IoT Applications in Energy and Utilities
In terms of IoT applications, the energy and utility space can be segmented in many ways depending on the context of the discussion. From an IoT application viewpoint the opportunities may exist in:
- Oil and gas
- Electric Power Generation and Distribution
- Coal
- Water
Of these Oil and Gas and Electrical have the best near-term prospects for IoT innovation. Industries in both of these sectors are undergoing digital transformation. In addition, Oil and Gas has seen a personnel shift, referred to as “The Great Crew Change”, that has injected new thinking into a traditionally paper-based industry.
Oil and Gas Market Segments
The Oil and Gas industry is usually divided into three market segments:
- Upstream—The collection and/or extraction of fossil fuels from the Earth
- Midstream—Transportation of fossil fuels in their raw of near-raw state to processing facilities
- Downstream—The processing or refining of fossil fuels into products suitable for Energy Generation or Transportation
IoT Improves Worker Safety and Reduces Unplanned Shutdowns
For all of these segments, field work can be dangerous, and worker safety is a paramount issue. One of the biggest areas of focus for Oil and Gas is improving worker safety in combination with asset knowledge. Better methods for detecting, cataloging and prioritizing incidents and then properly selecting a reaction are a constant need. IoT can be used for enterprise asset management (EAM), to apply data insights for predictive maintenance and cost savings through reduction in both planned and unplanned downtime.
These segments also have widely distributed resources and facilities somewhat loosely coupled to each other from an information perspective. Many of these facilities are remote and operating semi-autonomously. Unexpected system failures can go undetected until they engender other failures and potentially unscheduled shutdowns. Unplanned shutdowns and maintenance issues can cost a company millions of dollars a day due to lost production. Efficiencies in operation and collection of timely and accurate data for post-analysis by systems guided by artificial intelligence applications are critical for these industries struggling to stay in front of and react to fluid operational situations.
Thus, a very real need exists for each of the three segments for highly sophisticated event-driven network systems that are flexible enough to respond locally to emergencies and systems failures as well as support the needs of cloud-based predictive analysis operations.
Edge Computing in Energy and Utilities
Currently the data framework of installed legacy systems supports large numbers of simple “go/no go” sensors. These must be replaced or co-located with sensors capable of recording data, recognizing the significance of certain changes in the measurements and issuing an alert at an appropriate priority or a notification that a change has occurred in the recorded data. These inputs can be processed locally by an event broker capable of posting event objects in a space shared by applications that have registered for those events. The processes that analyze information close to the data collection source and initiate action are collectively known as Edge Computing, a pillar of the IoT approach to network information processing. The processed information can be passed to cloud-based systems, providing input for predictive maintenance applications and in some cases sophisticated “digital twins” that duplicate the function of a field system virtually so that it’s performance can be studied in detail. A successful IoT implementation provides for immediate local alerts for worker safety and emergency maintenance, as well as support for cloud-based systems in the single network. This elimination of redundancy and substantial decrease in latency can cut costs, prevent unfortunate environmental incidents and save lives.
IoT Applications in Electric Power Generation and Distribution
Traditional energy distribution systems comprise power generation facilities, distribution networks and local power conditioning/phase adjusting systems to provide AC power to residences and businesses/industry. Increasingly the power grid is being expanded by alternative resources such as solar and wind in an effort to drive the generation of power closer to the point of use, and to minimize the reliance on fossil fuels. Solar power generation is being deployed across the country, by utilities at vast solar “farms” and by individual residences, businesses, government and academic institutions. Many areas support wind generation or geothermal energy sources, microgrids that rely on a variety of alternative power sources, and so-called “peaker” plants built by utilities and running on traditional fuels such as natural gas that can be brought online quickly if other sources such as solar degrade due to inclement weather or night. All of these alternative energy sources, including residential solar, feed power to the same network shared by traditional coal, oil or gas-fired plants as well as nuclear plants. These widely disparate energy sources must supply consistent, continuous power through the grid to users, and do it in such a way as to minimize use of fossil fuels and the distance generated power must travel to reach an end user. The multiple levels of system management that must interoperate to achieve these goals are a perfect application for IoT design. A deep understanding of Edge Processing, IoT Architecture and network security will be necessary to build these systems at many levels that are adaptable to new standards and scalable to meet expanding grids.
Other Applications for IoT in Utilities
In many cities, existing infrastructure for water delivery and wastewater removal is very old and located under busy streets, so that digging a pipe up is a major undertaking with multiple impacts. Many utilities have turned to robotic inspectors that examine the pipes from inside. While most systems deploy video, infrared and ultra-sound systems may also be used to detect corrosion, etc. These robotic systems move very quickly and collect enormous amounts of data. While most deployments currently are temporary, there may come a time when robot inspectors are on duty 24/7, continuously gathering data that must be analyzed as close to the collection point as possible, then made available to other systems for post-analysis, another excellent opportunity for IoT development
Today’s water utilities are also having to deal with implementing processes for recovery and re-use of waste water, sometimes called grey water. It has been necessary for some communities to install parallel distribution systems to distribute recovered water, which may be obsoleted when recovered water can be legally and safely introduced into the community water supply. Until then these greywater distribution networks must be carefully monitored for breaks or overflows. Small differences in water pressure are common, and do not necessarily indicate a problem. Smart sensors can analyze patterns in water pressure differential and identify a break or overflow in the system that might be missed by human operators. Event brokers can process rupture alerts from multiple sensors to determine that a major emergency may be underway requiring immediate large-scale remediation/recovery. Data passed to cloud-based analytics can be further analyzed to detect trends in failures that might be tied back to defective parts or installations. This is another strong opportunity for IoT-based systems that can help water utilities avoid costly and politically damaging release of greywater into the environment.
RUMBLE IoT is uniquely positioned to address complex development needs at this level of IoT design. Flexibility, scalability, interoperability and security by design will need to flow together into highly reliable systems. Speak to the experts at RUMBLE to see where you can go.
