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Avangrid Renewables is a subsidiary of Avangrid, Inc., and part of the Spain-based Iberdola Group, the largest wind energy company in the world. Avangrid collects a wide variety of data from many different sources. In the past, it faced challenges in gaining useful insight from these data. Particularly problematic was determining and documenting lost generation across its wind turbine fleet time due to voluntary generation curtailment to meet contractual obligations. Inability to do so can lead to lost revenue.

Avangrid Renewables’ Klondike wind farm.

Avangrid Renewables owns and operates nearly 60 plants in the US, with more than 6,000 MW of owned and controlled renewable generation assets, including 3,000 wind turbines. It also has 636 MW of combined cycle gas turbine generation, 50 MW of solar generation, plus 55 MW of controlled biomass generation.

The company collects a wide variety of time series and other data from its wind turbines and other operational assets, plus weather systems, pricing systems, market data systems, etc., and responds to signals from the local Independent System Operator (ISO) systems. Data sources include the OSIsoft PI System, SAP, SCADA systems, and SQL databases. The company wanted to investigate the data that was already in the OSIsoft system so it could better visualize and understand the data. The company was using various analytic tools that allowed it to analyze the data, but found these to be difficult and time-consuming to use.

To alleviate the situation, Avangrid Renewables deployed data investigation and discovery technology from Seeq, which helps industrial organizations gain business value from their data by integrating data from existing databases, historians, and analytics without tampering with the systems of record.

Curtailment Can Mean Losses

The red area shows previously unaccounted-for lost generation.

In the US, wind generation companies must curtail wind power generation at certain times, both to balance supply and demand under contractual obligations with the local ISO, and to help ensure safe operation.

Renewables companies can be compensated for lost generation if they can accurately calculate, document, and report the monetary value of what they would have put on the grid during these curtailment periods. According to Brandon Lake, former Senior Business Systems Analyst at Avangrid Renewables, “Prior to implementing the new technology, the company was not able to report the losses accurately, and was losing money.”

It can be challenging to track wind turbines’ losses because of the time it takes to return to full speed. The company needed to dig into the data to determine how much power it was not allowed to produce (calculating in the wind speeds during those time periods), and the economic impact of the curtailment. Under its contractual agreement, the ISO would only compensate Avangrid Renewables for its curtailment losses if it could produce sufficient proof of the impact. “We knew we were losing money, but to determine the actual impact required investigating years of turbine data,” said Lake. This was a time-consuming and difficult task.

Previously, the company did not investigate the ramp-down time cost or other areas because of the time and effort required to do this in Excel, and the need for expert consultants. According to Lake, using the Seeq tool enabled the company to further examine the cost of shutdown time by isolating the events, adding analytics, and determining what was happening in hours, versus days or weeks.

The company was able to visualize the information on a screen, determine the curtailment time, add pricing and other potential power set points, and combine the information to determine “what if” differential power scenarios between potential and actual to determine losses. Once Avangrid Renewables isolated the time periods, Seeq was able to sum the data to identify the revenue to claim.

While these losses don’t seem that significant when looking at just a single turbine over the course of a single day, they added up to real dollars when multiplied across the company’s entire fleet of wind turbines over years of operation. By exporting the data from Seeq to Excel, Avangrid Renewables was able to add price information and determine the cost to the company, which estimated savings from $30,000 to as much as $100,000 per year, depending upon the ISO contract, wind curtailment, and wind availability.

Seeq enables several types of searches on time series data; in this case, the shape or pattern of the signal has been defined as the search criterion, and instances where that pattern occurs are identified by the solid horizontal lines at the top of the trend viewer, known as “capsules.” These capsules, individually or as a group, are the basis for managing and interacting with time periods of interest in the data.

The technology can isolate events at multiple windfarms, helping transform data into intelligence that allows Avangrid Renewables to find important correlations.

Benefits of the Technology

Finding patterns in the data and identifying capsules.

According to Lake, it only took 45 minutes to learn how to apply this new technology to solve the problem. This included accessing more than 250,000 tags to start getting the answers and insights he was looking for. This represents a significant improvement over other solutions the company evaluated.

Now that Avangrid Renewables can accurately calculate the dollar value of what it would have put on the grid if it did not have to curtail power to recoup its lost revenue, it is looking to expand the tool with additional factors, as well as in other potentially revenue-producing areas using other attributes.

Some key benefits that Avangrid Renewables received from using the Seeq technology include:

  • The ability to find key points in the data and examine large amounts of data from multiple sources.
  • The ability to isolate incidents in the data that would have taken exponentially longer using Excel alone or other tools.
  • Transforming industrial process data into useful information and actionable intelligence.
  • Once an event has been isolated, the user can expand the time frame and quickly adjust the queries for other wind farms.
  • Significantly reduced the time required to investigate and gain the needed insights and analysis (from months or even years, to hours)
  • Accelerating time to discovery.

The Seeq solution for Avangrid Renewables did not require the specific expertise of data scientists to implement and use to gain actionable insights from Big Data. The software enabled process engineers and control operations personnel to investigate and discover insights on data that could not be done in the past.

This article was written by Janice Abel, Principal Consultant at ARC Advisory Group, Dedham, MA, and was reprinted from ARC Advisory Group Insight (here )

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