The drive to decarbonise energy, as well as the recent rise in energy prices, have brought into sharp contrast the need to re-examine how we generate, distribute, and consume energy, said Natalya Makarochkina, senior vice president, Secure Power Division, International Operations at Schneider Electric
It has been well argued that simply generating more electricity is not the answer to the myriad of requirements now being faced. Greater transparency, management, and efficiency in distribution and utilisation must all be achieved to better use what is available, even as demand might require greater volumes.
The increasing digitalisation of industry, through the application of technologies such as Industrial IoT (IIoT), 5G and automation, has offered greater insights and visibility of how electricity is used than ever before. As Industry 4.0 has brought digital to industry and manufacturing, creating the Industrial Edge, that same trend in energy, Electricity 4.0, can have its methodologies adopted and implemented. Enabled by intelligent management systems, leveraging expertise from the world of data centres, microgrids and secure power, these tools can ensure they utilise energy as efficiently as possible.
Industry 4.0 is the application of digital technologies to industry processes, supporting, enabling, and extending Operational Technologies (OT). Within this, the Industrial Edge is the subset of edge computing where OT and information technologies (IT) combine to apply high speed analytics in a localised, on-site system, addressing various industrial and manufacturing challenges. The industrial edge can provide simple, secure, highly available, powerful autonomous edge computing solutions that can be managed remotely.
Electricity 4.0 is a similar fusing of electricity generation and distribution with digital technologies to deliver new capabilities, insights, and manageability. It will be the foundation of the future of renewable energy sources and net-zero carbon, to allow intelligent distribution.
The growing wave of digitalisation in industry driven by transformation efforts, especially the implementation of IIoT, has meant that industries are better placed than ever before to gather and manage data on energy usage.
The development of the Industrial Edge, that interface between OT and IT, has meant there are now facilities to utilise the data from every sensor.
Schneider Electric’s EcoStruxure Micro Data Centre and EcoStruxure IT combines edge computing expertise and innovation with remote intelligent management systems which enable customers and partners to make deep energy management more practical and informative than ever before.
The interface has the potential to deliver greater visibility across the entire infrastructure, from edge sensor to intelligent insight. With a holistic view of energy usage across the organisation, predictive modelling can ensure that management can stay ahead of demand.
With many geographies likely to see some restrictions on energy supply soon, as major transitions towards renewable energy sources are embarked upon, the ability to confidently predict consumption and demand, moderate it where necessary and support sustainability goals, is vital.
IIoT can facilitate predictive maintenance regimes, monitoring performance and efficiency, to identify where failures may occur. Preventative measures can be taken to ensure continuity. This applies not just in production and processing, but across the operation through power distribution and IT.
There are many examples of industries taking the lead to bring the benefits of IIoT, edge computing and direct intelligence to their business.
Brazil's largest wastewater treatment plant, Aquapolo, achieved a 15% increase in operational efficiency, with a lower cost of ownership, while providing drinking water for more than 500,000 customers. This was achieved while also improving compliance standards for environmental protection.
With challenges expected as the world transitions to net-zero energy and operations, organisations that have achieved deep insights from sensor to core, will have the ability to predict, implement and adapt to change.
