Weekly Brief

Streamlining Energy Efficiency with Smart Grids

Utilities Tech Outlook | Monday, April 10, 2023

The government is investing billions into new grid infrastructure, while private companies are developing artificial intelligence to forecast outages.

FREMONT, CA: Governments are investing billions in new grid infrastructure, private companies are creating new systems to mitigate outages, and artificial intelligence is becoming more accurate than ever, making it easier to develop a truly smart grid.

This increased investment in infrastructure and technology will allow for more efficient energy production, distribution, and consumption. It will also allow for better energy resource management and a more reliable and secure energy supply.

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Funding smart grid technology: Computer processing, control systems, and two-way communication technologies have made smart grid technology possible. Operators can assess grid stability using advanced sensors known as Phasor Measurement Units (PMUs), advanced digital meters that provide consumers with more information and automatically report outages, relays that recognize and recover from faults in substations automatically, automated feeder switches that reroute power around problems, and batteries that store excess energy to meet customer needs. Operators can quickly detect problems and take action to correct them. For example, PMUs can detect disturbances before they become bigger problems, allowing operators to take preventive action. Similarly, automated feeder switches can reroute power around problems, keeping power on and preventing outages. A battery can store excess energy and make it available when needed, ensuring a reliable power supply.

New technology: When an underground fault or single loss of source occurs on an underground residential loop, certain automated systems automatically locate and isolate the fault and reroute power from an alternate source—all within 60 seconds. This intelligent system reduces the impact of sustained outages that commonly last for hours. It eliminates the need for immediate crew intervention, keeping power on until the underlying issue can be resolved. The automatic isolation of faults also greatly simplifies locating faults on underground residential circuits and reduces medium-voltage exposure for crews. Furthermore, the devices do not need programming, firmware updates, computers, internet connectivity, batteries, radios, or antennas. This makes fault detection and isolation much faster and safer for crews since they do not have to manually locate and isolate the fault. The devices are easy to install and use since they do not require any programming or additional components.

Artificial intelligence: Beyond Limits is an industrial AI company that develops hybrid AI solutions by combining data and expert knowledge. The company has developed solutions for the energy industry, including power production optimization. Accurate predictions help companies better plan power plant unit operations and minimize spinning reserves. That reduces the operation cost and the carbon emissions caused by running unnecessary power generation units. By accurately forecasting power demand, companies can determine when to increase or decrease power generation to meet the demand without running too many power plants. This helps them save money on power generation and reduce the number of emissions caused by running these extra plants. Furthermore, when companies can accurately predict the electricity demand, they can purchase electricity from the grid when cheaper, which also helps reduce operational costs. Additionally, the reduction in the amount of power generation units used results in fewer emissions being released into the atmosphere, which is beneficial for the environment.

Having accurate weather predictions is also very important. Most companies use numerical methods like numerical optimization to improve power plant operation. But as the number of renewable generation units increases, the numerical calculations become more complex with many more decision variables, often greatly affected by the weather. If utilities want to solve those problems in real-time, numerical optimization could be improved, especially when there is high uncertainty in the power sources.

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