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software in a COVID-19 pandemic world

The global COVID-19 pandemic is changing how we live and work in ways that are not yet well understood. Fear-based behavior modifications like additional hand-washing and social distancing may become ingrained in our culture, much like the 1918 Spanish flu epidemic made not sharing drinking cups and covering your cough common courtesies.

 

Ready to leverage the potential of data analytics?   Download the playbook

 

 

Utilities face uncertainties

Some not so obvious changes are also occurring during the pandemic. For example, COVID19 fears add a layer of uncertainty for utilities, which must keep employees and the public safe, cope with complications related to recovering from storms and outages, and deal with changes in demand patterns that affect distribution network performance.

For example, mutual assistance from surrounding utilities to restore power after storms may be less available post-pandemic, according to a recent article on the Scott Madden Management Consultants’ website. “[Utility] executives need to contemplate is whether mutual assistance will be available at all and, if so, under what conditions,” stated the article.

“[Utility] executives need to contemplate is whether mutual assistance will be available at all and, if so, under what conditions,”

 

Scott Madden Management Consultants.

Changes in demand patterns are forcing utilities to rethink processes. Worldwide commercial and industrial demand for electricity has decreased sharply, with demand drops as high as 22% recorded. At the same time, peak demand has shifted in many areas from the morning and evening to mid-afternoon due to work-at-home trends.

This shift in demand has resulted in changing load patterns. Pre-COVID-19, you might have a load concentrated in one part of the grid during the day, and in another at night. But that is changing rapidly. Utilities need to find ways to adjust and manage these changes.

 

 

Demand for more information

One big change to the status quo brought by the COVID-19 pandemic is an increase in retail consumers’ energy use because of work-at-home mandates. Austin Energy, for example, recently sent about 33,000 Austin, Texas, residents high-usage alerts in mid-March warning them that they were using significantly more electricity than previously, reported the Austin American-Statesman.

It makes sense that when customers use significantly more electricity that they would appreciate more in-depth understanding of what is causing the increase so they can take action to save money. The difficulty is that it is challenging to understand exactly how electricity use is distributed among devices and appliances in a home.

This is where the concept of data disaggregation comes into the picture. Data disaggregation:

  • Provides utilities with a detailed breakdown on how individuals are using electricity in their homes, and what their “baseload” is and usage on appliances, heating, cooling, and electric vehicle charging.
  • Gives utilities enough information to make concrete suggestions on steps consumers can take to save money such as charging electric vehicles late at night when rates are lower, rather than in the middle of the afternoon.
  • Facilitates the promotion of specific equipment upgrades to reduce costs. For instance, utilities could use the information gleaned from data disaggregation to target customers with a standard pool pump with discounts for purchasing variable-speed pumps that save electricity and reduce their bills.

 

 

A growing role for analytics

According to a recent report by OMDIA, uncertainties surrounding COVID-19 are amplifying utility concerns around top-line revenue and bottom-line costs more than ever. The report suggests that utilities may find solutions to their concerns in the existing AMI software and services technology they already have.

 

 

Data at the meter

Data from meters on advanced metering infrastructure (AMI) systems can help utilities understand the effects of increased residential demand caused by people working at home. When analyzed correctly, the data can help engineers recognize what phases of the electrical current meters are operating on,  how transformers are loaded, and switch consumer load when needed.

For example, utility engineers can use the analysis to determine how to handle specific problems. For instance, they can optimize operations by making informed decisions on whether equipment, such as a transformer in a residential area that is becoming overloaded, should be upgraded or whether they can add a capacitor bank to improve power quality to keep it operating effectively.

Meter data also is useful for pinpointing the location of faults before they become outages. Missouri-based Platte-Clay Electric Cooperative analyzes its meter data using patent-pending algorithms from Aclara to detect when a fault occurs. The software solution decreases time lost “driving the line” looking for the outage, eliminates reliance on member calls to report outages, and allows the utility to target truck rolls to the likely location of the cause of the service disruption.

 

 

Data beyond the meter

Technologies like grid monitoring with smart grid sensors are also important tools for utilities dealing with the changes caused by COVID19. The data from these devices offer real-time visibility that can help utilities pinpoint faults without having to routinely send work crews to the field to look for them. This is an important consideration during a time when utilities may be experiencing personnel constraints or may want to limit the contact their workers have with the public, thus necessitating the need to remotely monitor their distribution networks.

  • Managing summer peaks – As we are entering the summer season, peak electricity demands put a tremendous strain on the grid, increasing the risk of blackouts and brownouts. Utility companies must manage the increased load on their circuits and transformers to avoid an overload. One way that utilities can monitor the increased load without having to send crews is by installing grid monitoring sensors with load monitoring capabilities.
  • Substation monitoring – was an important consideration for NV Energy when it deployed a combination of medium-voltage and power sensors as part of a grid monitoring solution in a location that was difficult to access. The sensors revealed a weakness in the area’s network infrastructure which the NV Energy team addressed immediately. Without the sensors identifying the problem, service may have been disrupted. Check out this case study to learn more.

Almost as important as the devices themselves, however, is the software used to analyze the data from smart grid sensors. In the case of substations, for example, the Aclara sensor management system software allows utilities to build a transformer model for the substation including the mega volt amp (MVA) and voltage ratings. Alarm points are also defined for the transformer based on the percentage of MVA rating. For instance, an alarm can be generated when the load on the transformer reaches 90% of the MVA rating and can automatically alert utility personnel. Check out this webinar on how to use the actionable intelligence derived from smart grid sensors to improve system reliability and customer satisfaction.

 

 

Conclusion

The COVID-19 pandemic has caused major upheaval in the way we live, and the fallout for utilities is just beginning. One thing is certain however, software and analytics will be central to utilities’ successfully meeting the challenges ahead.

Learn more about the power of data analytics. Download the playbook.

 

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