Insights

Home Energy Management Systems: The Future of Smarter Grid Operations

One51 — Sun, 28 Jun 2026 16:30:56 GMT

The Energy industry is evolving rapidly, shifting from a one-way linear power flow to a dynamic, two-way ecosystem. Enhancements in technology have been a key driver of this evolution, including the rise of Distributed Energy Resources (DER). DER assets include PV Solar Panels, Batteries, and EV Chargers. As DER expands across the grid, it poses challenges for Distribution Network Service Providers (DNSP) to handle. Firstly, an oversupply of energy can lead to power outage issues, and secondly, the sheer volume of telemetry data being outputted due to the large amount of edge devices across the network leads to a data management challenge. The industry has started to adopt Home Energy Management Systems (HEMS) as an approach to bridge the gap between siloed home appliances and convert them into orchestrated, cohesive, data driven grid resources.

The Telemetry Explosion: Shifting to a Medallion Architecture

With advancements being made in the industry, requirements of the utility systems are also shifting. For example, the volume of data is vastly different now compared to what was seen historically. Instead of capturing 1 data point per quarter for a basic meter or 1 data point every 30 minutes for a smart meter, HEMS devices can stream telemetry data near real-time. To be able to handle large data workloads, DNSP’s need to move away from legacy data architecture and introduce modern cloud-based medallion architecture. DNSP’s also need to invest in a robust data transfer workflow which bridges Operational Technology (OT) networks and Information Technology (IT). The HEMS data will feed directly into the OT network. For business users to be able to access this data outside of the control room, the data will need to be moved into an IT environment. It is important that a secure data transfer process (OT to IT) is designed and monitored. Implementing a secure OT to IT bridge will unlock analytical and strategic value for DNSP’s, while maintaining the physical security of the grid.

Beyond the Inverter: Eliminating the Behind-the-Meter Blind Spot

One method DNSP’s use to stabilise the grid is by curtailing consumer exports. This operation is performed by the distributor communicating with the end user’s smart inverter and throttling the export limit. Although, a limitation of this operation is the distributor cannot see anything behind the meter. The consumer may have several edge devices that lose their value when a curtailment is taking place. This is where HEMS can add more value for both the customer and the grid overall. With a HEMS system installed, it will be visible what edge devices are present at the site and energy can be repointed into those devices, rather than it being curtailed or spilled into the grid. As a result, consumers can save money on their energy bills and can participate in virtual power plants (VPP). For distributors they have a better understanding of the overall landscape of devices present at every site with a HEMS system. Additionally, DNSP’s do not have to make any capital investments on physical infrastructure, as the investment is purely within digital data platforms.

The Path Forward: Data as the Ultimate Grid Asset

Ultimately, the rise of HEMS and intelligent edge devices demonstrates how fundamentally the energy industry is changing. Modern data platforms are no longer just a backend support tool; they are a mission-critical core component of how DNSPs must operate moving forward. Transitioning to a cloud-based medallion architecture and establishing a robust, secure data transfer workflow between OT and IT environments gives utilities unprecedented analytics capabilities outside the control room while keeping the physical grid entirely secure. By unlocking complete visibility of the decentralised network edge, DNSPs can defer massive capital investments, eliminate the behind-the-meter blind spot, and deliver real financial value back to their customers. Building this secure, scalable data foundation is the ultimate key to success for both modern distributors and the communities they serve.

Moreover, Home Energy Management Systems transform the grid from a reactive infrastructure into a coordinated, data-driven energy ecosystem where visibility and orchestration unlock real operational and customer value.

To explore how your organisation can design and implement secure OT–IT data platforms that unlock the full potential of HEMS and modern grid operations, contact One51 today.

Ready to unlock the full potential of HEMS?

Contact the One51 team to start the conversation.

Four Key Takeaways from Australian Energy Week 2026

One51 — Mon, 22 Jun 2026 15:01:55 GMT

After two days attending the recent 2026 Australian Energy Week, one thing became clear: while the energy industry is dealing with no shortage of challenges, many organisations are wrestling with the same underlying questions.

Working the exhibition floor gave us the opportunity to speak with people from network operations, asset management, engineering, digital, strategy and executive teams. The specifics varied from conversation to conversation, but four themes surfaced repeatedly. They also happen to sit at the intersection of where data, technology and network operations are increasingly converging.

IT/OT Convergence Is No Longer a Future Initiative

IT/OT convergence has been on industry roadmaps for years, but it feels like many network businesses have reached the point where it can no longer be treated as a standalone transformation program.

As networks become more dynamic, decisions increasingly depend on bringing together operational and enterprise data that historically lived in separate worlds. Asset information, outage data, network telemetry, planning models and customer insights all need to work together in ways that many organisations weren’t originally designed to support.

What we heard repeatedly was that the challenge is rarely a lack of data. Most networks have invested heavily in collecting it. The difficulty lies in creating a consistent, trusted view across systems, teams and business functions.

For many organisations, the next generation of use cases—whether that’s advanced analytics, operational decision support or AI—depends less on new technology and more on solving some of these long-standing integration challenges. The networks making the strongest progress appear to be treating IT/OT convergence as a capability-building exercise rather than a technology deployment.

Asset Management Is Becoming More Predictive

Asset managers have always relied on data, but the conversation is increasingly shifting from visibility to foresight.

Predictive maintenance, fault detection, and asset health analytics featured in discussions throughout the week. Not because the concepts are new, but because organisations are moving beyond pilots and asking how these capabilities can be embedded into day-to-day operations.

The focus has become more practical. Rather than debating whether machine learning can identify emerging asset issues, people are asking how predictions fit into maintenance planning, how confidence can be measured, and how operational teams can trust and act on the outputs.

Computer vision was another recurring topic, particularly for inspection programs and defect identification. Many organisations are now sitting on growing volumes of imagery and sensor data and are looking for ways to extract more value from it without simply creating another stream of information that requires manual review.

Underlying all of this is a desire for better asset visibility. As networks become more complex and operating conditions become less predictable, static asset records are no longer enough. The organisations gaining traction are building a more continuous understanding of asset condition and network behaviour, allowing them to intervene earlier and allocate resources more effectively.

AI Is Expanding the Conversation

Unsurprisingly, AI was impossible to avoid, but the conversations were more nuanced than the headlines would suggest.

A lot of attention was focused on agentic AI, operational copilots and conversational interfaces that can help people interact with data more naturally. For many organisations, the appeal isn’t necessarily full autonomy. It’s the ability to make information more accessible to engineers, planners, operators and field teams without requiring them to navigate multiple systems or rely on specialist analysts.

At the same time, there was strong interest in more established techniques such as machine learning, forecasting and computer vision. These capabilities continue to deliver value across asset management, defect detection, demand forecasting and network operations, and many organisations are focused on scaling proven use cases rather than chasing the latest trend.

What emerged from these conversations was that agentic AI and traditional data science are not competing approaches. They solve different problems and, in many cases, complement each other. Machine learning models might generate forecasts, risk scores or asset insights, while agentic AI provides a more intuitive way for people to discover, interpret and act on that information.

The common challenge remains the same: data quality, governance and integration. Whether an organisation is deploying computer vision models, predictive analytics or AI copilots, the value of any solution ultimately depends on the quality and accessibility of the underlying data. As several attendees pointed out, making data easier to access is only useful if people can trust what they’re seeing.

The DNSP-to-DSO Transition Is Moving from Theory to Practice

The most strategically important discussions weren’t necessarily about technology at all. They were about the changing role of distribution networks in a power system that is becoming increasingly decentralised, dynamic and customer-driven.

For a long time, DSO concepts have largely existed in industry reports, regulatory discussions and future-state operating models. What felt different this year was how often elements of that future state appeared in practical conversations about planning, operations and investment.

The traditional model of electricity flowing from large generators through transmission networks to passive consumers is steadily giving way to something far more complex. Distribution networks are now managing growing volumes of rooftop solar, batteries, electric vehicles and other distributed energy resources, all of which are changing how power flows through the system.

Against that backdrop, there is growing recognition that the future role of distribution businesses extends beyond managing poles and wires. Increasingly, they will be expected to coordinate a much broader system of network assets, flexible demand, customer energy resources and distributed generation.

A common thread across industry discussions is the opportunity to unlock more value from infrastructure that already exists. Better utilisation of network capacity, combined with more active participation from consumer energy resources, has the potential to reduce system costs, improve reliability and provide greater flexibility as the energy transition accelerates.

That shift also requires a different approach to planning. Rather than relying solely on top-down forecasts, networks are increasingly looking to combine system-wide planning with much richer visibility of local demand patterns, constraints and emerging customer behaviour. As distributed resources continue to grow, understanding what is happening at the edge of the network becomes just as important as understanding what is happening at the centre.

The transition to a DSO model is ultimately much bigger than a technology upgrade. It represents a structural evolution in how distribution systems are planned, operated and coordinated with the wider electricity system. The details are still being worked through across the industry, but there is growing consensus that this direction of travel is becoming increasingly difficult to avoid.

Looking Ahead

Australian Energy Week didn’t answer every question facing the industry, but it did highlight a noticeable shift in mindset. The conversation has moved beyond whether change is coming. The focus now is on how networks adapt, build capability and deliver through it.

If these themes resonate with what you’re seeing in your own organisation, we’d be glad to continue the conversation.

At One51, we work with energy and infrastructure teams to turn complex operational and data challenges into practical, scalable capability—from IT/OT integration through to analytics, AI and modern network decision systems.

Get in touch with us to explore how your organisation can move from insight to impact.

Ready to turn energy network challenges into practical outcomes?

Contact the One51 team to start the conversation.

Getting the foundations right with Microsoft Purview

One51 — Mon, 15 Jun 2026 14:00:00 GMT

Purview can deliver on its promise of a unified data governance platform, but some early architectural decisions are harder to unwind than they look. Here is what is worth thinking through before you start.

AI Harnesses: Turning Model Intelligence Into Business Outcomes

One51 — Tue, 09 Jun 2026 14:00:00 GMT

For most of the generative AI cycle, AI products were essentially chat interfaces. You opened a window, asked a question, and the model replied. In that world, the obvious path to improvement was waiting for a better model. Better reasoning, larger context windows and stronger instruction-following all translated directly into a better user experience.

Microsoft Fabric alongside a legacy platform: Where to start

One51 — Mon, 08 Jun 2026 14:00:00 GMT

Most organisations don’t get to start with a blank slate. A full migration from a legacy data platform to Fabric is a significant commitment, and often the appetite simply isn’t there yet. So how do you start getting value from Fabric today, without waiting for a migration that may never come?

Building trust and increasing usership for a self-serve reporting platform

One51 — Mon, 01 Jun 2026 14:00:00 GMT

Every BI team eventually faces the same question from their users:“Where does this data actually come from?”

Unlocking Utility Graph Network Intelligence with Databricks + GraphFrames

One51 — Mon, 25 May 2026 14:00:00 GMT

Utilities have spent decades building reliable Geographic Information Systems (GIS) as systems of record to capture assets as they exist in the field. These GIS platforms are highly effective in supporting operational monitoring and day-to-day management of the network. However, modern grid management now requires grid-level analysis across connected assets, not just operational reporting. They now require the capability to compute, validate, and reason over the network at scale—covering its present state, how it has evolved over time, and how it may evolve in the future. This shift moves GIS beyond a static system of record, positioning it as the foundation for network intelligence within utilities.

WEEKLY AI NEWS – 22 May 2026

One51 — Thu, 21 May 2026 14:00:00 GMT

1. Databricks Genie Powers Industry Solutions

Why we picked this: Pinned as priority: published by Databricks (priority topic for our team).

The manual processes holding property operators back, and how AI is changing that

One51 — Tue, 28 Apr 2026 14:00:00 GMT

Why property is primed for AI, and why most efforts stall

Property operators in 2026 are not short of data. Buildings generate it continuously: maintenance requests, lease events, utility readings, inspection records, contractor updates, compliance obligations. The problem is rarely volume. The problem is that this data sits across disconnected systems, reconciled manually, and rarely assembles into a clear picture in time to act on it.

How Infrastructure as Code Enabled a Smarter Energy Network

One51 — Tue, 07 Apr 2026 06:26:07 GMT

Being part of the modern energy market comes with huge challenges. It is not about managing a few centralised energy sources and providing power in one direction anymore, the network is decentralised in millions of Distributed Energy Resources, renewables, rooftop solar panels, home batteries and electric vehicles. Energy flows in two ways: scalable cloud computing is often required to ingest and process the amount of telemetry data provided by IoT devices, smart meters, sensors and automated substations to assist in predictive maintenance, forecasting and end user applications that showcase daily energy consumption and costs. The hyper-volatility of the energy market demands constant updates on energy trading platforms and a digitized grid requires cyber security, compliance with regulatory frameworks and disaster recovery capabilities.

Manual intervention alone is no longer sufficient. Delays in provisioning can lead to operational and financial impacts, dissatisfied customers and even outages. Underlying technology has become critical to grid reliability and performance. It is increasingly difficult to meet modern standards without automation.

Laying the groundwork for a modern energy platform

Terraform and Infrastructure as Code (IaC) solve these issues by providing a framework that automates the provisioning of infrastructure through reusable templatesfollowing enterprise policies, best practices and reference architectures. This provides a solution featuring:

Speed: infrastructure provisioning can be reduced from days or weeks to minutes as there is no need to deploy resources by hand, the same applies to their decommissioning.
Reliability: recovery can be accelerated through automated redeployment.
Auditability: supports auditability and contributes to compliance requirements.
Security: policies are embedded in code, so it reduces the risk of misconfiguration through policy-driven deployment.
Error mitigation: as templates follow the standard testing procedures before release, no infrastructure settings are configured by hand and chances of human error are greatly reduced.

From cloud to code: bringing the platform to life

Following the diagram, the flow is comprised of:

Source Control and Continuous Integration: The Terraform code for the resource modules, variables and configurations (IaC) is committed to the Azure DevOps repository. Versioning is handled by the platform using Git Tag commits pushed by the developers, these ensure what is promoted to production.
Orchestration and State (Terraform Cloud): TFC is in control of the different workspaces for the development, staging and production environments. It also stores the state file, tracking the current and desired state of infrastructure in Azure and helping prevent conflicting changes through state management and locking.
CI/CD Flow: a plan is triggered in TFC on every commit, checking syntax errors and previewing changes on Azure (CI). In CD, an approved plan (manually or via tags) is then applied.
Deployment (Azure): using the Azure Resource Manager API, Terraform communicates with the Azure cloud to provision the physical infrastructure being managed.

It is important to mention as well that stacks are created in the Terraform Cloud to group different resources or modules that integrate an enterprise platform. This way it is possible to deploy a full solution through automated pipelines aligned with predefined company standards, policies, and configurations. These could be entire applications or data platforms that consist of compute, databases, networking, secret vaults and storage.

Turning infrastructure into competitive advantage

In summary, a shift from manual provisioning to IaC yields several benefits for an energy company:

Accelerated operational efficiency and time to market: speed improvements, elimination of bottlenecks and rapid scalability.
Enhanced reliability and business continuity: rapid disaster recovery and reducing the risk of financial and reputational impact through faster recovery.
Proactive risk mitigation and security: built-in cybersecurity and reduction of human error.
Streamlined compliance and governance: automated auditability and enforced standardization.

Partnering for transformation

Modern energy demands more than incremental change – it requires a step shift in how your infrastructure is designed, deployed, and managed.

At One51, we help organisations move from reactive, manual processes to scalable, automated, and resilient platforms using IaC with Terraform and Azure. Combining deep technical expertise with real-world delivery experience, we enable faster deployments, stronger governance, and infrastructure built to keep pace with your business.

Ready to modernise your infrastructure and unlock real operational impact?

Get in touch with our team to start the conversation and take the first step toward a more agile, secure, and future-ready platform. Contact us now.