The energy sector is undergoing a profound transformation and Edge Computing is positioned as one of the enabling technologies to manage an increasingly distributed energy.
New technologies are changing the way the energy system works. As the energy system becomes increasingly reliant on renewable sources and energy use is becoming more electric with the increased use of electric vehicles and heat pumps, the electricity system is becoming more decentralised and dynamic.
In order for the energy system to be able to integrate various renewable energy sources and ensure that electricity production and consumption always match, grids need to be smarter. This requires a high level of digitalisation and automated communication and control, and this is where technologies such as Edge Computing help to manage and automate processes based on real-time data .
Edge computing proposes that data does not have to be centralised in its entirety in the cloud, but that part of it can be processed on distributed computers callededge nodes in the same place where the data is generated. Only the result or aggregate of such computing is centralised, thus avoiding overloading the infrastructure, eliminating unnecessary latency, and mitigating security risks.
In this respect, the advantages of edge computing are based on three pillars:
1) Increased scalability. By distributing the storage and processing of information across many locations, the growth of investment in infrastructure and capacity for a higher volume of traffic is more controlled.
2) Increased security. By not leaving their original location, the risks of theft or improper access to information are much lower.
3) Higher number of data processed and lower response latency. Analysis frequencies make it possible to work with thousands of data almost instantaneously, and analysis and response times are in the order of milliseconds. This allows for almost real-time use cases, unthinkable in cloud environments more oriented towards offline analysis of batches of information.
Imagine a Smart Grid, where the infrastructure to communicate, centralise and store all the data from thousands of distributed energy resource sensors is so complicated that the return on investment may not be viable. However, through Edge Computing, each energy element, be it an electrical substation, a transformation centre, a distributed energy resource or behind-the-meter consumption profiles, analyses its information in situ in real time and only communicates with the centralised infrastructure those relevant deviations that could have a significant impact on the grid.
The application of Edge Computing is already materialising in very specific use cases that companies in the electricity sector are implementing. We can find:
1. Edge Computing for the virtualisation of Transformer Substations
Many existing transformer substations still use electronic equipment with little ability to communicate. IoT devices can provide this communication to create a digital twin of each centre for greater flexibility, efficiency and effectiveness in operation and maintenance.
Furthermore, the processes executed by Edge Computing enable actions such as real-time dynamic regulation of the new "Smart Transformers", in periods of fluctuating power supply and peak demand, to maintain an optimised voltage.
2. Edge Computing for fraud and leakage detection
The development of artificial intelligence algorithms in the Edge makes it possible to detect possible fraud and leaks in the consumption of the low-voltage network . The consumption of electricity through illegal connections to the grid means an unplanned increase in demand that can cause large losses for distribution companies and breakdowns and fires in their transformation centres.
3. Edge Computing for distributed generation
The year 2021 was an unprecedented year for self-consumption of energy. In homes and industrial centres, small energy generation "power plants" are beginning to emerge, altering the balance of supply and demand. Therefore, the need arises to be able to manage a large number of distributed elements of electricity generation and storage, which allows the distribution and distribution of energy to be optimised.
Edge Computing facilitates an intelligent management of all these assets and allows to treat all of them in an aggregated way, under the "Virtual Power Plants".
4. Edge Computing for the development of new business models
The use of renewables and self-consumption makes it difficult to have visibility over decisions on whether or not to inject the energy generated into the grid. In addition, it is difficult to predict their generation capacity in real time due to the nature of their sources.
In the transition towards an energy balance regulated not by generation but by demand, new business opportunities arise, as well as the operational need to create new services and commercial offers, based on real-time information for consumers. Edge computing makes it possible to execute energy flexibility processes wherever energy is generated or consumed, and to adapt demand to generation possibilities.