Hourly load study of 800,000 U.S. utility customers shows utility returns vary widely


College Station, TX, U.S.A. — (METERING.COM) — July 2, 2009 – A study of the hourly load of 800,000 utility customers at 200 of the largest utilities in the United States shows potential smart grid savings of 115,145 MW with avoided costs of more than $120 billion and net savings after smart grid costs of $48 billion.

The total savings for these 200 largest utilities was 115.1 MW, corresponding to 20.8 percent of peak demand. However, percentage peak reduction varied widely across the utilities, ranging from 16.2 percent (for Sierra Pacific Power) to 30.6 percent (for Public Service New Hampshire).

The study, by Jerry Jackson, president of Jackson Associates, was aimed at assessing the economic feasibility of smart grids and answering questions such as the economic feasibility of deploying advanced smart grid technologies to all utility customers.

The study found that commercial customers provided about one-quarter of the potential avoided cost savings, while individual utility avoided cost savings ranged from $49 million to more than $5.5 billion. Subtracting the costs of a comprehensive smart grid deployment provided net savings that ranged from negative savings to $3.2 billion.

Such variations, which are seen even between utilities within individual states, depend on a complicated mix of factors including dwelling unit size, age, electric appliance holdings, demographics, etc., the study states.

Utility analysis shows that nearly all utilities will save enough in avoided costs with a comprehensive smart grid deployment to at least cover smart grid development and deployment costs. However, many utilities barely break even. For example about 10 percent of utilities achieve benefit/cost ratios less than 1.2 and should be considered at risk of incurring costs that are greater than benefits given uncertainties concerning actual deployment costs. More than one-third reflect benefit cost ratios less than 1.5.
However, customer detailed analysis shows that all utilities can significantly improve returns on smart grid investments by targeting individual market segments with specific technologies.

Insights provided by “bottom-up” utility customer end-use hourly load data like that applied in this study will be an essential component in the development and evaluation of smart grid deployment at individual utilities, the study comments.

The study used Jackson Associates’ Market Analysis and Information System (MAISY) Utility Customer Hourly Loads Databases.