Forecasting

Itron's 2021 Forecasting Benchmarking Survey & COVID-19 Impact

October 11, 2021

COVID-19’s impact on energy consumption is not a secret. Since the pandemic began, we’ve watched electric sales drop and slowly recover (but not fully). Itron has documented the COVID-19 system level impacts in a series of memos, read the last blog here. 

But what about the class-level impacts?  Anecdotally, we’ve built stories about residential sales increasing from more office employees working from home. We suspect declining commercial and industrial sales from closed stores, empty buildings and reduced manufacturing output. While we may have seen the class-level impacts on our individual systems, are these impacts consistent across all systems? And how large are these impacts?

This year, Itron’s 2021 Forecasting Benchmarking Survey included measuring the COVID-19 impacts on 2020 class sales. For the first time since COVID-19 began, class-level impacts are reported for over 90 participating energy companies. The 2020 average class-level impacts on electric and natural gas sales are shown below.

  • Residential Sales
    • Residential electric sales increased between 2.91% and 3.53%.
    • Residential natural gas sales increased between 0.97% and 1.12%.
  • Commercial Sales
    • Commercial electric sales decreased between 5.15% and 5.31%.
    • Commercial natural gas sales decreased between 3.21% and 4.00%.
  • Industrial Sales
    • Industrial electric sales decreased between 1.24% and 3.67%.
    • Industrial natural gas sales decreased between 7.39% and 8.88%.

 

The results confirm our anecdotal understanding of the sales impact with many utilities showing similar results. Of course, the range of impacts varies based on the composition of each companies’ customer mix, but the overall patterns are consistent – residential sales are up, and commercial/industrial sales are down.

Looking into 2021 and 2022, the key question is when, or if, the sales will recover. The survey responses indicated that a full recovery to pre-pandemic sales levels is not likely in 2021 and estimates of the recovery’s timing is challenging at best.

With uncertainty surrounding the recovery, Itron is committed to continuing its research on the COVID-19 effects. We hope that all  survey participants are also committed to sharing data to better understand industry-wide growth patterns.

If you didn’t participant in this year’s survey and want to participate next year, send us an email at forecasting@itron.com and we will put your name on the list.

By Mark Quan


Principal Forecast Consultant


Mark Quan est consultant principal en prévisions au sein de la division des prévisions d'Itron. Depuis qu'il a rejoint Itron en 1997, M. Quan s'est spécialisé dans les solutions de prévision énergétique à court et à long terme, ainsi que dans les projets de recherche sur la charge. Quan a développé et mis en œuvre plusieurs systèmes de prévision automatisés pour prédire la demande système du lendemain, les profils de charge et la consommation au détail pour des entreprises aux États-Unis et au Canada. Les solutions de prévision à court terme comprennent des systèmes pour le « Midwest Independent System Operator » (MISO) et le « California Independent System Operator » (CAISO). Les solutions de prévision à long terme comprennent le développement et le soutien des prévisions à long terme (ventes et clients) pour des clients tels que « Dairyland Power » et « Omaha Public Power District ». Ces prévisions comprennent des informations sur l'utilisation finale et les impacts de la gestion de la demande dans un cadre économétrique. Enfin, Quan a participé à la mise en œuvre de systèmes de recherche de charge, notamment chez Snohomish PUD. Avant de rejoindre Itron, Quan a travaillé dans les secteurs du gaz, de l'électricité et de l'entreprise chez Pacific Gas and Electric Company (PG&E), où il a participé à la restructuration du secteur, à la planification de l'électricité et à la planification du gaz naturel. M. Quan est titulaire d'un master en recherche opérationnelle de l'université de Stanford et d'une licence en mathématiques appliquées de l'université de Californie à Los Angeles.


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