In the energy sector, there has long been talk of smart grids. The underlying concept is to modernize the physical infrastructure that electric utilities rely on for their delivery systems. This is typically accomplished through the use of computerized remote control and automation systems. Since this involves bringing legacy equipment into the digital world, it is also often referred to as an example of an Industrial Internet of Things (IIoT) initiative.
The current state of the grid
For this type of industry, change is slow. Part of this is due to the complexity of retrofitting or upgrading an extensive network of components that requires near 100% up-time. It is also a regulated industry, which brings with it additional challenges in terms of policies and standards. To get a better understanding of the current state of smart grids, it is helpful to map out its sub-segments: generation, transmission and distribution.
Generation refers to the power plants themselves. Some of these are considered core to the grid, always producing a base amount of electricity. Others are brought online to handle peak usage times or to augment maintenance windows at one of the core facilities. Transmission refers to the high capacity lines that carry this power to the regions that require it. Finally, distribution is effectively the last mile, where it is delivered to businesses and residences.
The smart grid movement has led to improvements in both power generation and transmission. For the most part, those two segments have made the investments necessary to enable a second by second understanding of how the grid is operating. However, this is not the case for distribution. In fact, most utilities have little visibility past the substation and even those aren’t fully monitored. Thus, the smart grid is not truly complete. There is a large blind spot that inhibits a full end-to-end understanding of operations.
At first, it may seem like the industry stopped short for no reason. But, there was a time when a detailed view of the distribution network was not critical. For decades, utilities could use a mathematical calculation to understand the capacity requirements of a neighborhood. This is important because regulations require utilities to keep a certain amount of capacity on the grid and over-producing power is wasteful because there is no way to preserve it if it goes unused.
Adapting to changing conditions
Then, the world changed. The popularity of electric vehicles has increased power consumption, while financial incentives for solar installations as well as environmental awareness has led to power being added back to the grid. All of a sudden, there was no predictable way to understand capacity needs. The math no longer worked on a consistent basis and utilities lost the ability to reliably forecast demand.
The time is right to solve the final piece of the puzzle. This means completing the promise of smart grids by extending it all the way to the edge of the network. One method of accomplishing this is replacing mechanical meters with smart meters. But, converting to smart meters is more than just new hardware. It also requires rethinking how a meter operates and the value that it can bring to utilities in understanding this currently invisible last mile.
The primary function of a meter is to measure electricity consumption, which is critical to generating revenue for a utility. However, smart meters create the possibility to deliver more value than just acting as the utilities’ cash register. They can offer more insight into how the grid is operating, including demand requirements and overall health.
For example, most utilities have poor documentation on how equipment within the distribution network is connected. They know where the meter is physically located for billing purposes, but they do not know which feeder, transformer or phase connects it. This impairs their ability to quickly restore power during an outage because the burden is on field teams to manually map it out. Smart meters can improve this situation through locational awareness. Leveraging peer to peer networking technology, they can dynamically create a network map and pinpoint the source of an outage. This reduces repair times and increases the availability of the grid.
It is also possible to take advantage of the added intelligence in smart meters to monitor line conditions. By evaluating changes in current flow and voltage levels, these meters can detect theft of service by determining when current is being drawn on the secondary of a transformer yet bypassing the meter. There are also safety applications like identifying high impedance connections, also referred to as hot spots, which can contribute to electrical fires or other hazards. These are conditions that can be difficult and time consuming to locate using traditional methods.
Industrial IoT completes the vision
There is no question that smart grids can provide significant value in terms of operational awareness, operational efficiency and grid stability. However, to realize those benefits, more work needs to be done to extend visibility to the edge of the network.
Over the next decade, smart meters will be pervasive in many markets. The data they create will give utilities and their customers unprecedented insight into consumption, helping them to improve energy efficiency, develop new products and services, improve asset operations, and make forecasting more accurate, and to enable demand-response programs – which in turn permit more renewable power to be deployed.
Industrial IoT holds the key to completing the smart grid vision, provided that the focus is not just on deploying a new generation of smart meters, but leveraging the data they generate to unlock new capabilities for both the utilities and those who rely on them.
About your guest blogger: Dave McCarthy currently serves as Director of Products at Bsquare Corporation where he leads both product management and product marketing. Dave has a passion for solving complex business challenges through the use of technology. He recognizes that IoT highlights the need for businesses to extract value from data, regardless of the source. Dave brings a unique perspective to inform how companies can better integrate data with enterprise systems to improve business outcomes.