Have you ever wondered why the wind energy sector is lagging behind in its quest to achieve net-zero? Digitalisation of the wind energy sector is without question one of the biggest factors.
Data has never been more important than it is today, yet there is still no generalised technical data vocabulary to act as a collaboration and communication interoperability framework within the wind or wider electricity industry. Such a wind energy framework would make bridging the gap between third parties and the energy sector much easier by making data more reliable and easier to manipulate.
What’s more, a mandatory wind data standard would simplify data sharing and collaboration, making it possible for the energy sector to accelerate innovative practices and minimise costs. There are several data groups and taxonomies currently in place. However, these documents lack depth and fail to keep up with the wind energy sector’s rapid growth.
If we’ve piqued your interest at all, then we’d strongly urge you to continue reading this article to learn more!
Current Wind Energy & Data Groups/Taxonomies Unsuitable for Digitalisation
This section contains information regarding the data groups and taxonomies:
Table reference: “Wind Energy Digitalisation towards 2030″
Current wind energy data groups and taxonomies ill-suited to achieving digitalisation of the wind energy sector or wider electricity industry.
RDS-PP to Clarify Component Status in Wind Systems
The Reference Designation System for Power Plants (RDS-PP) provides a method for applying designated codes to power plant systems based on international best practice principles and standards. Hence RDS-PP is the recommended designation language active within the wind industry today, with most if not all wind farms using RDS-PP on some level irrespective of where they are around the world.
Hierarchies are fundamental within wind farms because each level represents a separate object. RDS-PP data moves across many different levels ranging from groups of wind farms right down to circuit breakers in a control panel. Therefore, creating a hierarchy relating to equipment importance and status imperative – a more structured approach streamlines the design and construction of wind farms.
Construction, operations, and maintenance rely heavily on RDS-PP because it provides a standardised blueprint of the entire wind farm system. Every component within the wind farm’s system possesses an identification code depending on its stage within the lifecycle. Many professionals will work with a component from planning to maintenance during its lifetime. Therefore, it’s necessary to have a clear designation framework to avoid confusion over a component’s status. Thus, simplifying processes such as communicating with third parties, improving business intelligence, and making it easier to integrate new workers.
GADS Aids in Wind Data Collection and Reporting
The General Availability Data System (GADS) is a system of reporting developed in 1982 by the NERC to act as something of a manual to complement data collection within energy assets. Energy analysts use GADS as a benchmark to gauge their data against, and the approach can prove invaluable when researching power outages. The taxonomy provides standardised definitions for the analysis of operations and maintenance actions, wind turbine availability and reliability standards.
Energy systems use GADs to provide medium-level equipment data while operating data and value measurements are also available more generally. There are three different types of data GADS collects. Firstly, design data relates to equipment and MW ratings of components. Next, performance data relates to the amount of energy produced. Fuel units are an excellent example of a performance-based metric. The final source of GADS data stems from actual events such as equipment failures and planned maintenance.
What makes GADS so valuable is its ability to provide reporting instructions about bulk power outages. This information is in the GADS Data Reporting Instructions (DRI) manual. GADS is, therefore, a key player in ensuring the collection and analysis of reliable outage data, thus simplifying the prevention and treatment of outages.
ReliaWind's Contribution to Wind Energy and Data Standardisation/Regulation
ReliaWind is a taxonomy used to gain actionable insights into energy sector equipment resulting from an investigation into the reliability of wind turbines and their recommended measuring methods from 2008 until 2011. The ReliaWind consortium’s primary objective was to make wind turbines more reliable by improving the components and sub-components of onshore and offshore turbines, thus lowering O&M costs while increasing wind turbine availability.
Therefore, ReliaWind was an important development in wind energy because it emphasises measuring and understanding failure rates and downtime data in wind turbines at the system right down to component level. A direct result of the ReliaWind project was an increased understanding of failure within wind turbines. For example, six critical WT sub-components along with five failure modes relevant to each.
A logical architecture was created using the findings to diagnose equipment failures within WT systems. The findings presented a programme to the IEC that mapped the standardisation of wind energy reliability information. ReliaWind has helped acquire funding for R&D and encouraged works to standardise WTs in Europe to this day.
An Unorthodox Solution to Wind Energy and Data: ISO 14224
ISO 14224 Petroleum, petrochemical, and natural gas industries – Collection and exchange of reliability and maintenance data for equipment is an international standard. ISO 14224 provides a detailed overview of reliability and maintenance data structure during the lifecycle of renewable energy assets.
This standard guides how best to extract meaningful insights from data regarding equipment failure. Detailed advice on collecting reliable data is contained alongside information on data categorisation during storage and understanding the role of human error by carefully defining the cause of failures.
This international standard ensures that data collection is of the utmost integrity. What’s more, it also helps to ensure data infrastructures are maintainable. Hence by collecting data using this ISO format, there is a clearly defined approach to data activities. Having a uniform method of information organisation provides data-driven decision-making potential with minimal concern regarding the accuracy of insights. Therefore, ISO 14224 ensures that the appropriate care and planning has gone into data operations and design, which translates to lower costs and safer working conditions.
Zustands-Ereignis-Ursachen-Schlüsse (ZEUS) represents a wind energy data standard focussing on providing wind turbine failure and fault data. ZEUS provides a standardised means of identifying and diagnosing status conditions, events, and causes. Fördergesellschaft Windenergie und andere Dezentrale Energien (FGW) first mentioned ZEUS within the technical guide, TR7. ZEUS provides readers with a description of wind turbines and their components using blocks.
These blocks are not exhaustive but contain a great deal of information regarding the many different stages within a wind turbine’s life cycle. Wind entries are taken using ZEUS with high accuracy and contain precise metrics related to wind activity. Hence, it’s unsurprising that maintenance and detection data is also a strong point within the ZEUS system. ZEUS uses blocks to ask questions relating to a wind turbine’s status. The answers to these questions are within sub-blocks.
This taxonomy is important for several reasons. It, for one, highlights the considerable difference between the need for a repair and a replacement. What’s more, it’s easier to identify a WT’s state courtesy of ZEUS’ specific description of all important turbine states along with the appropriate course of maintenance. This information lends itself to preventing WT failure, lowering O&M costs, and improving overall business effectiveness.
IEC 61400-25 Aids Wind Energy Data Information Exchange
IEC 61400-25 is an international standard used by energy companies as guidance during information exchange regarding the monitoring and control of wind power plants. Wind power plants contain a great deal of information; hence the correct procedure must be followed during configuration. Thus, a logical information hierarchy is of the utmost importance, as outlined in the document.
Information is detailed and assists when pulling data relating to components such as, for example, the rotor. Wind turbines can be contacted by SCADA systems using multiple vendors. SCADA applications can be configured using the standardised self-description of components retrievable using an online device or an XML file. A key thing to remember about this document is that one of its primary aims is to enable components to communicate with other components irrespective of the vendor or geography. Hence this standard encourages wind farms to place data within object-oriented data structures.
Overall, this standard provides a uniform approach to communication that makes interacting with third parties, outsourcing, and integrating co-workers much easier. Wind power plants rely on protocols and models within the document to streamline communications, thus improving interoperability. Therefore, IEC 61400-25 simplifies exchanging information between a wind farm and SCADA systems.
This information model considers not only production but also time-based availability indicators. Availability management becomes more accessible due to key performance indicators (KPIs) used to monitor and understand service performance in wind energy assets. Therefore, end users can tailor availability metrics to make and organise standardised calculations that suit their needs.
Information categories state in no uncertain terms how operations are to be labelled and segmented based on this IEC guide. This model can be used to process information and decide which information category to prioritise when more than one category is applicable. Information standards are available to judge data once it enters and exits the system. Meaning production values and timing is applied to the correct information category.
Information contained within IEC 61400-26 applies to data originating in wind turbine generation systems. Therefore, this document is applicable irrespective of whether there is a single turbine or multiple wind power stations, thus making it highly flexible.
Wind Energy & Data Within Preventative and Prescriptive Software
SCADA records the activity within wind energy systems and reports on goings on. This information provides operators with the data needed to decide if corrective action is required to protect the system’s integrity.
Wind Energy and Data: RDS-PP and SCADA
RDS-PP has different maintenance events: 1) prevention, 2) reaction, and 3) condition-based. A reactionary event is unplanned and sets off an alarm in the SCADA system. The system contains RDS-PP coding, which alerts support teams to the affected component’s problem. There are many ways to assess the vitality of a SCADA monitored system. One of which is SCADA signals connected to RDS-PP coded objects, making it easier to ensure that the correct maintenance actions are taken.
Wind Energy and Data: RELIAWIND and SCADA
Down-time data and other information relating to WFs were collected using ten-minute SCADA averages by the RELIAWIND consortium.
Wind Energy and Data: GADS and SCADA
GADS uses definitions that help make working with SCADA data more straightforward irrespective of geographic barriers. Examples of data include SCADA Type, SCADA Manufacturer, and SCADA Model.
Wind Energy and Data: SCADA and ISO 14224
SCADA data doesn’t possess a mandatory standard for data collection and structuring. However, ISO 14224 does provide recommended hierarchies and detail on the oil and gas industry mirrored somewhat in IEA Wind Task 33 regarding standards and principles to abide by when working with SCADA data in the wind industry.
Wind Energy and Data: IEC 61400-25 & IEC 61400-26
These standards act as Common Information Models (CIM) to aid SCADA data exchange and provide parameters to improve maintenance. Again, both fail to deliver enough definitions regarding wind energy.
Computerised Machine Maintenance System (CMMS) for Wind Energy and Data Maintenance
SCADA data is then sent and stored within the CMMS. A CMMS is an essential element within the operation and maintenance of a wind farm. It acts as a detailed log recording all turbine failures, safety events, and necessary maintenance to the sub-component level. The best practice is to ensure that the CMMS is integrated with the other databases connected to the turbine’s engineering system.
Wind Energy and Data’s Role in Digitalisation - Conclusion
Wind energy currently lacks a robust set of documents and principles to regulate and optimise energy production within the industry properly. The digitalisation of the energy sector in Europe will require a robust data-sharing infrastructure that provides demand-side flexibility to better use wind energy assets. An EU data space that aligns with similar areas is possible, but a common interoperability framework is first needed within the winder electricity industry. As it stands, the data groups and taxonomies in place don’t possess the depth to satisfy this need, and that’s a problem that must be rectified moving forward to achieve net-zero energy someday.
ANNEA Failure Prediction
ANNEA Underperformance Detection
ANNEA Energy Production Forecasting
ANNEA (Drone) Image Recognition
ANNEA Maintenance Planner
ANNEA Monitoring (upcoming)
© 2022 annea.ai GmbH, All Rights Reserved.
A note to our visitors