~ The size and complexity of power networks makes remote distributed asset management difficult — but not impossible ~
The loss of electricity can have a significant impact, whether on the day-to-day operations of a business, the productivity of staff working from home or the bottom line of power asset management companies and grid operators. Here, Beth Ragdale, product manager at energy control system expert Beckhoff Automation UK, explains the role that modern control systems play in power asset availability.
In 2020, several UK power asset management companies paid a sum of £10.5 million due to failings that led to a power cut affecting over a million people in 2019. Although the cause of the initial fault was stated by UK energy regulator Ofgem to be “an extremely rare and unexpected event” caused by a lightning strike, it highlights the impact of asset failure in power networks.
Maintaining network availability depends upon correctly functioning assets. An operator must be certain that every asset, from those involved in generation such as wind turbines or photovoltaic panels to distribution assets like transformers, circuit breakers and power lines, is in good working order with a low probability of failure (PoF).
However, asset risk in an electrical network is no simple process. Electrical assets experience a broad range of time-based, utilisation or random failures. These each produce distinctly different failure modes, such as an electrical flashover or a failure of a circuit to trip.
There is also the fact that assets are neither uniformly complex nor equally accessible. A power transmission line has far fewer components than a transformer, and both have fewer components — and are much easier to access — than an offshore wind turbine. The more complex the asset, the greater the potential for failure.
When you scale this complexity and scope for risk to the size of an electrical network, it’s no surprise that asset maintenance is a priority for operators. RIIO-ED1, Ofgem’s current price control running from 2015 until March 31 2023, introduced a regulatory requirement for operators to report on asset health and criticality. This requirement is set to remain through to 2028, with Ofgem publishing an electrical asset health assessment methodology in April 2021 for the upcoming RIIO-ED2.
Part of the methodology for assessing risk is to account for planned interventions in a reporting period. These interventions include replacement, refurbishment or maintenance activities that aim to reduce the PoF of assets. Many of these activities contribute towards an operator’s network asset secondary deliverables that relate to the improvement in risk delivered by asset replacement.
Paramount to the delivery of interventions that reduce electrical asset PoF is accurate health monitoring. This has traditionally been conducted by manual inspection and assessment in most cases, which has proven to be a costly and inefficient practice that did not cater well to remote assets. As automation and control technologies have become increasingly interconnected and able to share data digitally, this process has been streamlined to make it easier, more cost-effective and more comprehensive.
For example, a wind farm operator might have several dozen turbines that it is responsible for reporting on to the network operator. Accurately assessing the health of a wind turbine depends on insight into how each constituent part is operating. This means evaluating parts like the blades and tower separately, as well as critical components like the drivetrain generator and turbine controller.
However, not every automation software is well-suited to deliver on remote asset health monitoring. Even in applications such as a wind farm, not all assets are designed in the same way and part replacements over time may lead to the installation of new systems from different manufacturers. This means that open automation software is essential, to ensure interoperability between the condition monitoring software and connected systems.
It’s for this reason that many asset management companies and power distribution network operators are turning to Beckhoff’s TwinCAT 3 software as a basis for condition monitoring systems. Built on open automation standards, TwinCAT 3 offers a flexible means of connecting assets from various manufacturers to not only acquire performance data, but to efficiently fulfil control functions.
The TwinCAT 3 software is also modular in design, so additional functions can be quickly introduced based on the specific requirements of different assets. This means that control functions can be quickly adapted to the unique needs of new assets, reducing setup time.
Simply introducing an open automation software platform such as TwinCAT 3 would suffice to meet the minimum asset health data requirements of RIIO-ED1 and RIIO-ED2 reporting. However, for operators that want to make the reporting requirements directly benefit their operating efficiency and costs, it also underpins more effective maintenance strategies.
One of the driving forces behind the boom in industrial data analytics and condition monitoring in the past few years has been the advancement of sensors. More granular data can now be easily collected from field devices and systems, contributing to a more comprehensive insight into operations.
For example, operators can connect a substation and get insight into the performance of the transformers, switchgear and other components. Each of these parts can provide several data sets each. From a transformer, operators with a sufficiently advanced setup can remotely draw data about voltages, local alarm system events, operating temperature, noise, vibration and even a breakdown of dissolved gases in insulating oils.
Maintenance teams and operations managers benefit significantly from the insights of granular data, more so if it can be attained in real-time. This requires a condition monitoring system able to synchronously collect multiple data points from single sources and share them. To do this in real-time, the communication protocol underpinning the system must be able to share data packets quickly — something that EtherCAT excels at, making the PC-based control of TwinCAT 3 ideal.
The cost of failure for power network operators is high and the sheer size and complexity of modern networks certainly makes minimising PoF a difficult task. Fortunately, with asset health reporting set to stay a regulatory requirement for the foreseeable future, operators can turn this necessity into an opportunity to improve their maintenance, make their automation software more flexible and bolster their bottom lines.