The following blog provides a health analytics approach to electrical asset risk management in electrical energy systems. Through predictive & pro-active analytics, asset longevity can be enhanced and failure times reduced.
Electrical Asset Risk Management & the Health Analogy
The emergence of “wearable technology” for the health & fitness market has grown hugely over the last few years. Fit Bit, Apple & others are tapping into the knowledge that a real-time understanding of your key health statistics will help to drive proactive and iterative actions to ensure longevity of health as well as lower health insurance costs and other financial benefits from better health.
This development in real-time health analytics is a great analogy to utilise for electrical asset risk management in electrical energy systems.
The Reliance on Electricity
Electricity is the focus of this blog, although energy obviously encompasses a large number of other sources. One key reason for this focus is that businesses rely hugely on electricity. Globally, electricity accounts for 48% of all energy consumed by businesses.
So, like a human body, a business that really cares about its longevity and the risk of system failure will want to ensure that their electrical system is as healthy as possible. As such, they will want to predict any issues before they happen.
This approach is electrical asset risk management for electrical energy systems.
This criticality of electricity to the life and death of a business, and the issues that can cause important equipment to fail and / or degrade more quickly, is an area that we are passionate about. As a business dedicated to energy and risk management, we have taken a strategic interest in the development of electrical asset risk management and its application to electrical systems.
How we communicate this is becoming more and more obvious as we examine the crossover with human health approach.
Electrical Asset Risk Management through the Lens of Health
Specifically, in relation to electrical asset risk management, how can we help businesses to enhance their real-time awareness of the health of their electrical energy system? If we can do this well through pro-active asset risk management, then the overall health of the electrical assets should be optimised, risks minimised and the lifetimes enhanced.
We think the health analogy – a sort of Fit Bit approach to electrical systems – works really well in this energy asset risk management context.
This approach, in engineering terms, is typically referred to as Reliability Centred Maintenance (RCM) which uses a combination of predictive and preventative maintenance techniques to achieve much lower overall maintenance costs.
Figure 1 shows research from the American Society of Mechanical Engineers (ASME.) It shows the difference in cost (per rated horse power, HP) for different maintenance regimes from reactive (fix when broken) to TPM (Total Productive Maintenance – a specialised approach to maintenance in manufacturing environments.)
Figure 1: Maintenance Cost Comparison (ASME)
If you take the heath analogy, a preventative approach (what most businesses do these days) is to go to the doctor every year for your annual check up and get all your key performance indicators taken (BMI, blood pressure etc). This is great, yet it only provides a one-off snapshot of what is going on in your body at that moment in time. It does not give the doctor (aka maintenance team) any idea as to the variability of these key risk factors throughout the day, different times of the week & / or year.
Preventative maintenance is not an optimised approach to “health-based”electrical asset risk management.
Real-Time Electrical Asset Risk Management & Health Statistics
You could put on a blood pressure monitor for a 24-hour period, as some people do, to give a better idea as to the relative fluctuations in this risk factor. This will give better data.
However, it is still limited to the day that you choose and the particular stresses on your body for that specific period. It does not give you an overall insight into the issues driving that particular risk marker.
In electrical systems, this is equivalent to the approach of fitting temporary monitoring to your electrical system. It will provide a snapshot, yet only of value for that particular period. O&M teams doing this will get the same bias as the example above – an insight that is relevant to what is going in the system at that moment / week but not for the whole year.
However, going back to the human health analogy, imagine if you were to wear something that would take your bloods, BMI, temperature, blood pressure etc. every 30 minutes and relay it back to a central health analytics. In this virtual monitoring office doctors and nurses would interpret your health data and feedback what you needed to do to mitigate existing and potential risks. This would all happen in real-time. A sort of remote electrical asset risk management solution for your health & well-being.
This is where electrical asset risk management of electrical energy systems is going – in our opinion and it is what we are doing for commercial & industrial clients with their electrical systems. Remote electrical asset risk management.
Electrical Asset Risk Management & Leveraging Existing Metering Assets
The key to all of this is monitoring hardware and sensors – something the Internet of Things (IoT) is all about. Where can we put sensors to add value to real-time information, feedback & optimisation.
The interesting fact is that most commercial and industrial organisations already have a level of monitoring hardware in place that means they do not need to spend more money on sensors. In this case most businesses are either not extracting the relevant data from existing metering assets or have not connected their existing metering assets to an appropriate system. If they do than they will enable a real-time approach to electrical asset risk management.
It’s amazing how many commercial businesses we visit where there has been a significant investment in high-level metering (e.g. Schneider power meters) which is then only read manually every week. This data is then entered manually into an excel spreadsheet and then emailed to their finance team / energy managers.
In addition, this data is typically only singular i.e. energy (kWh), and does not include the multitude of other data points that are available for unearthing significant electrical asset risk management opportunities.
More Data & the Right Assets
Connecting these metering devices (and new ones) to a real-time analytics platform such as Argand’s Lenz can help to transform the ability for a business to move towards an RCM-based approach to maintenance. This real-time “health analytics” approach to their business and asset risk management will enable all of these unused data points to be analysed in real-time to drive electrical asset risk management insights that are currently invisible to operations directors, finance directors and their teams.
However, this is just the 1st step. The next step is to use the data to create valuable electrical asset risk management information.
Yet, which assets should a business focus on? The simple answer is all assets – if you can. However, if you are capital and time-constrained then the best place to start could be motors or Electric Motor Distribution Systems (EMDS.)
According to the International Energy Agency (IEA, see http://www.iea.org/Textbase/npsum/ee_for_electricsystemssum.pdf) electrical motors account for 57% of total electricity use by industrial (64%) & commercial (20%) organisations across the world and 45% of total global electricity consumption. This is broken down in figure 2.
Figure 2: % of electricity accounted for by motors by type of use (IEA)
So, any organisation that is interested in enhancing the health of their assets should start to take a real interest in the state of their motors. This will enable a focus on the key electrical assets and help to increase their longevity through real-time electrical asset risk management analysis.
Most electrical equipment, including motors, are typically sensitive pieces of equipment (electrically) that need to work within defined limits.
This sensitivity to limits allows us to utilise a health analogy easily. We’ll look at this approach in the next part of our blog.