Power distribution systems are rapidly evolving across the world in an effort to reduce carbon emissions and meet bold climate goals. Today, governments at the national, state and local levels are collectively investing trillions of dollars to build renewable energy sources and modernize their grid. In the US, the recent infrastructure bill includes $65 billion to rebuild the country’s aging energy infrastructure.
This energy transition is driving surging investment at the edge.
While the traditional fossil fuel-based grid is mostly centralized, the new grid will be highly distributed, with solar, wind and other energy resources scattered across diverse geographies. These environments are all being equipped with edge infrastructure to manage, maintain, and measure these deployments.
In particular, edge systems will be key to solving a major challenge of using distributed, renewable energy resources: namely, the existing grid was built for resources (such as coal and nuclear) that provide a predictable, consistent power load. But the performance of modern, renewable assets (such as solar and wind) varies significantly based on weather.
Edge applications will help utilities balance these resources – especially through the management of battery energy storage systems – so they can provide sufficient, consistent loads to accommodate fluctuating demands on the grid. To optimize these new grid settings, organizations are turning to hybrid, open edge technologies.
Hybrid edge-cloud – lower latency, lower cost
For a number of years, the energy sector has invested significantly in cloud infrastructure as a key component of its ongoing transformation. Driven by IoT adoption, the growth in the number of internet-connected devices in energy has exploded. With this exponential increase in the amount of OT data, it is becoming unfeasible to continually ship this huge volume of data to the cloud for analysis and processing.
This approach is too expensive and introduces too much latency into the supporting tech infrastructure. The power grid of the future must be much more reactive to real-time changes in energy generation and demand. A cloud-centric approach tends to inhibit this.
This is where local edge computing plays a major role in connecting the assets, then acquiring and processing the data where it’s created – all in real time, enabling more timely and efficient reaction to fluctuating energy demand. Local data storage can be provided whenever necessary to support periods of intermittent connectivity.
An edge solution can also provide the integration point with the backend cloud systems providing the overall grid management. In this case, only a subset of the OT data collected needs to be forwarded to the cloud for further analysis, where response times are not so demanding.
Ultimately, the modern power grid needs both edge and cloud components, although more OT applications will reside at the edge, with their deployment and updates managed centrally from the cloud. As a result, the hybrid edge-cloud model is becoming the norm.
Openness at the edge – freedom and flexibility
Edge computing is essential in enabling modern grid environments to function effectively and efficiently. However, despite the benefits outlined above, there are still significant challenges that remain. For a fully interoperable and decentralized electric grid, the edge layer will become the integration point for both legacy and new assets at the substation level and across distributed energy resources (DERs).
This requires the edge systems to communicate with many different types of equipment using a plethora of communication protocols, and to acquire and normalize the data from a disparate set of endpoints. Moreover, the fusion of data from multiple sources is critical to the creation of a common representation of the data that can support the edge applications (such as control, monitoring and analytics) in a consistent and interoperable manner.
This is a significant challenge when you consider the wide range of communication and data mapping standards used in the energy sector such as Modbus, IEC-61850, IEC-60870, DNP3, OPC UA, EtherNet/IP, MQTT, Sparkplug and SunSpec. Individual grid assets may use their own proprietary or specialized communication protocols, which also need to be integrated into the edge system.
Closed, proprietary software approaches make it difficult to support all these different data sources, types and protocols. These traditional approaches don’t provide the flexibility needed to accommodate data complexity. Instead, they’re designed to lock an organization into a single vendor’s ecosystem and the limitations that come with that.
When relying on a closed and proprietary offering, energy companies are at the complete mercy of the vendor – and only able to handle the specific data formats, APIs, protocols, and so on that the vendor supports. This hurts their ability to integrate legacy and new assets and limits which apps they’re capable of rolling out, ultimately minimizing the value that they can provide.
An open software approach offers the flexibility needed to accommodate all these components, deliver advanced edge apps, and support highly decentralized grid deployments. Openness allows organizations to work with any data type, standard and protocol at the edge, since they are not confined to a single vendor’s capability or roadmap. With this flexibility, utilities and energy companies can deploy any application, including customized apps developed by themselves or third parties.
In addition, openness makes it simple to add new equipment and grow an edge environment as new requirements inevitably evolve.
Building the grid of the future
As the world moves quickly to modernize and transform its grid infrastructure, a new generation of edge solutions is revolutionizing the power industry. Broadly speaking, edge systems are playing a fundamental role in this transition to a more intelligent, agile, and distributed electricity grid.
Specifically, it’s a hybrid, open approach that is giving these edge systems the speed and flexibility to support real-time decision-making and seamless interoperability.
