display the live data in their central Istanbul office, using a single web-based application.

“We needed a way to quickly view the energy production status in each of our two wind farms,” said the Director of Operations. “We also wanted to see a summary of the total count of turbines in operation, in maintenance, and in failure status, along with detailed data from each turbine.”

A challenge for the data integration was that each of the two remote wind farms is controlled by a SCADA system that cannot be connected directly to the Internet. NSC Teknoloji, Skkynet’s partner for the Turkish market, proposed a solution using the DataHub® WebView™ application.

At each remote location NSC Teknoloji installed DataHub® software and connected it to the company’s SCADA system. Then they connected both of those sites to a WebView instance running at their central office. Once the data connection was made, NSC staff created special web pages to display summary and detailed data of the system and the wind turbines.

“The system is performing very well, transmitting more than 30,000 data points over the Internet, with 1-second refresh time,” said Mr. Ibrahim Serhan Arslan, Director of NSC Teknoloji. “It is incredible that we can carry this huge amount of data over the tightly restricted bandwidth of our Internet connection.”

nsc-wind-system

The HMI screens and controls were created easily through the WebView browser interface, with no programming. From his office, the Director of Operations can now view online megawatt production, wind speeds, temperatures, and total turbine count and operational status for each wind farm, all on a single page.

“In the near future we will add the third wind farm data to the system,” said Mr. Arslan. “Before they were only able to access this data for each wind farm one by one using the SCADA vendor’s web connect tool, and they had no way to view data from the whole system in one screen. Now they have a summary screen for all power plants, and the details for each plant are just one click away.”

“This is very efficient way to review the status of our wind farms,” said the Director of Operations. “We want to thank NSC Teknoloji and Skkynet for making this system work for us.”

Case Study: Citect (Schneider Electric), USA

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Citect optimizes OPC-based system using the DataHub

A major battery manufacturing plant in the United States was recently faced with an interesting data integration challenge. Management needed access to data coming from a large number of different processes. Over 220 OPC-enabled field devices across the plant had to be connected to a single Citect MES system. The many OPC servers used for these connections are unique in that their data set is very dynamic. From one minute to the next any of the 220 devices may be present or absent in the data set.

citect-logo “Our challenge was to provide data from our dynamically changing OPC servers to a Citect system that is designed to work with a fixed data set,” said the company project leader. They decided to bring in a team from Citect to come up with a solution.

Citect, of Schneider Electric, is well known in the industrial process control world for their line of automation and control software solutions, particularly their MES systems. Dan Reynolds, the team leader for Citect, had heard about the DataHub® through his support department, and thought it might work. They configured the DataHub for OPC tunneling, to communicate across the network without the hassles of DCOM. And, thanks to the DataHub’s unique approach to OPC tunnelling, Dan found that it also solved the problem of providing a fixed data set.

citect-battery-manufacturing-system

“The DataHub mirrors data across the tunnel,” said Dan, “so the Citect system sees a constant data set. When a device goes offline, the tag remains in the DataHub. Just the quality changes from ‘Good’ to ‘Not Connected’.” Confident in their approach, the Citect team moved the testing from their location to the battery plant. But they soon found themselves faced with another challenge.

The production system is designed so that a field device can add or remove OPC items at any time. So, not only the OPC servers, but individual tags can suddenly appear or disappear from the system. When a new tag comes online, the server updates its tag count, but doesn’t say that a new value is available, because the OPC specification doesn’t require a server to say when a new point is created. This looked like a show-stopper for the configuration team. They knew that there is no OPC product on the market that can deal with that kind of behavior. Continually rereading the data set was not possible, because new points may be added during the read. So Dan got in touch with Cogent (a subsidiary of Skkynet), and working together they came up with a plan.

The solution was two-fold. First, the device behavior was modified to compact the tag add/delete cycle to a limited time. Then Cogent wrote a DataHub script that monitors a few OPC server tags, and when these tags change, a time-delayed function in the script re-reads the server’s data set. The scripted time delay allows for all the new points to be added before the data set is reread, and the DataHub thus discovers all of the new data as soon as it all becomes available.

“We are pleased with the performance of the DataHub for this application,” said Dan Reynolds. “There is no way we could have done this project with any other OPC tunneling product, or combination of products.”

“The Skkynet software has become an integral part of our MES solution,” said the project leader. “Without the DataHub, we would not be getting reliable data. If we hadn’t had it, our MES integration project would probably have come to a halt.”

System Integrators Prepare for Smart Manufacturing

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Luigi De Bernardini, CEO at Autoware, in Vicenza, Italy, sees that system integrators are going to need to adapt quickly to the idea of software-as-a-service in manufacturing.  In a recent guest blog in AutomationWorld, he says, “System integrators will have to be ready to change their business model, at least in part, by offering subscription services …”

According to De Barnardini, assuming that every company will sooner or later  incorporate the Industrial IoT, cloud computing, analytics and Big Data into its evolving smart manufacturing formula, system integrators need to wake up right away, and smell the coffee.

He offers two insights:

1. The move from system and software ownership towards software-as-a-service makes good economic sense.

2. Although adopting software-as-a-service reduces the complexity of that specific service, there is still a need for system integrators to bring together the different solutions into a coherent whole.

The upshot, he says, is that system integrators need to support the traditional business model, while at the same time offering services to customers moving towards the Industrial IoT.

Interestingly, this is the same approach that Skkynet takes–with the Cogent DataHub supporting traditional, in-plant data connectivity and integration, and yet also connecting seamlessly to SkkyHub and the ETK for secure, remote data access and other Industrial IoT applications.