Creating intelligence at the grid edge is a key component of tomorrow’s intelligent grid.
For a long time, the industry has thought of the intelligent grid as an inevitable but albeit distant future. However, as technology has rapidly improved and become more capable, that future is upon us.
It wouldn’t be the first change that took the sector by surprise - from smart meters to distributed energy resources (DERs) and electric vehicles (EVs), rolling out technology without properly preparing can negatively impact everyone from the consumer to the grid operator.
Using expert insights from key players across the grid intelligence market, we explore how grid edge intelligence solves some of the pain points of the intelligent grid.
Grid edge intelligence business benefits
The intelligent grid will generate previously unimaginable volumes of data and analysis capabilities, most of which can no longer be dependant on centralised collection and processing. So, how can utilities break away from decades of centralised thinking?
The International Data Corporation (IDC), suggests that 40% of data created by the Internet of Things (IoT) will be subject to IoT edge computing.
By bringing intelligence to the edge with localised data collection and processing, only the most valuable, insightful and neatly packaged data need be transferred to central points of operation.
In its white paper ‘Edge Intelligence’, the International Electrotechnical Commission (IEC) explains the benefits of computing at the edge: “Edge intelligence allows future applications to depend on context awareness capabilities for mutual detection and proximity services, (near) real-time responsiveness for a tactile internet, data analytics at the edge and/or end device and device-to-device communication capabilities.”
For decision making, edge intelligence can reach decisions according to its local area, accessing and managing control policies and following local regulations seamlessly. The IEC says: “Even in the dawn of 5G networks, which will dramatically reduce delays in communication and increase available bandwidth, advances are mostly being achieved via geographically localised optimisations in the network.”
All of this in turn can significantly lower communications costs and decrease latency, with the capability to cache or use local algorithms to pre-process data so that only decisions or alarms need be forwarded to the a central point.
Implementing edge intelligence - use cases
Aside from the overall benefits in improved data collection and transfer, creating intelligence at the grid edge can have significant benefits when applied to other intelligent grid developments, such as those identified in a recent Navigant study.
In the study, Navigant suggests: “In the longer term, grid edge intelligence and automation will enable the proactive development of markets for aggregated clean resources and services; reliable, efficient, and self-healing power delivery networks; and end-to-end integrated grid management strategies.”
For instance, DERs can be optimised significantly with the advent of edge intelligence on the grid. Edge intelligence allows for enhanced demand response capabilities, responding quickly to localised interruptions, peak demand loading or problems further along the transmission and distribution systems.
Itron, recognised for its revolutionary IoT OpenWay Riva platform, recently conducted a survey of electric utilities across North America to gain an understanding of what DERs meant for their businesses, finding that 94% of utilities consider the conjunction of demand response and renewable generation a priority in the next 1 to 3 years.
Furthermore, the survey showed that 68% of utilities expect DERs to significantly impact their operations within the next 5 years, and that AMI meters, line sensors and smart thermostats, i.e. intelligent edge devices, are the most critical devices for utilities managing DERs.
By utilising edge intelligence, localised decision making can relieve pressure from the grid by switching supply to local generation such as solar photovoltaics instantaneously, improving service and efficiency automatically.
Edge intelligence can lead to better asset management, controlling and directing edge technologies such as rooftop solar, behind the meter storage and EVs according to local situations including weather and demand.
In a white paper, ‘Bringing Intelligence to the Edge', IoT solutions providers Indra and Intel discuss through the lens of their partnership how edge intelligence can be used to leverage transactive energy.
The white paper explains how, by giving consumers visibility over energy costs, consumers can not only take measures to reduce consumption in peak hours, but also sell energy back to utilities to assist in grid load balancing.
Leonardo Benítez, Director of Smart Energy for Indra explains in the white paper: “You as a client could determine what can/should be switched off, in order for the utility to manage demand. If a utility needs to reduce load, this needs to be done rapidly so having these pre-programmed rules enables rapid response to load management. Because these types of decisions need to be made in milliseconds, edge computing is vital for the speedy response is needed. This is why we believe this is a very powerful opportunity.”
The potential in edge intelligence is clearly there - all utilities need to do is take it, implement it and leverage it. At our upcoming Engerati Meets on the intelligent grid, we will discuss several potential use cases and business models centred on edge intelligence.