Four Edge Computing Applications in the energy sector

The electricity sector is undergoing a revolution and Edge Computing is positioning itself as a great ally. But in which use cases is this technology being applied?

Smart Grid

Beyond Edge Computing, the energy sector is undergoing a profound transformation due to several interrelated phenomena: the decentralisation of electricity generation, the emergence of the prosumer who generates and consumes energy as well as new actors on the demand side and the growing incorporation of renewable sources.

This transformation is generating new relationship models between service providers and end-users (such as the emergence of energy communities or demand flexibility markets) and forcing companies in the sector to undertake major changes.

Edge Computing in the electricity sector

Among these major changes is the digitisation of processes to collect information and even predict future scenarios, which implies the need to collect a lot of data, analyse it and understand what decisions need to be taken and what actions need to be executed.

In order to make this processing more efficient, a new computing model is emerging strongly in the industry: Edge Computing. This involves complementing processing in centralised cloud infrastructures with Machine Learning or Artificial Intelligence algorithms executed at the edges of the network. That is to say, at nodes closer to where the data is captured.

This computing model is spreading very fast: if in 2019 Grand View Research put the value of the Edge Computing market at 3.5 billion dollars, the same firm claims today that this figure will rise to 43.4 billion dollars in 2027, following an annual growth of 37.4%. And the main reason for this trend is that it brings three major advantages for the industrial sector compared to the centralisation of computing in a single point (the cloud):

  1. Increased scalability: by distributing storage and processing over many locations, the growth of investment in infrastructure and capacity for higher traffic volume or better algorithms is more controlled.
  1. Greater data security and sovereignty: by not leaving its original location, the cybersecurity risks of theft or improper access to information are reduced.
  1. More data processed and less latency in responses: Analysis frequencies allow working 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.

The use of Edge Computing is already materialising in very concrete use cases that companies in the electricity sector are starting to implement.

1. Edge computing for transformer centre virtualisation

This is possibly the most important application in the sector. Medium to low voltage electricity transformation centres are the infrastructures responsible for adapting electrical energy so that it can be consumed by citizens in their homes. They are part of the distribution network, and there are hundreds of thousands of them in a country the size of Spain.

Edge Computing for Substations

These transformation centres have a series of industrial equipment whose digitisation can provide tremendously valuable information to both the centre operators and the manufacturers themselves, or even to the end users.

The Spanish Technological Platform for Electricity Networks FUTURED, an association that includes electricity distributors, manufacturers and technology centres in the electricity sector, has a working group especially focused on this task of digitising and providing intelligence to transformer substations, and it is something in which the vast majority of distributors are involved.

The central element of this "virtualisation" of transformer substations is the Smart Transformer. Through Artificial Intelligence and Edge Computing technologies, applications are being developed that make it possible to predict and anticipate demand or detect potential failures even before they occur (known as predictive maintenance ).

In addition, these edge computing applications also enable actions such as real-time dynamic regulation of power supply to the different lines on which new elements such as electric chargers or batteries now hang, which serve to meet the estimated demand at all times, to prevent equipment failures that force unnecessary trips, and to generate new services that increase the ROI of the entire value chain.

2. Edge Computing for fraud detection

Very much in line with the previous initiative, a complementary edge computing application that is being implemented by the transformation centres is the development of artificial intelligence algorithms that can detect possible fraud in the consumption of the low-voltage network.

The consumption of electricity through illegal connections to the distribution network leads to an unplanned increase in demand that can cause large losses to distribution companies due to faults and fires in their transformer stations. In addition, these faults often cause serious damage to other citizens whose supply is affected as a result.

This is why a major concern of distribution companies is the early detection of this type of irregularities, which allows them to protect their teams and distribution centres and not to neglect their legitimate customers.

Related article: Edge Computing: challenges and opportunities for the energy sector

3. Edge Computing to serve distributed generation

Smart grids Edge Computing Barbara IoT
smart grids

One of the most important changes taking place in the electricity market is the role of end users. While they have traditionally been mere consumers of energy, with the boom in solar self-consumption installations, more and more "prosumers" are beginning to emerge.

In homes and industrial centres, small power generation "plants" are beginning to emerge with new elements such as batteries or electric vehicle chargers that alter the traditional balance of energy supply and demand. Low-voltage grids are no longer unidirectional (from transformation centres to supply points) but bidirectional.

In addition to this scenario, new models of energy production and consumption are emerging, such as energy communities or demand aggregators, where groups of citizens and companies (even entire neighbourhoods) come together to generate, share or sell energy.

All of this creates the need to be able to manage a large number of highly distributed elements in order to optimise the distribution and distribution of energy. This is why many companies, both providers of self-consumption services and even distributors, are developing Edge Computingapplications that enable intelligent management of all these assets and treat all of them in an aggregated manner.

4. Edge Computing as a route to servitisation

A final case worth highlighting is that of servitisation . The concept of servitisation implies a change of business model and almost a cultural change in companies. It consists of moving from a model of large investments in assets to a new, much more flexible model of payment for services and for the use of products.

This new relationship paradigm allows, for example, electrical switchgear and power electronics manufacturers to have a new revenue stream with a high added value offer for their customers. Thanks to Edge Computing applications and algorithms, they provide intelligence to their industrial assets, which allows them to provide extremely valuable information for the operation of the plants or facilities that their customers, industrial and power grid operation companies, have to manage.

Barbara, the Cyber Secure Industrial Edge platform

Edge computing is being implemented as one of the mechanisms that can most help the digital transformation of the electricity sector. To be able to govern this new model of distributed intelligence, it is necessary to have a platform on the edge such as Barbara's.

Barbara is an industrial edge platform designed with cybersecurity by design oriented to distributed intelligence governance that enables:

  1. Connect, analyse and manage data from your industrial assets and integrate it with your remote business logic.
  1. Develop, deploy, debug, operate and maintain your edge computing applications and algorithms.
  1. Protect your equipment and data with cybersecurity mechanisms designed in accordance with industry standards such as IEC-62443.

The electricity sector is one of the sectors in which Barbara is most widespread, in Edge Computing projects such as those carried out by the Cuerva Group in its Transformer Substations, or EDP in its distributed generation facilities.

We encourage you to contact us to explain how Barbara can help you with your edge computing project.