In partnership with PLMA, this group is for practitioners from energy utilities, solution providers, and trade allies to share load management expertise and explore innovative approaches to program delivery, pricing constructs, and technology adoption.

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How AMI Data Can Transform Load Research

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writer and researcher BrightGreen PR

Julian Jackson is a writer whose interests encompass business and technology, cryptocurrencies, energy and the environment, as well as photography and film. His portfolio is...

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Load research is fundamental to utility company operations. However the old methods of testing a sample of “non-smart” meters is being overtaken by Advanced Metering Infrastructure (AMI) data.

From rate and program designs for improved energy efficiency, demand response initiatives, grid planning and reliability, utilities and their customers benefit when load research is comprehensive, accurate and actionable.

Unfortunately traditional approaches, which were based on a small sample of residential meters do not give sufficient information for optimal results. That is not to denigrate load management teams using these methods, they are doing a good job with the data available.

AMI will give utility companies a much better insight into consumer behavior and help them plan more effectively. Smart meters and sophisticated analytics can deliver up-to-date and relevant insights that benefit utilities, their customers, and the grid. Over 107 million smart meters had been installed by the end of 2020 and are expected to reach 70% of the US market by 2021.

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AMI data is comprehensive, from all households using the smart meters. It can give very granular detail about consumption from home appliances, DERs, and even EVs that are charging. This can make load modeling much more effective. When combined with AI and ML this can potentiate all sorts of valuable consumer insights. However there are drawbacks:

  • The cost and time to change over systems

  • The need for IT and AMI teams to manage huge amounts of data

  • Concerns over data quality - “data cleaning” is needed

 

The benefits are significant. Utilities using AMI data to create new distribution networks have cited savings of up to two per cent of the total project cost. It also provides information about factors stimulating peak consumption, which can be translated into business strategies such as proactive load management, outage prevention and consumer incentive programs, as well as optimizing distribution network planning.

More advanced pricing structures, reduced billing cycles and reduced input to customer services like call centers are some of the advantages of using advanced systems of data analytics via AMI.

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