Grid modernisation and data security are of focal points as Artificial Intelligence (AI) revolutionises infrastructure performance and business insights.

The Executive Order from the White House on the “Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence” signifies a crucial step towards establishing trust and security guidelines for rapidly advancing AI technologies.

This initiative is particularly vital for the digital energy sector, where AI plays a central role in critical infrastructure projects such as Virtual Power Plants (VPPs) and Energy as a Service (EaaS).

Looking ahead, the future priorities for AI in this industry revolve around ensuring productivity, authenticity and security.

AI’s role in digital energy productivity

Beyond content generation, AI serves as the driving force behind automating decision-making processes in the digital energy sector, notably in projects like Virtual Power Plants and Energy as a Service.

VPPs leverage AI to optimise energy generation and distribution, ensuring a balanced supply and demand. EaaS, powered by AI, provides consumers with flexible, adaptive energy services. These innovations have the potential to transform energy production and consumption, making it more sustainable, efficient, and cost-effective.

Ensuring data provenance and authenticity

Critical to AI’s success in the digital energy industry is the assurance of data provenance, authenticity and transparency.

The Executive Order aligns with the establishment of a universal data, IoT and AI trusted interoperability standard. This framework sets clear provisions for governing and tracking content and decisions made by dispersed AI platforms.

Have you read?
Energy cybersecurity in 2024: Building accountability and responsibility
Generative AI for smart grid modelling

Key aspects include:

• Training AI Algorithms: AI algorithms rely on authentic and unbiased data for training, directly impacting their effectiveness in optimising energy processes. A layered trust stack ensures the security of data provenance and device authenticity.

• AI-Driven Decision-Making: Authentic, authoritative, and policy-compliant data is essential for AI-driven decision-making in critical infrastructure projects. An interoperable standard must be future-proofed to handle evolving cyber threats, including quantum computing.

• Verification and Authentication: The order emphasizes verifying AI compliance with policy criteria, requiring authentication of verifier credentials. A universal secure interoperability standard necessitates a stack of verification algorithms adaptable to diverse layers.

Transparency in AI-generated content

In the digital energy sector, AI-generated content influences people’s actions, demanding transparency to build trust and ensure responsible AI use. Transparency provisions are effective when assuring entity authenticity and authorisation across diverse technologies and statuses.

An authoritative and authenticated web is being designed to address:

• Provenance of Data and Content: Tracing and recording the origins of data and content are crucial for reliability in energy information. In a VPP, a well-managed software platform is essential for administering all aspects, from monetisation to compliance reporting.

• Credential Authentication: Verifying data providers’ credentials and sensor properties ensures the legitimacy and trustworthiness of data sources, crucial in systems like Energy as a Service.

• Interoperability for Assurances: Interoperability is crucial for applying assurances effectively in distributed systems. TEIA, the Trusted Energy Interoperability Alliance, founded by Intertrust, answers the call for AI regulation, integrating security and interoperability within a flexible standard.

Policy and data in trustworthy AI operation

The executive order stresses the need for using both policy and data to manage trustworthy AI operations. With AI influencing decision-making in various automated systems, recognising its roles is crucial.

Trust management and adaptable policy frameworks are necessary for:

• Reasoning About AI: Transparency, trust management and agile policy frameworks are vital for reasoning about the provenance and authenticity of AI inputs and outputs.

• Security Infrastructure: An efficient security infrastructure must ascertain data and AI provenance, providing tools for authentication by both people and automated applications.

• Real-Time Responsiveness: Security infrastructure and policy frameworks must be self-adaptable to meet the real-time requirements of decision-making in the digital energy industry.

• Resilience to Attack: Interoperable security measures across IoT and data processing fabrics ensure resilience against malicious attempts, safeguarding energy infrastructure.

• Integration with the Web: Seamless integration ensures broader, comprehensive security, crucial in the digital energy sector where VPPs and EaaS rely entirely on digital platforms.

The Executive Order on AI development and use is a significant milestone for the digital energy industry, emphasizing the importance of AI in optimising energy processes.

Intertrust’s TEIA aligns with the order, ensuring AI-driven decisions comply with accurate data and policy criteria. Industry stakeholders should actively engage with the proposed mechanisms and TEIA solutions, contributing to a secure and dynamically adaptable digital energy future. This collaborative approach will foster efficiency, reliability, and sustainability in the evolving landscape of AI in the energy sector.

About the Author

Hebberly Ahatlan is product marketing director, energy at Intertrust Technologies and has 15 years of experience in the tech industry developing go to market strategies.

In an exclusive interview with Stuart Thompson, President of ABB Electrification Service and Antonio Martinez Reiner, Utilities ＆ Renewables Global Leader at ABB Electrification Service, we unpack circularity as a solution and what the barriers to digital adoption are.

Watch the full video interview below.

This interview was filmed in November 2023 at Enlit Europe in Paris, France.

ABB helps customers deploy proactive, predictive maintenance using real-time data analytics to monitor and evaluate asset health, reducing downtime, total cost of ownership, extending asset lifespan and preserving finite resources.

Read ABB’s latest whitepapers on how circularity and digitalisation improve sustainability and drive new levels of operational efficiency:

• Tackling Throwaway Culture – your guide to smart services
• See the full potential of digital, faster – find ways to overcome your biggest IIoT barriers with this guide

You might be interested in:
A proactive mindset is vital to accelerate the energy transition, says ABB President
ABB boss Guggisberg says switchgear is going back to its sustainability roots

The initiative, part of the Tennessee Tech University led smart grid modelling and testing ‘Smart Grid Deployment Consortium’ project in the Appalachian region of the US, will focus on creating AI-driven generative models for customer load data.

These will then form inputs to the modelling services of the HILLTOP microgrid simulation platform for modelling and testing new smart grid technologies, in particular for the rural electric utilities that serve much of the region and for example for energy tech startups that are interested in scalability and interoperability.

“This project is a powerful example of how generative AI can transform a sector – in this case, the energy sector,” says Kalyan Veeramachaneni, principal research scientist and principal investigator at the LIDS.

Have you read?
Generative AI solutions for utilities on the rise
The vital role of R&D in the energy transition

“In order to be useful, generative AI technologies and their development have to be closely integrated with domain expertise. I am thrilled to be collaborating with experts in grid modelling, and working alongside them to integrate the latest and greatest from my research group and push the boundaries of these technologies.”

The generative models are expected to have far-reaching applications in that when trained on existing data, they can create additional, realistic data that can augment or replace limited datasets.

For example, in this case generated data can predict the potential load on the grid if an additional 1,000 households were to adopt solar technologies and how that load might change throughout the day

The initiative has been awarded $1.37 million in funding from the Appalachian Regional Commission and will include other participants from across Ohio, Pennsylvania, West Virginia and Tennessee.

The legislation, proposed by Peter Welch of Vermont and Angus King of Maine in the Senate and Kathy Castor of Florida, Paul Tonko of New York and Scott Peters of California in the House of Representatives, requires the Federal Energy Regulatory Commission (FERC) to establish a shared savings incentive for GETs to encourage their deployment by July 2025.

Instead of the traditional fixed rate of return on a capital investment, a shared savings incentive would return to the developer a portion of the savings attributable to the investment in a GETs, with some of the savings also going to customers.

Additionally, the proposed Act includes an annual reporting requirement that directs transmission owners to report the costs associated with congestion to FERC and directs FERC to analyse and make this data publicly available.

Have you read?
Grid enhancing technologies – a potentially cost-effective option for transmission upgrades
The puzzle of transmission grid planning

It also charges the Department of Energy with creating an application guide for implementing GETs projects. providing technical assistance to stakeholders interested in GETs and managing a clearinghouse with examples of implemented GETs projects.

Senator Welch commented: “We’re at a crucial turning point in our work to achieve a clean energy transition, and meeting this moment requires new investments in clean energy technologies that strengthen the capacity of our transmission system.

“The Advancing GETs Act will motivate grid operators and developers to bring new projects online that expand transmission capacity by guaranteeing returns for these targeted, cost saving investments. This legislation will be crucial to boosting transmission capacity and helping the United States achieve its clean energy electricity goals.”

The introduction of the Act follows a week after Senators Welch and King and Representatives Castor and Tonko urged the FERC in a letter to implement a cost saving incentive for GETs – a proposal first made to the organisation in 2020 by the industry associations the WATT Coalition and Advanced Energy United.

Julia Selker, Executive Director of the WATT Coalition, said since that time no alternative proposals to incentivise utilities to deploy these technologies have been made.

“GETs do not fit well into today’s utility business model. By designing an incentive based on the system benefits of deployments, consumer value and protection is built into the regulation. This policy would drive innovation that has been stalled for years and start to unlock capacity and flexibility on the existing and future transmission grid.”

Some individual states have started acting on GETs. In Illinois and New York, for example, studies are underway to evaluate their potential and legislation is being advanced in Minnesota and Virginia among others.

Grid enhancing technologies are hardware and/or software that dynamically increase the capacity, efficiency, reliability or safety of the existing grid and include dynamic line rating, advanced power flow control and topology optimisation.

Karman is built on a custom module that leverages the NVIDIA Jetson platform for AI in order to capture and analyse data to improve grid operations and manage distributed energy resources (DERs).

A first for the Karman platform, the integration should bring a new level of data insights to Aclara smart meter implementers, with up to a stated 100 times more processing power than traditional solutions.

Local AI models also will continuously learn to improve in areas such as grid planning, grid operations, load management, customer service and more.

Have you read?
Intelligent edge platforms, accelerating grid modernisation
Unlock the business value of Grid Edge Computing

“As the grid becomes increasingly more complex and dynamic, utilities need more technology options to operate a clean and reliable grid,” comments Erik Christian, Division President, Grid Automation of Hubbell, of which Aclara is a division.

“By combining Utilidata’s extensive knowledge of distributed AI with Aclara’s decades of experience providing industry-leading hardware, we’re now able to bring new, innovative, interoperable solutions to our customers, starting with smart meters.”

A company statement reports that the partnership follows the trend of market momentum and federal funding driving the utility industry’s need to modernise and report its operational efficiencies, for which distributed AI holds vast potential.

In October 2023, the Department of Energy announced $3.5 billion in funding for grid modernisation projects, including awards to Portland General Electric, Duquesne Light Company and Commonwealth Edison Company to deploy over 100,000 Karman units to increase reliability and accelerate decarbonisation and electrification.

Elizabeth Cook, Vice President of Technical Strategy of the Association of Edison Illuminating Companies, said that utilities are seeking more options for new and innovative technologies, like distributed AI, for easily accessible and actionable data.

“Utilidata’s partnership with Aclara makes it easier for utilities to integrate this important technology as the industry continues to build a smart and adaptive grid that is resilient and reliable for customers.”

Josh Brumberger, CEO of Utilidata, points to a meter-embedded distributed AI platform as only a beginning.

“There are more opportunities beyond meters within the electric grid ecosystem that can benefit from having easy to access data and predictive analytics.”

Announced alongside the Group’s full-year results, E.ON plans to boost its four-year investment plan from €33 billion ($36 billion) to €42 billion ($46 billion), focusing on energy networks and energy infrastructure solutions.

“Across Europe, there are massive expansion plans for renewable energy facilities that will need to be connected to networks,” said E.ON chief financial officer Marc Spieker in a release.

“Millions of heat pumps, residential electricity storage systems, and charging stations will need to be installed as well. That’s why we’re investing even more and even faster in our power grid infrastructure, which is set to continuously grow by an average of ten percent annually through 2028.”

Within the plan, €34 billion ($37 billion) will go towards E.ON’s energy network business, given a suitable regulatory environment. More than €25 billion ($27.3 billion) – 70% – of network investments will be made in Germany.

Approximately €5 billion ($5.5 billion) will be devoted to energy infrastructure solutions, E.ON’s growth business which provides solutions for industries, cities, and municipalities.

Other areas for investment include digitalisation projects, the rollout of smart meters and intelligent e-mobility charging solutions.

Have you read:
50Hertz claims €20.7bn transmission investment plans
Dutch demand continues to outstrip supply despite record grid investments

Said CEO Leonhard Birnbaum during a press conference: “We again defied challenging circumstances in the financial year 2023. And we again delivered very good results that exceeded our expectations.

“This result is proof … that we increasingly benefit from our consistent strategic focus on energy networks and sustainable energy infrastructure and customer solutions.

E.ON investment: 2023 results

The Group significantly accelerated its investments in the financial year 2023, bringing it a total of €6.4 billion ($7 billion), a one-third increase from the year prior.

Specifically, the Group invested €5.2 billion ($5.7 billion) in network expansion, modernisation, and digitalisation and €1.1 billion ($1.2 billion) into customer solutions, of which approximately €700 million ($765 million) went toward its energy infrastructure solutions.

Energy networks delivered the largest share of Group earnings from 2023 with a €1.2 billion ($1.3 billion) year-over-year increase. Higher investments in E.ON’s growing network infrastructure were a key driver, ensuring increased connection rates for renewables, heat pumps and charging infrastructure.

In 2023, E.ON added more than half a million new connections to its distribution networks. Alongside higher investments, the recovery of the energy market environment had a positive impact on the network business. This led to a significant reduction in costs for redispatch in Germany.

Added Spieker: “E.ON looks back on a strong financial year 2023, in which we grew in almost all European markets. The outlook for the years ahead is very promising as well.

“Our network business is a growth business that is in the focus of attention for policymakers, the public and investors. Our energy networks are system-critical for the energy transition, and we’ve again proven that we can successfully and cost-efficiently expand them.”

The blueprint, which has been prepared by the Interoperability Network for the Energy Transition (int:net), is aimed to guide on transitioning the existing energy sector data infrastructures towards data space solutions and to define a general data space architecture that can enable an initial set of real-world business use cases.

In particular, the architecture is aimed at interconnecting the existing data infrastructures with federated data spaces, in which multiple datasets are mapped.

The concept of data spaces has been gathering momentum in various domains for sharing of data between multiple participants and the establishment of a common energy data space is one of the key actions set out in the EU’s energy sector digitalisation action plan.

Have you read?
First version of the European energy data space is up for funding
Creating data space with smart meter hubs

Foundational aspects that must be considered pertain to security and privacy, data quality and integrity and governance, while other aspects that need to be taken into account include the business model related to data exchange, legal and operational details and the technology, with a primary objective to ensure interoperability both internally and with other data spaces.

The blueprint document states that at the highest level, the CEEDS is foreseen as the common framework that federates different data spaces implemented at national, sub-national or international levels and allows the participation of single users.

Business use cases

The five representative business use cases, in which specific exchanges of data from diverse sources must occur among the involved actors, were defined as:

• Use case #1 – Collective self-consumption and optimised sharing for energy communities
• Use case #2 – Residential home energy management integrating distributed energy resources (DER) flexibility aggregation
• Use case #3 – TSO-DSO coordination for flexibility
• Use case #4 – Electromobility: services roaming, load forecasting and schedule planning
• Use case #5 – Renewables O&M optimisation and grid integration.

Based on these the proposed model corresponds to the creation of the energy data space as the combination of multiple ‘distributed data ecosystems’, i.e. the existing legacy data platforms, with an overarching layer defined as the ‘federated data space’ where the data is indexed and made discoverable and providing a ‘marketplace’ for sharing and possibly trading of data and data services.

Data space connector

The different data space participants are connected through a software component known as the ‘data space connector’, which realises the interconnection and data exchange.

This data space connector should be incorporated into the pre-existing platforms to enable identification, data harmonisation and brokerage towards data spaces, which can be useful for integrating data from different sources or for allowing multiple applications to access the same data without having to duplicate it in multiple places.

Moreover, in this model, the data space connector also enables the exchange of energy data and execution of services both among the existing legacy platforms and through the federated layer.

The document notes that to fully achieve the deployment of the CEEDS, starting from the federation of projects’ data space instances, detailed interoperability measures are necessary including technical interoperability, semantic interoperability and governance interoperability.

The document states that the presented blueprint underscores the critical need to adopt data space solutions within the energy domain, marking a pivotal moment for the transformation of the industry.

“The fundamental pillars of data spaces not only foster the active engagement of key stakeholders across the energy value chain but also promise mutual benefits, ranging from monetary compensations to an elevated quality of services.

“At this scope, the establishment of clear rules, policies and regulatory adaptations is a linchpin in facilitating fair data exchange, paving the way for an open market that fosters the participation of new actors, including data and service providers, as well as data consumers.”

The int:net initiative managed by the Fraunhofer FIT is an EU Horizon Europe-supported project to bring together stakeholders from across the European energy sector to jointly work on developing, testing and deploying interoperable energy services.

Key parties are the projects in the ‘energy data spaces cluster’, i.e. Omega-X, EDDIE, Enershare, Synergies and DATA CELLAR, whose findings have fed into the blueprint, while further inputs should come from the newly launched HEDGE-IoT, ODEON and TwinEU projects.

In the meantime, the blueprint will continue to be updated with version 2 due to be released in June 2024.

According to the Commission in a release, the network code will be an important step to improve the cyber resilience of critical EU energy infrastructure and services.

The delegated act follows a consultation process with relevant stakeholders, including contributions from ENTSO-E, EU DSO Entity and ACER, as well as a four-week period for public feedback at the end of 2023.

It will support a high, common level of cybersecurity for cross-border electricity flows in Europe.

EU network code for cybersecurity

The EU network code aims to establish a recurrent process of cybersecurity risk assessments in the electricity sector.

These assessments are aimed at systematically identifying entities that perform digitalised processes with a critical or high impact in cross-border electricity flows, their cybersecurity risks and then the necessary mitigating measures that are needed.

To do so, the network code establishes a governance model that uses and is aligned with existing mechanisms established in horizontal EU legislation, notably the revised Network and Information Security Directive (NIS2).

This is the case, for example, for the reporting of cyberattacks and vulnerabilities using the established Computer Security Incident Response Teams (CSIRTs), or coordination with the CyCLONe network in case of large-scale cybersecurity incidents and crises.

The new rules will promote a common baseline while respecting existing practices and investments as much as possible, states the Commission.

The model is hoped to be able to develop, follow and regularly review the methodologies of different stakeholders, considering the current mandates of different bodies in both the cybersecurity and electricity regulatory systems.

Have you read:
Cybersecurity standards to be developed for EU distribution systems
US developing uniform guidance on distribution cybersecurity

Although there is already a comprehensive overall legal framework for cybersecurity, the energy sector presents areas in need of renewed attention, including:

• Real-time requirements

Energy systems need to react at a speed that removes the need of standard security measures, such as authentication of a command, or verification of a digital signature, due to the delay these measures impose.

• Cascading effects

Electricity grids and gas pipelines, states the Commission, are strongly interconnected across Europe and beyond the EU. An outage in one country might trigger blackouts or shortages of supply in other areas and countries.

• Combined legacy systems with new technologies

Many elements of the energy system were designed and built before cybersecurity considerations came into play. This legacy now needs to interact with the most recent state-of-the-art equipment for automation and control, such as smart meters or connected appliances and IoT-connected devices, without being exposed to cyber-threats.

Foreseen under the Electricity Regulation (EU) 2019/943 (Article 59) and in the 2022 EU Action Plan to digitalise the energy system, the delegated act is now subject to scrutiny by the EU co-legislators.

With the announcement from the Commission, the dossier now passes to the Council and European Parliament to scrutinise the text over a period of up to four months for objection.

The rules will enter into force once this period is over.

The project, implemented as part of Enea Operator’s activities to modernise the energy infrastructure and introduce new solutions to improve the quality and security of supply, is aimed to contribute to improving the management of the distribution network.

Its basis is the use of proprietary deep learning algorithms from Polish software developer Affexy, with a focus on the most relevant data enabling continuous improvements that can improve the precision of forecasts and their adaptation to dynamically changing network conditions.

The project is predicated on the need to better adapt the grid to the changing conditions of the electricity market with growing renewable energies and for example new energy efficiency regulations.

Have you read?
EIB invests in Polish and Belgian network modernisation
Although Poland is on its way, a greater push is needed to reach net zero – IEA report

It is focused on three areas, of which the main one is the data analysis to enable understanding of the load on the network and identification of factors that affect the variability of that load.

Prior to that is the processing of the acquired data so that it can be efficiently analysed by the advanced AI models.

In the final step, a report and recommendations will be made with the conclusions from the analysis and suggestion of actions to optimise the data collection process and the quality of the forecasts.

Enea Operator anticipates that benefits will include a better understanding of the network load and the patterns that drive it – aspects that are critical for effective network management.

The project also introduces and pilots the advanced AI techniques, thereby testing the effectiveness of the algorithms in real-world conditions.

With the results and experience obtained, Enea Operator anticipates the implementation of a full-scale system.

Alongside this project, Enea Operator has concluded a PLN1 billion ($255 million) investment loan agreement with the European Investment Bank for distribution works.

These are to include the modernisation and construction of almost 8,000km of medium and low voltage grids, installation of 2.4 million smart meters, connections of 140,000 new customers, upgrading transformers by 633MVA and the connection of 4.3GW of new renewable generation capacity.

If there’s one place where generative AI has the ability to make a tremendous impact, it’s the energy sector. AI could help streamline energy production and distribution, increasing efficiency and cutting carbon emissions from the vital processes that enable us to keep warm, travel and live our modern lives.

While businesses all over the world are investing in generative AI and the talent needed to implement it, the energy sector is facing its own talent issues when it comes to generative AI.

For example, data shows that 40% of businesses in the energy sector find it difficult to hire data scientists with the skills they need. Without the right combination of talent and data necessary to accurately and quickly utilise foundational models, many energy companies will not be able to leverage generative AI fully. They will therefore be at a disadvantage compared to competitors for the future of energy — one that entails a global transition that will likely occur at an increasingly rapid pace. 

So what do you do when there’s a talent shortage but your business needs to add more skills? You train the talent you already have. In 2024 and beyond, as energy demands grow on a global scale, the energy sector will find combining generative AI with proper upskilling to be extremely valuable.

Generative AI’s effect on enterprise talent

For many organisations, a successful approach to upskilling will begin with an understanding of how generative AI can affect almost any position within an organisation.

Some employees will see generative AI agents augment their current position and give them access to more relevant data. Other staff members may collaborate side-by-side with generative AI agents that sit either upstream or downstream of a human in a business workflow. Then there’s the software engineers, or those who will be charged with creating or fine-tuning generative AI agents.

Ultimately, each company will have to assess which new roles will be required (i.e. prompt engineers) and which ones will change materially (i.e., software developer). They’ll have to train each employee on how to use the technology — even if that training is at a basic level.

Generative AI and the energy sector

There are already growing use cases where generative AI is making an impact in energy and, as energy consumption increases, those use cases will expand.

For example, generative AI is currently playing a key role in safety procedures at various energy companies around the world. Historically, before any operator at an energy company begins a job, they’d receive a standard, but often generic, safety briefing. Traditionally, the safety analysis has been completed manually, which can leave out a more comprehensive view of all the necessary safety measures.

With a generative AI agent trained on the right safety data, operators will have access to insights on near misses, extensive safety records, weather conditions, etc. Operators can receive briefings that are specific to their role, job site and team.

Generative AI is also accelerating the rate at which energy employees can access data. With a generative-AI powered enterprise search, enterprises now allow their employees to find pertinent data as soon as they start a job. Through retrieval augmented generation, the generative-AI agent will learn which data is most relevant to the right staff members as they search. This will allow employees to access the right data such as log data, geographical data, information on local culture and much more.

For the energy sector to reap these benefits they’ll need to apply sound, repeatable upskilling practices at the right scale and to the right employees.

Have you read?
How AI and advanced analytics will be key for the grid of tomorrow
Robot dog Spot to transform into Sparky with AI enhancements

Upskilling talent — Who? How? Why?

Like other industries, the energy sector is competing for talent that can match their plans for generative AI implementation. This is why external hiring of data scientists isn’t occurring at the rate energy executives would like to see. Also, the energy sector requires a specific set of expertise, which further commodifies generative AI-related roles at energy companies such as data scientists, prompt engineers and software developers.

Since finding data scientists and other roles with the right expertise hasn’t been easy, certain energy companies are instead looking to the experts already within their ranks. This translates to upskilling initiatives for as much talent as possible in generative AI, which helps close the gap in external hiring. Some of the upskilling will be for roles such as data scientists, enterprise architects and data engineers.

There are already examples of energy companies taking intentional approaches to upskilling. For example, as Duke Energy continues its cloud journey, it has built a framework that allows many of its employees to access relevant training content and engage in learning that aligns with Duke Energy’s cloud computing and clean energy goals.

Other avenues are available to energy companies who want to upskill their talent on generative AI. Some companies may choose to turn to cloud and foundation model providers to support internal employee training through formal class or online learning. This is another reason why it’s important to develop relationships with the partners who are developing the generative AI technology that companies are trying to use.

Other upskilling approaches include providing free sources of consumable training content through sites such as deeplearning.ai. Further, there are some enterprises that are creating opportunities for experiential learning through proof of concepts, hackathons and workshops. These experiential opportunities in particular are great ways to train talent on scenarios that extend past technical skills.

One energy company AWS worked with recently leaned into an experimental upskilling initiative to better leverage radio communication transcripts. The radio communications team and edge team worked together to develop a generative AI agent that combines radio communication transcripts with asset IoT data to produce daily job status reports. The radio communications and edge teams did not typically work together. However, joining forces to create the prototype helped them develop the required relationships to take generative AI to the next level.

Breaking silos and bringing different departments together — like the example above — is a major reason to invest in the right generative AI training. However, getting buy-in from boards of directors and participating in responsible AI practices are also good reasons to practice upskilling.

Upskilling promotes responsible AI

Despite some of the benefits generative AI brings, there are still many leaders, particularly in the energy sector, that have concerns about the introduction of generative AI into their companies. For example, many energy/utility companies have access to customer information and confidential internal data that can be introduced to foundational models. Board members and c-suite leaders want to be sure this information remains secure. From a financial standpoint, today’s enterprise leaders want to make sure investing in generative AI issues an adequate return on investment.

In each scenario, training all members of an organisation on responsible AI practices should be a part of any upskilling approach. This includes understanding responsible AI tenets such as fairness, explainability, robustness, privacy and security, governance, and transparency. With proper responsible AI training, enterprises can safely power innovation, mitigate stakeholder concerns and see continued ROI.

Keeping pace with innovation

The current hiring landscape suggests that energy companies won’t be able to hire generative AI talent at the expected (and necessary) pace of innovation.

This talent and recruitment landscape likely points to a world where energy companies will not only have to begin investment in upskilling their own talent, but possibly double and triple down on investment initiatives.

With energy consumption on the rise, organisations will have to place greater focus on empowering the talent they already have to train generative AI models, analyse subsequent data and leverage that data to create the solutions necessary for the future.

About the Author
Joseph Santamaria is director of WW Energy and Utilities Solution Architecture at AWS.

In his role, he works with the largest utilities, oil and gas and energy producers in the world to utilise the cloud to solve the most complex problems in the energy transition and operations.

Modernising the energy grid is a complex, large-scale endeavour, ranging from distributed energy resource management to grid digitisation, smart metering to the rise of prosumers, and much more.

Grid modernisation

In the coming decades, energy needs are forecast to increase as the global population continues to rise and as countries develop and their economies grow. During this transformation, accelerating the availability of clean, renewable energy is critical to meet this growing demand while addressing climate concerns.

As the world looks to a net zero future, technological advancements in electrification are helping address challenges associated with scaling renewables and enabling them to become viable alternatives to traditional fossil fuel sources of energy.

Furthermore, as the grid evolves, the distribution, storage and management of electrical energy are changing. There is a shift from centralised power stations to distributed renewable energy- characterised by smaller and widely spread power generators, usually coupled with energy storage capacity, which feed into the distribution grid. Decentralisation results in bidirectional energy flows, where end consumers become prosumers, necessitating the evolution of new energy markets. Done right, decentralisation can promote energy resilience and reduce transmission losses.

From a technology perspective, this distributed nature of energy assets like cars, homes, and manufacturing sites is giving rise to the Intelligent Edge where analogue sensing meets digitalisation. Simply put, we need intelligence at all the critical nodes: across every energy consumption, production, distribution, and reserve modality.

Watch the full video interview with Patrick Morgan below.

Data is the lifeblood of this new technology world. To create and capture value, technology developers like ADI must interact in new ways throughout the ecosystem. Our focus is to learn and co-create, as we develop complete subsystems at the Intelligent Edge with our partners. As we grow, we are bringing in new expertise, in areas that stretch beyond the typical approaches into areas like artificial intelligence, data science, virtualisation, battery chemistry, and more. Plus, we are advancing our IP strategy to include systems and standardisation to drive the industry. In taking a holistic view of Intelligence at the Edge and in designing with the total cost of ownership in mind, we are enabling the Intelligent Edge to stretch into the key area for value creation and growth.

You might be interested in reading:
Why we need ‘intelligence everywhere’ to build the energy ecosystem of the future

There is no time to waste and with the signs of climate change all around us, a combination of innovative technology and legislation is helping us to electrify and ensure a brighter and healthier future for us all. At ADI, we look forward to engaging with the full electrification ecosystem to help realise its decarbonisation potential.

Regardless of complexities, ADI solutions aim to simplify the paradigm into Energy Conversion, Energy Management, and Energy Storage. It is our unique position in the ecosystem, across the industrial, energy, automotive and consumer markets, which provides us with a macro-to-micro perspective into the challenges and opportunities.  

Learn more:
The Future Is Electric (Sustainability Series #2) | Analog Devices

The five-year project included the deployment of 50,000 smart meters and the connection of Itron’s distribution intelligence (DI) enabled platform with Coopesantos RL’s customer information system.

With this upgrade with grid edge intelligence Coopesantos RL now has visibility and control across its diverse rural service territory, which includes mountainous and hard-to-access areas.

“Being the first cooperative to deploy smart meters in Costa Rica and Central America marks a significant step toward the modernisation of the infrastructure and distribution of electrical energy in rural areas where we provide service to all homes, businesses and industries,” said Mario Patricio Solis Solis, General Manager of Coopesantos RL.

Have you read?
Latin America smart meter penetration to triple by 2028
Costa Rica and Panama lead green hydrogen ambitions in central America

“Our electrical distribution deployment has been strengthened with this investment in technology and devices from Itron, automating and optimising our operational processes. We’re thrilled to continue working together as we embark on creating a reliable smart grid to prepare for the future.”

The solution was delivered via local Itron channel partners Conelectricas RL and Itecna.

Benefits anticipated by Coopesantos RL include more rapid insight and response to power outages with Costa Rica prone to extreme weather events, a reduced carbon footprint with reduced need for meter reading and increased client satisfaction with detailed insight into energy use and early detection of technical irregularities such as theft.

Coopesantos RL, headquartered in the city of San Marcos de Tarrazú, is one of four electric cooperatives in Costa Rica.

The cooperative claims 100% clean energy generation from two hydro plants, the 13MW Los Santos wind farm and growing distributed solar PV, primarily from commercial users.

In addition to energy generation and supply the cooperative offers fibre Internet services.

In 2023 the installed base of smart gas meters amounted to 55.9 million units and at a CAGR of 6.8% is projected to reach 77.6 million units by 2028, Berg Insight’s data indicates.

The annual shipment volumes amounted to 4.8 million units in 2023 and are expected to be around 5 to 5.8 million throughout the period.

The UK, Italy and Belgium were the most active markets, together accounting for the majority of the smart gas meter shipments during the year.

Have you read?
Italgas rolls out first 20,000 Nimbus H-ready smart meters
The need for speed on smart meter rollouts

While the rollouts in Italy, France and the Netherlands are largely completed, the UK market is ramping up yearly installations to reach a peak of around 3.3 million units per year during 2024–2025.

Belgium and Ireland also are expected to contribute with significant shipment volumes in the coming years. The Spanish market is expected to reach yearly shipment volumes of 1 million units by the end of the forecast period.

Smart gas meter networking

Berg Insight highlights how the smart gas meters deployed in Europe have been networked somewhat differently from the smart electricity meters.

A common model observed in the UK, the Netherlands and Belgium is to utilise a local wireless or wired interface to transmit gas data via the customer’s smart electricity meter.

A mix of 169MHz RF and 2G/3G cellular communications has been the primary model for the largest projects in which smart gas meters have been deployed independently of smart electricity meters, such as in Italy and France.

However, with the more ready availability of new types of LPWA technologies a shift in favour of these has begun.

Italy, for example, was the first to initiate large-scale adoption of NB-IoT as a primary smart meter connectivity choice and in 2023 the installed base of gas meters with NB-IoT connectivity in that country reached more than 2.5 million.

Berg Insight anticipates that by the end of the forecast period NB-IoT/LTE-M will become the go-to connectivity option for smart gas meters in several European markets, reaching an installed base of around 13.2 million units and accounting for as much as 60% of the annual shipment volumes.

The analyst also highlights the anticipated increase in the use of hydrogen in the European gas supply, with pilots underway in the UK and Italy with metering devices capable of measuring blend of hydrogen and natural gas or pure hydrogen and that interest in hydrogen meters is likely to increase as the technology matures.

ChatGrid, the brainchild of Pacific Northwest National Laboratory (PNNL) optimisation and grid modelling researcher Shrirang Abhyankar, was conceived to exploit the question-and-answer approach of generative AI tools to support grid operators in their decision making.

With this, the user can then ask a question such as: “What is the generation capacity of the top five wind power generators in the Western Interconnection?” with the response of a visualisation showing the desired information.

Users can ask questions about generation capacity, voltage, power flow and more, while customising the visualization to show different information layers.

Have you read?
Tech talk | On the grid edge
Europe’s grid action plan: a step in the right direction, but is it enough?

Abhyankar says the aim is to simplify the experience for grid operators who have to make many decisions as they monitor the grid in real-time.

“We’re envisioning a new way to look at data through questions. ChatGrid allows someone to query the data – in a literal sense – and get an instantaneous answer.”

ChatGrid runs on a publicly available large language model, with the input data the synthesised data from the Exascale Grid Optimisation (ExaGO) model, which was developed to take advantage of the power of supercomputing to simulate the nation’s power grid in real time.

Moreover, to further protect grid security, the model was not trained on the data itself.

Instead, the data was compiled in an internal database in columns with headings such as ‘capacity’ and ‘location’ of power plants and the model used to produce a ‘structured query language’ (SQL) that allows ChatGrid to search this database for its answers.

Work in progress

For Abhyankar, ChatGrid remains very much a work in progress.

He hopes that once grid operators start using ChatGrid and providing feedback, a better version can be built that they can then safely use in their control rooms with real-life data.

For that to work, ExaGO’s developers need the data to be useful on regular computers as well, however.

Further, while ChatGrid is available for download on GitHub, the process takes a few steps and once the feedback starts rolling in, the development of a one-step download process is anticipated.

Users also are invited to play around with the phrasing prompts and questions to assess how to produce the best answers.

The 30 millionth meter was connected to the network at midday on March 1 by E.ON.

With the average daily connection rate approaching 16,000, the number of connections is growing apace and corresponds to over 18 million homes, or about 70% of all homes now being connected.

“Reaching 30 million connected smart meters in over 18 million homes is another landmark milestone in pursuit of our purpose to make Britain more connected so we can all lead smarter, greener lives,” says Angus Flett, CEO of the DCC.

Have you read?
‘Alt HAN’ rolls out for smart metering in Britain
The need for speed on smart meter rollouts

Gill Baker, Director of Smart Field Connections at E.ON, says the company is delighted at having fitted the 30 millionth smart meter.

“[We] are equally proud to have fitted more than five million others before this one and are pleased to be part of this exciting milestone for Great Britain’s energy system.”

The smart meter network is considered a critical part of the nation’s energy infrastructure and an important platform for digitalising the power grid, enabling real-time data delivery to customers, network operators and suppliers.

With its use, the DCC estimates current CO2 savings at 1.125Mt/year.

DCC work programme

To advance its use, a range of initiatives are currently underway by the DCC, of which a key one is the migration of the more than 15 million first-generation SMETS1 smart meters to the network.

As of November 2023 (the last data available), almost 11.6 million SMETS1 meters were connected to the network.

Closely related is the central switching service, which is aimed to reduce the supplier switching to five working days and subsequently to 24 hours.

In particular, the ‘Enduring change of supplier’ (ECoS) programme is aimed at enhancing the security of a switch, with the essential component the replacement of a key on the smart meter. The migration from the previous programme to the ECoS is currently underway and due for completion in Q2 2024.

The third major initiative is the rollout of dual band communications hubs, which are intended to enable the smart meters to communicate in buildings such as apartment blocks or with thick walls where communication is not possible with the single band hubs – about 25% of British households.

These hubs use the 2.4GHz frequency of the single band hubs as well as a HAN frequency of 868MHz and are expected to open up the benefits of smart meters to these households.

Further updates on Britain’s smart meter rollout are expected with the release of the government’s annual review for 2023, which is included with the March release of the quarterly update.

Though the ‘edge’ has been talked about for years, it is increasingly taking central stage as more and more homes and businesses take up solar and battery systems, switch to electric vehicles ((EVs) and heat pumps and instal the smart appliances that are advertised as bringing more convenience to life.

In broad terms the edge is where the utility and customer meet and is effectively represented by the meter – the utility side in front of the meter and the customer side behind the meter.

With this growth of decentralised resources and the increasingly complex and unpredictable power flows, some of the risks include the likely emergence of hyper-local capacity constraints and that ageing infrastructure can be put at risk.

Have you read?
Generative AI solutions for utilities on the rise
‘We need to think smart and fast’ to future-proof the grid

But there has been what Itron has termed a ‘control gap’, with the challenge that whereas a typical SCADA manages approximately 1,000 assets per million customers and a typical advanced distribution management systems 10,000 assets, that to the point of service is a further two orders of magnitude greater at around 1 million points.

But that is changing, with the evolution of IT and other technologies opening the way for a variety of new products and services to provide visibility and control to address the challenges of the evolving grid.

Itron’s grid edge intelligence portfolio

A pioneer of edge intelligence in the energy sector, Itron has consolidated its offerings into a cloud-based edge intelligence portfolio combining connectivity, analytics and applications with intelligence for AMI operations and optimisers for the low and medium voltage grid, DERs and EVs, coupled to a central datahub.

To simplify the process the Itron Enterprise Edition has been made available in the Microsoft Azure marketplace, also opening the way for integrating the Azure OpenAI generative AI solution for users to expedite and improve visibility on data and operations.

Among the new solutions launched are Active Transformer Load and Voltage Monitoring (ATLM/ATVM) applications to enable visibility on transformer loading and voltage statistics in real-time along with configurable threshold-based alarms.

Key for broader uptake of the solutions is partnerships with other providers with these opening the way for Itron’s grid edge intelligence solutions to be integrated into Schneider Electric’s digital grid solutions and to GE Vernova’s new GridOS Data Fabric alongside the GridOS apps.

A further partnership is with the Mobility House as part of its Fast & Flexible Interconnect (FIX) programme for charging of EV fleets in constrained distribution systems.

Don Reeves, senior VP of Outcomes at Itron, reports that customers have advised that the company’s Grid Edge Intelligence portfolio can enhance grid capacity by approximately 20% through the optimisation of existing grid assets.

“Utilities are operating in a more complex environment than ever before and there is a real sense of urgency that change is needed to ensure grid reliability, resiliency and sustainability and improve the customer experience.”

Landis+Gyr and Span partnership

Landis+Gyr has announced a partnership with home electrification technology developer Span, with the first joint product combining their respective solutions to deliver a grid edge solution with circuit-level billing-grade metering, DER visibility and controls.

Describing the co-innovated solution as “a whole-home multi-asset virtual power plant (VPP)”, Werner Lieberherr, CEO of Landis+Gyr, says: “The partnership not only expands our flexibility management platform but also helps [utilities] reduce costly grid infrastructure investments required for electrification. We’re particularly excited to bring SPAN’s service upgrade avoidance capabilities and intuitive app experience … to drive energy efficiency and flexibility.”

While full details of the solution are still to be released, the companies promise to evaluate it in pilots with US utilities starting later in the year.

Siemens Gridscale X

Siemens has launched Gridscale X as a modular software to scale grid capacity and handle the complexity of DERs.

A key component of Gridscale X is DER Insights which is designed to unlock visibility over the distribution grid, with features including the location and behaviour of DERs, grid impact identification and digital grid mapping and modelling.

“With the electrification of everything and the exponential growth of DERs, there is an urgent need for increasing grid capacity fast,” says Sabine Erlinghagen, CEO Siemens Grid Software, pointing to the use of such software as enabling utilities to focus on critical infrastructure upgrades and reducing the impact and occurrence of grid equipment failure, outages and technical debt.

Users of these or similar softwares are invited to contact us with case studies.

Jonathan Spencer Jones

Specialist writer
Smart Energy International

Follow me on Linkedin

The European Commission is making available €74 million (US$80 million) in funding towards the creation of the energy and other sectoral data spaces as part of an over €176 million ($191 million) package for the Digital Europe 2023-2024 work programme.

The sectoral data spaces, a key component of the EU’s data strategy, are intended to form repositories for pooling, accessing, sharing and processing data from within the respective sectors from across the EU.

Based on common data infrastructures and governance frameworks, their evolution is being driven by users within their respective sectors.

Have you read?
Tech Talk | A framework for a European energy data space
ODEON to demonstrate data orchestration and sharing in Europe

Over time the goal is for them to be gradually interconnected, furthering the data sharing – for example, energy with mobility opening the energy sector to wider participation – and ultimately forming a single market for data that can assure Europe’s global competitiveness and data sovereignty.

Energy data space

With various initiatives well under way towards the energy data space, proposals for the 2023-2024 programme should foresee the deployment of the first version, building on these, in at least ten member states with piloting of at least five use cases in areas such as distributed energy resources management, provision of flexibility services for electricity grids or smart and bi-directional electric vehicle (EV) charging.

These should use a commonly agreed reference architecture with replicable and scalable building blocks, e.g. on data models and formats, data exchange APIs, data provenance and traceability, metadata, etc.

In particular regarding data interoperability arrangements, the data space should be based on agreed minimal interoperability mechanisms that will align energy-relevant key stakeholders on a set of minimal sufficient capabilities needed to achieve interoperability of data, systems and services between the key players of the energy value chains at all levels, i.e. European, national and local.

Another requirement is the consideration of a complete set of open standards, while other deliverables required are the definition of suitable business models that can ensure financial sustainability of the energy data space beyond the end of the project and the implementation of a governance system for overseeing its operations.

An amount of €8 million ($8.7 million) is allocated for this energy data space advancement, which is expected to take place over 36 months.

In addition to the support for the data spaces, the €176 million package includes funding to advance research and use of artificial intelligence, for projects on the cloud to edge infrastructure and for skills development.

Since the deployment began in October 2022, Vodafone Spain has already connected more than 250,000 meters to its NB-IoT network and the initial target is to complete connections to over 1 million water meters during the first 5 years of the contract.

Aqualia’s goal is to offer remote meter reading and other services to its over 3 million customers in Spain in the coming years.

Daniel Barallat, director of IoT at Vodafone Spain, says the control and management of water use in Spain is a constant and vitally important challenge today.

Have you read?
EMASESA to deploy 77,300 smart water meters in Seville
Spain offers lessons on how to balance Europe’s energy transition

“With this contract, we put our most cutting-edge technology at the service of Aqualia to actively contribute to the better conservation of natural resources and more efficient water management.”

The initiative is being undertaken as part of the government’s Strategic Project for Recovery and Economic Transformation (PERTE), which is aimed to modernise the urban water systems to improve efficiency, reduce losses in the distribution systems and improve the wastewater treatment infrastructure.

Vodafone’s Water Meter solution for homes, businesses and public institutions includes the digitalisation of the meters and the reading and analysis of the data.

In a pilot currently underway in the city of Vigo, Aqualia and Vodafone are investigating the use of the remote meter read data for detection of fraudulent activities such as tampering and reverse flow and for leak detection with hourly water balance analyses, with the aim to develop a comprehensive solution.

It is also intended to provide the data to customers to enable them to become aware of their consumption and to use the data for the prediction of consumption patterns to improve water management and broadly make the cycle more sustainable.

For example, with optimised pumping in turn the energy consumption is optimised and stresses on the network reduced, which also should reduce the risk of breakage and leaks and the loss of non-revenue water.

NB-IoT is the preferred communication for water meters in Spain as many are underground or in other outdoor locations.

The company has been piloting the software 1Streetworks, which provides traffic management plans, with the finding that the average time taken to connect new or altered power connections was reduced by a quarter across approximately 300 Surrey roadworks sites where it was used.

Based on this outcome UK Power Networks is now planning to roll out the technology in a larger one-year trial in Kent to test its use in other workstreams across the company.

“Planning streetworks to the high standards we expect takes time and few have tried to revolutionise the process during my 23 years in the sector,” says Paul Dooley, streetworks performance manager at UK Power Networks.

“So, I’m excited about the potential of 1Streetworks to streamline complex traffic management plans, enable better communication with customers and highway authorities and improve the speed and accuracy of streetworks plans.”

Have you read?
Why a UK consortium is bidding on geospatial planning for net zero
Mapping the future of utility networks

Traditionally a streetwork design plan for a smaller power connection, overhead line or underground cable repair usually needs a surveyor to assess the site, take measurements then plot signage on a CAD system – a process that can take hours of work, with the need to maintain high levels of safety and accuracy and to meet industry regulations.

The cloud-based 1Streetworks from the Cambridge headquartered location and geospatial data specialist 1Spatial is stated able to produce similar plans on-site in under two minutes.

Once the user plots the location of the work on a map, the software instantaneously plans site-specific traffic management, integrating layers of maps with main roads, bus stops, lane rental and streetworks rules.

Claire Milverton, CEO of 1Spatial, said the pilot has been a key milestone for the company and a culmination of many years of work and investment.

“We are delighted that our innovative 1Streetworks application has delivered such fantastic results for UK Power Networks and its customers. We look forward to roll out the software further across the network over the coming months.”

UK Power Networks has 190,000km of cables and delivers thousands of streetworks every year across London, the southeast and east of England.

On average there are over 4 million low-speed road works undertaken in the UK each year.

1Streetworks was developed initially with GB gas network operator Northern Gas Networks for expediting works on its underground pipelines.

The increasing complexity of power grids with high levels of inverter-based variable renewables and unpredictable electric vehicle charging patterns has brought with it challenges for power grid operation and the need for real-time control as key for maintaining voltage stability.

Based on deep reinforcement learning – a subset of machine learning – the new algorithms are designed to solve this challenge by delivering intelligence to power converters in the grid utilising what the researchers describe as a novel data synchronisation strategy to optimise the large-scale coordination of energy sources safely under fast fluctuations without real-time communication.

“Centralised control is not cost-efficient or fast under continuous fluctuations of renewable energy and electric vehicles,” says Qianwen Xu, one of the researchers involved in the project.

Have you read?
It’s time for a new era of low voltage grid management
How digitalisation can solve grid challenges for TSOs

“Our purpose is to improve control strategies for power converters, by making them more adaptive and intelligent in order to stabilise complex and changing power grids.”

The research, which was demonstrated in KTH’s smart microgrid hardware platform and published in the IEEE Transactions on Sustainable Energy, proposes a projection-embedded deep reinforcement learning algorithm to achieve decentralised optimal control with guaranteed 100% safety.

This is intended to overcome the challenge of existing deep reinforcement learning methods in power system applications of not being able to achieve optimal performance and guarantee safe operation at the same time.

In essence, the approach of the researchers is to formulate the grid control problem as a deep reinforcement learning problem with hard physical constraints and then based on this to project a multi-agent algorithm onto a set of constraints characterised by the physics of the distribution system.

With this, the proposed method can achieve the optimal control of the distribution system in a decentralised manner without real-time communication while guaranteeing the physical constraints of the system all the time. As such, it is thus flexible for scalability and practical deployment.

The research formed part of KTH’s Digital Futures Centre which collaborates with researchers from the Universities of California, Berkeley and Stockholm University.

Deep reinforcement learning combines deep learning and reinforcement learning and has been developed for application in complex, unpredictable systems.

The first radio site successfully started operation at E.DIS north of Berlin in late 2023, with the first use case for smart metering.

With this E.DIS is no longer dependent on the availability of public mobile networks and intends to gradually transition its smart grid applications to the 450MHz network as the buildout in Germany grows towards expected completion in 2025.

Dr Alexander Montebaur, CEO of E.DIS Netz parent group E.DIS AG in turn part of the E.ON group and Deputy Chairman of the Supervisory Board of 450connect, who played a leading role in the developments around the 450MHz network in the group, commented that E.DIS subsidiary e.discom Telekommunikation was involved in the first pilot tests of the 450MHz network.

Have you read?
450MHz network to be built out for critical infrastructure in Germany
Is Germany’s grid renewables ready?

“The introduction of the 450MHz network is an important milestone for us in order to ensure and improve communication in the energy sector in a crisis-proof manner under the constantly growing requirements such as e-mobility and the connection of numerous renewable energy plants and to drive digitalisation forward,” he said.

“We are convinced that this technology will help us to successfully meet the challenges of the energy transition.”

The 450MHz band – formerly known as the C band – has gained growing interest for military and other critical applications with characteristics such as strong signal penetration and suitability for large scale IoT applications.

While interest in the band is widespread globally, in Germany its use has been awarded to the energy and water sector backed 450connect, an organisations with equal shareholdings by Alliander, E.ON, the 450MHz consortium of regional energy suppliers and the Utility Alliance 450 of small energy and water supply companies.

The German network is being deployed by Nokia, which also is contracted for other services including maintenance until 2040.

Other key features include a dual-use role with normal operation being monitoring and control of critical infrastructures and in times of crisis for communication and other critical control measures and being backed up with a 72-hour emergency power supply in the event of power outages and enabling information exchange for speedy service restoration.

E.DIS Netz is one of the largest regional energy grid operators in Germany and operates a power grid of around 79,000km in Brandenburg and Mecklenburg-Western Pomerania.

With the publication, the data, which has been aggregated to a minimum of five smart meters on an individual feeder, is now available for access by interested parties such as local authorities, flexibility providers or academia for modelling and planning.

With the publication also, SSEN has become the first of Britain’s network operators to make such data available, having pioneered the development of an ‘open data’ portal for distribution data in the country.

“These are exciting times for accessing and utilising smart meter data. SSEN is delighted to be the first DNO to unlock the full consumption datasets at such a granular level, and to make them available on our open data portal for interested parties to access,” says Paul Fitzgerald, Smart Energy Systems Manager at SSEN.

Have you read?
GB’s Scottish and Southern Electricity Networks opens up energy data
Creating data space with smart meter hubs

“Smart meter data plays a key role in supporting a cost-effective and efficient transition to net zero. As we decarbonise heat and transport and move towards low carbon technologies, knowing current demand on the electricity network will help identify new opportunities for low carbon technologies, flexibility and reinforcement.”

SSEN has over 1.8 million smart meters – about 54% coverage and increasing daily – in its two distribution areas in the north of Scotland and across central southern England recording active and reactive half-hourly consumption.

This equates to over 170 million readings per day with the opportunity for insight into 84,000 LV street-level feeders and over 36,000 distribution substations.

The systems to process and aggregate this large volume of data for publication on a daily basis were developed with CGI as SSEN’s ‘DCC adapter’ – the intermediary enabling the supplier to connect and communicate with the Data Communications Company’s (DCC) smart meter network.

A key aspect was around the methodology for sharing the data in a consistent manner and in particular aggregation to protect individual consumer privacy.

In collaboration with the other network operators agreement was reached on an aggregation level of five or more smart meters from an individual circuit on the low voltage network, with any less than five meters or sensitive sites, following data triage, being excluded.

Other top initiatives are renewable energy integration, grid modernisation and microgrids and disaster response and recovery plans.

Furthermore, the utilities are adopting new approaches to improve outage recovery times through advanced networking, with predictive maintenance analytics topping the list, followed by smart grid technologies and enhanced communications, as well as the use of drones and robotics to inspect assets.

Phil Beecher, President and CEO of the Wi-SUN Alliance, comments that extreme weather events are fast evolving from a rare occurrence to something that should be built into the risk profile of any utility company.

Have you read?
ESB Networks to use digital twin to mitigate weather impacts on the grid
Extreme weather pushes power grids to the brink – Is AI the answer?

“The emergence of smart grids, microgrids and other technologies, like predictive maintenance and fault finding, offers a way of controlling costs while increasing resilience and stability to help mitigate the impact of outages.”

But, he adds, “technologies like this are only as good as the underlying communications network to provide reliable and secure delivery of the data needed to deliver a truly smart grid.”

The research was conducted among more than 250 senior professionals in the US utilities and power sectors and highlights the role of new tools and technologies to help improve resilience and outage recovery times as weather events and environmental disasters become commonplace.

According to US Department of Energy data cited by the Wi-SUN Alliance, extreme weather conditions – from heatwaves to Arctic vortexes – have doubled power outages in the US over the past 20 years.

The research also founds that utilities recognise opportunities to integrate artificial intelligence technologies to address resilience, with viable use cases including energy consumption forecasting, automated fault detection and grid optimisation.

Looking ahead to the next five years building infrastructure resilience remains among the top issues, with others including security enhancement, customer-centric services, renewable energy integration and IoT integration and data analytics.

The study was conducted for the Wi-SUN Alliance by Censuswide in February 2024.

The rollout follows the regulatory approval given in September 2023, which authorised up to $153 million for the initiative and forms part of Rhode Island Energy’s grid modernisation activities to enable the integration of renewable energies to support the state’s climate goals.

The Revelo metering platform features grid edge sensing and edge computing capabilities to manage load and support grid troubleshooting, with the Revelo meter operating on Landis+Gyr’s RF Wi-SUN network.

Additionally, the advanced grid-edge processing allows for greater consumer engagement with applications such as real-time load disaggregation and pricing information.

Have you read?
Smart metering and demand response continue to increase in US
How digitalisation can solve grid challenges for TSOs

“The Commission’s approval to implement our advanced metering plan is an important step in modernising the state’s energy infrastructure for the benefit of all Rhode Islanders,” said Dave Bonenberger, president of Rhode Island Energy, of the approval.

With the prospect of being able to benefit from parent company PPL Corporation’s other smart meter rollouts in Pennsylvania and Kentucky, he continued: “We’ve seen the success of these new technologies across other PPL service territories, and customers should be excited about the advantages they’ll bring to their homes and businesses.”

The rollout is timely as approximately 60% of the electricity meters across the state are nearing the end of their design life and need to be replaced.

Before the start of the rollout, which is expected to begin in 2025 and to be completed over the following three years, Rhode Island Energy intends to engage customers to provide more details about the technology in advance of installation, as well as an opt-out option.

In October 2023 Rhode Island Energy was selected to potentially receive up to $50 million in federal funding from the Infrastructure Investment Act towards its almost $300 million smart grid investment programme to improve visibility and control on its grid.

Among the plans are advanced distribution management and energy management systems and a centralised asset hub data system and geographic information system to represent a digital twin of the grid.

Generative AI appears to be attracting as much interest in the energy sector as it is concerned.

New data from IBM, unveiled at DISTRIBUTECH International, indicate that almost three-quarters of energy and utility companies surveyed have implemented or are exploring using AI in their operations.

Moreover, in an earlier survey two-thirds of energy and resource CEOs felt they are more likely than their global peers to expect to realise value in the next three years from generative AI and automation.

However, an almost similar percentage expressed concerns about the sources of data used in generative AI.

Have you read?
Siemens brings generative AI to predictive maintenance
The EU Projects Zone Podcast: Using AI to boost the grid and renewables

As the latest iteration of AI, generative AI is attracting much interest in the energy sector, as elsewhere, with tentative steps being taken as utilities investigate use cases where it can add value.

Itron integrates Microsoft Azure OpenAI

So far few energy solution providers have incorporated generative AI into their offerings and among the frontrunners is Itron, which ahead of DISTRIBUTECH 2024 announced what should prove a significant innovation for the sector with its integration of the Microsoft Azure OpenAI service.

Initially, the integration of the OpenAI service – which is based on the same model as ChatGPT – is with the Itron Enterprise Edition Meter Data Management system, distributed intelligence applications and Itron’s cloud-based DataHub platform, which is intended as the common access point for all data from the company’s portfolio.

This includes data created by Itron as well as that from third-party DI applications, such as load disaggregation, transformer connectivity and loading data.

With the OpenAI solution users should be enabled to get answers to questions, perform tasks, access data across the MDM and on the DataHub and for example use plain language queries to generate charts and reports as well as receive suggestions and feedback to improve data quality, accuracy and analysis.

“Through this collaboration [with Microsoft], we will enable utilities and cities to leverage the power of generative AI to boost efficiency, unlock creativity and enhance data management,” said Don Reeves, Senior Vice President of Outcomes at Itron.

IBM’s watsonx governance

While IBM’s watsonx generative AI and data platform for utilities and other enterprises was announced in May 2023, the latest addition to it is the governance toolkit that is designed to allow users to direct, manage and monitor their AI.

In particular, it is aimed to strengthen a company’s ability to detect and mitigate risks, manage changing regulatory requirements and address ethical concerns for both generative AI and machine learning models.

Casey Werth, IBM Global Energy Industry General Manager, says that as energy and utility CEOs manage their ongoing transformation efforts, they can also capitalise on the opportunities of generative AI and foundation models.

“In doing so they need to remember to focus on their own data, how it is gathered, accessed and used within their workflows along with the governance that should be baked into their tools and processes.”

This content is password protected. To view it please enter your password below:

Password:

i-DE is testing the technology on its distribution network in Vizcaya province near Bilbao in the Basque region of Spain, where Iberdrola is headquartered, throughout 2024.

If the trial’s outcome shows improvement in i-DE’s processes, including supporting its vegetation management strategy, enhancing network reliability and aiding wildfire prevention, the technology could be further rolled across the company’s network areas.

The LiveEO Treeline satellite software solution is designed to improve vegetation risk assessments, including modelling and predicting vegetation growth as well auditing previous work.

Have you read?
Space data increasingly important for smart grid – EUSPA
Harnessing the power of the EU’s Space Programme for renewable energy

The AI-based package is designed to identify and evaluate all forms of vegetation risks based on satellite data that is processed on a near real-time basis, to enable identification and response to emerging risks as they occur.

LiveEO, regularly named among the top 100 geospatial companies, states its Treeline solution can deliver results including a 15% reduction in vegetation-related outages, a 20% reduction in contractor cost per km and a one-year return on investment.

Other utilities that have deployed the solution include Iberdrola subsidiary Avangrid, Dominion Energy and Liberty Utilities in the US and E.DIS in Germany.

Data from earth observation satellites is becoming an increasingly important element of utility datasets, with vegetation management being a key use case and others including planning and design of new renewables projects, while other space-based data is available for positioning and timing use cases.

The rollout of the Rometrix 2G smart meters was launched in October 2020, with the goal to replace the approximately 1.7 million meters in Rome and neighbouring municipality Formello by the end of 2025.

Since the end of January, as of the day of writing a further almost 21,000 smart meters have been deployed.

In a statement from Acea, the Rometrix 2G smart meters are stated to represent a significant turning point in the way energy consumption is managed and monitored, allowing greater transparency in consumption, as well as the possibility of optimising energy efficiency and reducing waste.

Have you read?
RomeFlex launches flexibility services in Italy’s capital
The EU Project Zone Podcast: Project Platone with Antonello Monti

Through the installation of these smart meters, Rome is moving towards becoming a sustainable and intelligent city, in line with the vision of the Acea Group which considers the use of energy in a responsible manner as essential.

The Rometrix 2G smart meters provide reads on a 15-minute basis, which are transmitted to Areti’s central system and from there delivered to suppliers for invoicing.

The primary communication is PLC in the Cenelec A band (9-95kHz).

Customers with smart meters are then able to activate the ‘Chain 2’ service to access their consumption data and start enabling home automation services.

Towards the delivery of new consumption models Areti was a participant in the PlatOne Horizon 2020 project, coordinating the Italian pilot to investigate blockchain-based flexibility mechanisms with smart meter customers.

Findings from that project have now been incorporated into the newly launched RomeFlex project also using a blockchain model focussed on the delivery of flexibility in congestion and voltage management.

North America’s National Association of Regulatory Utility Commissioners (NARUC) partnered with the US Department of Energy’s Office of Cybersecurity, Energy Security and Emergency Response (CESER) to develop a set of cybersecurity baselines.

Coupled with forthcoming implementation guidance, the baselines are intended as resources for state public utility commissions, utilities and DER operators and aggregators, encouraging alignment across US states on energy cybersecurity.

Regulatory oversight of electric distribution systems and DERs occurs at the state level in the US. The guidance developed by NARUC through CESER’s funding, will help provide states with uniform cybersecurity baselines instead of a patchwork of cybersecurity requirements across the country.

Further, the baselines will enable electric companies and DER providers to work with state utility commissions and energy offices, boards and communities to prioritise cybersecurity investments across the US.

The guidelines, to be developed in 2024, will include recommendations for assessing cybersecurity risks and prioritising assets the baselines might apply to.

“Safeguarding America’s energy infrastructure and advancing US cybersecurity capabilities is critical to achieving President Biden’s ambitious climate goals,” said US Deputy Secretary of Energy David M. Turk in a DOE-issued release.

“Today’s announcement underscores the Biden-Harris Administration’s commitment to working with key partners, like NARUC, to develop vital cybersecurity solutions and strengthen the resilience of America’s electric systems.”

Have you read:
Energy cybersecurity in 2024: Building accountability and responsibility
Cybersecurity standards to be developed for EU distribution systems

The growing cyber threat

The baselines represent the growing urgency of cybersecurity across sectors in the US.

In the DOE’s statement on the baselines, they state that cyber threats have been increasingly sophisticated and target critical energy infrastructure more frequently than ever before.

Earlier in February, the US Cybersecurity and Infrastructure Security Agency (CISA), National Security Agency (NSA) and Federal Bureau of Investigation (FBI) released a cybersecurity advisory on the threat posed specifically by cyber actors sponsored by the People’s Republic of China.

The advisory assessed that these Chinese state-sponsored cyber actors are seeking to pre-position themselves on IT networks for disruptive or destructive cyberattacks against US critical infrastructure, including energy, in the event of a major crisis or conflict with the country.

The assessment was based on observations from incidents at critical infrastructure organisations compromised by the cyber group known as Volt Typhoon, warning infrastructure organisations, such as the DOE, of the threat.

According to the advisory, agencies observed indications of Volt Typhoon actors maintaining access and footholds within some victim IT environments for at least five years, conducting pre-exploitation reconnaissance to learn about the target organisation.

According to NARUC, the initiative recognises that cybersecurity is an integral underpinning of power system resilience and builds on work that states have undertaken over the last decade to mitigate risk across their critical infrastructures.

The cyber baselines are based on DOE’s work on energy sector cybersecurity and the US Department of Homeland Security’s Cybersecurity Performance Goals (CPG).

NARUC convened a steering group of industry and government subject matter experts, including electricity sector owners and operators, state regulatory agencies, cybersecurity experts and others to inform the baselines.

GridOS Data Fabric, claimed a first for grid orchestration, uses data federation to access the decentralised data, enabling multiple datasets to be combined and then virtualised to create a centralised view across the grid ecosystem, from transmission to distribution and the edge and across information technology and operational technology applications.

With this grid operators should be able to discover, govern and utilise large volumes of highly distributed data from multiple sources for improved and more rapid decision making while orchestrating the grid in real time.

“Energy data plays a key role in delivering a more efficient grid. Utilities will need to connect energy data from across the grid ecosystem to effectively automate grid operations, orchestrating more intelligent, secure and resilient grid that is ready and built for future electrification needs,” says Mahesh Sudhakaran, General Manager at GE Vernova’s Grid Software business.

Have you read?
How AI and advanced analytics will be key for the grid of tomorrow
‘We need to think smart and fast’ to future-proof the grid

“By leveraging energy data, AI and machine learning powered technologies, utilities can move at speed to meet demand while addressing renewables management and electrification challenges.”

The GridOS strategy is centred around a modular, composable, data-driven software portfolio designed to orchestrate a more sustainable energy grid and help utilities keep pace with the energy transition, a GE Vernova statement says.

The announcement of GridOS Data Fabric, which follows GE Vernova’s acquisition of Greenbird Integration Technology and is the first major addition since the launch of GridOS a year ago, also includes GridOS Connect.

GridOS Connect is an energy data integration engine as a key component for the federated grid data fabric that feeds continuously updated data sets into the system – information that traditionally has been difficult for utilities to compile and analyse.

Itron collaboration

With the release, GE Vernova also has announced a collaboration with Itron, which intends to leverage GridOS Data Fabric to connect grid operations and grid edge data from sources such as residential solar, electric vehicles and more.

Don Reeves, Senior Vice President of Outcomes at Itron, says that a key component of the GridOS Data Fabric software is its ability to connect and integrate data to make more accurate real-time decisions to enable a reliable and resilient grid.

“The data to be exchanged with Itron’s grid edge intelligence solutions can provide new insights to promote grid stability and to train and power AI and machine learning applications that help automate key aspects of the grid operation.”