Energy and powerNews

New edge computing solutions set to revolutionise the power industry

The adoption of new edge computing solutions is forecasted to create much-needed disruption and growth opportunities in the energy industry, writes Andrew Foster, product director and IOTech co-founder.

Innovation is crucial if commercial organisations are going to disrupt existing markets and create new growth opportunities. In this respect, the energy industry is no different.

The adoption of new edge computing solutions is about to create this disruption. This latest generation of solutions is software-defined, capable of multi-mode operation and is OT-protocol agnostic.

These solutions are replacing traditional control and monitoring systems which are often hardware-centric and siloed. Instead, flexible edge systems running on commodity hardware are now being deployed across power industry use cases. They include renewable energy generation, battery energy storage systems and distributed smart grid control.

The digital grid of the future

The electricity grid is already undergoing a process of change, driven by the need for digitisation to support much greater efficiency and responsiveness. This is required due to the increasing grid complexity operators must deal with. It flows from the need to integrate new energy sources and to generate and store energy in a distributed manner.

Other factors driving this change include the need for generators, distributors and energy technology companies to offer new products and services in an increasingly competitive market. It is also important that both regulators and consumers have improved access to the very latest operational and commercial information.

When combined with much greater intelligence across subsystems, digitising the grid assets across operations is vital to help manage this complexity.

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The need for edge computing

Edge computing solutions that can support open, configurable and manageable software architectures are already starting to replace legacy control and monitoring systems.

Edge computing introduces local computing resources at the substation and field asset level in an electrical grid. It brings processing capabilities and storage closer to where it is needed. It also helps improve scalability, response times and operational costs by enabling systems that are easier to maintain and update.

By processing much of the data generated from the connected grid assets locally, users will see a significant reduction in network bandwidth costs associated with shipping the ever-increasing amounts of OT data to a data centre in the cloud. Fault resiliency of the grid is improved by enabling decentralised autonomous operations.

Edge computing is enabling a new generation of smart applications that can leverage the latest advances in artificial intelligence (AI) and machine learning (ML). It brings many of the benefits of cloud computing such as containerisation, virtualisation and modern approaches to application orchestration and updating to the OT world.

This makes it much easier to update existing systems or deploy new applications by leveraging commodity edge hardware – certainly when compared to traditional approaches based on dedicated hardware (e.g., PLCs and PACs). Importantly, there is less need to completely replace parts of a system during an upgrade, which is costly and time consuming.

Edge computing vs. cloud computing

For a number of years, the energy sector has invested significantly in cloud infrastructure as a key component of its ongoing digital transformation. Driven by the Internet of Things (IoT), the growth in the number of internet-connected devices and sensors has exploded. Across industries, this growth is helping to enable digital transformation.

The same trends are being seen in the energy sector. However, 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. It is too expensive and introduces latency into a system. The electric grid of the future must be much more reactive to real-time changes in energy generation and demand. A cloud-centric approach can inhibit this.

This is where edge computing plays a major role in connecting the assets, then acquiring and processing the data locally in real-time. Local data storage can be provided when 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.

This means it is a false choice between an exclusively cloud or edge-based architecture. The future electric grid needs both, although more OT applications will reside at the edge, with their deployment and updates managed centrally from the cloud. In this case, a hybrid edge-cloud model will become the norm.

Grid of the Future. Courtesy IOTech

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Challenges

Edge computing will become a key disruptor in the energy sector and can provide many benefits as already outlined, although significant challenges remain. For a fully interoperable and decentralised 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 normalise the data from a disparate set of endpoints.

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 (e.g., 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 specialised communication protocols, which also need to be integrated into the edge system.

Edge Computing also introduces a new layer of computing resources to support local processing. Despite being based on commodity hardware and using commercial operating systems (typically Linux-based), these devices can come in a range of different form factors (e.g., MCU, IPC, Server).

At the substation and across the grid, there may be many of these edge devices that need to be managed. It is crucial that users be able to manage these devices and their application workloads centrally, normally from the cloud, but also potentially on-premise when required. The latest generation of edge applications typically supports containerization (e.g., Docker) which provides a range of benefits such as application portability. However, a management system must also be able to deploy and manage other workloads, such as conventional executables.

Edge platforms

To meet these challenges and deliver on the benefits that edge computing will bring to the future electric grid, a new generation of power industry-specific edge solutions will be necessary. The key ingredient of these new products is the edge software platform, which is the underlying software framework on which the applications will be deployed.

To enable the distributed grid of the future an edge software platform provides a range of services and an interoperability foundation on which to build the edge applications. Key platform services include configurable, no-code multi-protocol OT integration, data normalisation, transformation and filtering, local rules and analytics support, data storage/store and forward, security services (including client authentication, access control and data encryption), alarm handling and cloud connectivity.

Openness is the key characteristic of these edge software platforms. This means providing an application deployment environment that the energy technology providers can use for easy creation of their own value-add applications. The platform must be OT protocol- and cloud-agnostic, hardware- and operating-independent, component- or microservices-based to support application composition and distribution. Critically important, it must provide a standard set of APIs to support the integration of the edge applications that are consuming and processing the OT data.

Both commercial and open-source edge software platform implementations have emerged over the last few years. These have reached a level of maturity that now offers the energy solution providers a range of viable options.

A key open-source initiative with broad cross-industry support is the Linux Foundation’s LF Edge. The objective of LF Edge is to establish an open, interoperable framework for edge computing. EdgeX Foundry is one of the largest projects under the LF Edge umbrella. It provides a flexible and scalable open software platform that facilitates interoperability between OT devices and applications at the edge. EdgeX Foundry and its commercial derivates, such as IOTech’s Edge Xpert, are seeing increasing adoption within the power industry.

The future power of edge computing

A new generation of edge solutions is set to revolutionize the power industry. These solutions are already helping accelerate digital transformation and support new use cases and services. Edge computing will enable a more intelligent, agile, efficient and distributed electricity grid. It is crucial to the integration of assets at the substation level and between DERs, and will support applications that are much easier to deploy and maintain as the grid evolves.

The electricity grid of the future will be based on a hybrid model that leverages the advantages of both cloud and edge computing.

Finally, open edge platform software that provides a range of configurable microservices will be the key enabler for a new generation of energy-specific solutions.

ABOUT THE AUTHOR

Andrew Foster & edge computing

Andrew Foster is the product director and co-founder of IOTech.