We sat down with re.alto’s Business Development Manager Jean-Pierre Hagen to get his thoughts on real-time energy data, including the importance of real-time data analytics, why the energy industry is lagging behind and how access to real-time data has the potential to enable Energy-as-a-Service.
When we talk about real-time data, what we’re actually referring to is the elapsed time interval between when the data was generated and when it was transmitted for processing and analytics. Real-time implies that that time interval is instantaneous, or in other words, the data is available to be processed as soon as it is generated. For this, the data needs to be dynamically streamed continuously from its point of origin, such as a sensor. We see plenty of examples of this in daily life – geolocation data from a mobile phone which tracks a person’s location in real-time on Google maps, or the sensors in wearable healthtech which track a person’s heart rate or blood pressure in real-time. In these cases, the technology becomes entirely redundant if there is a significant time lag between the data being collected and being processed, so the benefits are obvious.
Back in late 2019, Forbes highlighted how focus was shifting from big data, which has been a huge trend over the last decade, to fast data. They emphasised how it was no longer sufficient to simply have access to big data. Instead, the benefit comes from the capability to analyse and gather insight in real-time. That’s an important point to make. Real-time analytics requires technology that can process and analyse the data as soon it arrives, rather than storing it for slower processing at a later date. So, in order for real-time data to be exploited to its full potential, you need both access to the real-time data stream and the technical facility for real-time analytics.
The energy industry is a prolific generator of data but unfortunately the vast majority of it is not real-time. There is operational data, for example from renewable sources such as wind turbines or PV systems, or wholesale electricity pricing information. There are also vast quantities of consumption data which come from sources such as smart meters. In fact, the energy industry relies heavily on data to maintain day to day operations, such as grid load balancing. But energy data is rarely streamed or analysed in real-time which is very different from industries such as e-commerce or financial services.
Wholesale electricity pricing in the UK, for example, is done in 30-minute intervals, or settlement periods, through the day. Smart meters in the UK have largely been designed to fit this settlement infrastructure so they tend to only collect data in 30-minute intervals. (In other European countries, this time lag can vary from between 15 minutes to an hour). It’s also common practice for this metering data to not be transmitted back to the utility for another 24 hours. That’s fine for the homeowner who can track his own usage on the smart meter screen as it happens, but less useful for the utility. It puts them on the back foot, reliant on forecasting, which can be inaccurate, or data which can be days, or even weeks, old. It makes it very difficult to properly identify behavioural trends or consumption spikes, balance supply and demand more efficiently or make proactive operational decisions.
The lack of available real-time streamed data is obviously one core issue. But even if this data is made more easily accessible, there are still barriers to use which we’ve previously explored in detail in our whitepaper.
Although the energy industry is taking strides towards digitalisation, it still relies on historic practices or legacy system architecture. This outdated infrastructure is unable to handle real-time data, particularly as data volume and complexity increase. Once captured, data needs to be cleansed and standardised before any useful insight can be extracted. This is particularly problematic for the energy industry where there is still a lack of common data standards and proprietary data is often siloed. Adding this extra layer between data capture and data insight can be technically challenging and costly.
Cost is indeed another barrier to accessing real-time data. Upgrading existing infrastructure to make it fit for purpose can be prohibitively expensive. However, we are starting to see the emergence of new technological solutions which enable the integration of real-time, or near real-time, data from multiple sources in a cost-effective process, which is exciting. These solutions, like our own re.alto Connect, combine innovative API connectivity with a new Data-as-a-Service model. Our re.alto Connect Metering service, for example, can provide near real-time metering data tailored to business requirements even in areas without a smart meter roll-out by retrofitting residential sensors over existing analogue metering installations. It then handles data collection, standardisation, API integration and analytics in a fully managed service.
If you look at other industries like e-commerce or financial services, it’s clear that real-time data gives companies a clear commercial advantage – it enables them to move faster and make more agile, strategic decisions. Real-time data and real-time analytics deliver increased operational efficiency and improves the accuracy of decision making. Crucially, they enable businesses to personalise their services for a truly customer-centric model.
These benefits absolutely ring true for forward-thinking energy companies, but the potential is yet to be fully realised. Utilities, for example, could use real-time consumption data to tailor dynamic tariffs for customers or incentivise off-peak usage. It has the potential to accelerate the move towards distributed generation and widespread local energy communities by flattening the load curve at a local level and enabling consumers to play a more active role in supply. In a nutshell, real-time data is the enabler for the customer-centric business model we call Energy-as-a-Service. But for energy, the benefit of real-time data goes further still. There’s no doubt that real-time energy data is the missing piece of the jigsaw puzzle for the transition to a more sustainable system, the key to smart grids and full integration of renewable energy sources.
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