2012 MAISY Utility Customer Databases
MAISY® (Market Analysis and Information System) Utility Customer Databases are the energy industry's most widely-used, authoritative source of utility customer energy use information available. MAISY database information has been used by utilities, energy service providers, energy service companies, equipment manufacturers, research organizations and other organizations interested in utility customer energy use. MAISY data have also been used to support US Department of Energy appliance and equipment efficiency standards development.
MAISY Utility Customer Databases include energy use, hourly loads, building, equipment, operating, occupant and other energy-related information for individual commercial , industrial and residential customers records including day-type (peak day, week day and weekend day for each of 12 months) and 8760 hourly loads for individual end uses.
Databases have been developed from information on more than 5 million individual utility customers throughout the US and Canada, providing a representative sample of residential, commercial and industrial customers for metropolitan areas, utility service areas, states and provinces.
Databases reflect information from hundreds of different customer and market data sources including onsite customer surveys, utility and fuel supplier billing data, government, association and proprietary data, and other sources including ongoing Jackson Associates utility customer data development. Databases are continuously updated to reflect important recent trends in the most important determinants of residential, commercial and industrial energy use.
Large customer samples within geographic areas maintain the diversity of actual customer populations, providing a more accurate analysis of customers, markets and market segments compared to "average" customer information. (for more information on this topic see Avoiding "Prototype" and Average Load Data Aggregation Errors).
Additional MAISY Utility Customer database topics.
2012 Database Updates and Characteristics Summary
Hourly Loads Detail
MAISY Profiler Software
MAISY Versus "Prototype" Data
2012 Database Updates Now Available!
2012 commercial, industrial, and residential databases are now available.
These updates include new information on utility customers in individual metropolitan, utility
service areas, states and provinces. Extensions include Utility customer energy use and population
characteristics as of January 1, 2012.
MAISY Utility Customer Database Characteristics Summary
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| Individual Customer Data | Geographic Detail |
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| Detailed Energy Use Information | Other Customer Data |
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Each MAISY client receives a custom database including selected customer variables of interest.
The following links document database variables included in the Databases in more detail:
List of Commercial
Database VariablesList of
Residential Database VariablesList of Industrial
Database VariablesHourly Loads Detail
In addition to annual and monthly energy use, equipment, building, operating characteristics and other customer information, MAISY Databases include hourly electric, natural gas and fuel oil loads for each customer record.
Load data are weather-adjusted to reflect normal hourly weather data. Users can access and evaluate hourly loads for individual customer records or for any grouping of customers defined by variables in user-defined databases (e.g., heating fuel, business type, square feet, number of children, etc.) The large number of customers in the databases permits users to develop hourly load information for detailed customer types and market segments based on relevant customer characteristics.
Hourly loads are available as day-type /month summaries (week day, weekend day, peak day for each of the 12 months) and in full-year 8,760 formats for electric, natural gas and oil energy use as whole-building loads and for individual end uses (e.g., space heat, air conditioning, etc.). Hourly loads data are accessed through the MAISY Profiler and may be exported to other software.
MAISY Profiler Software
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MAISY Profiler Software applies a proprietary data slection process to provide exactly the information required for your application. For example, a Profiler application designed to provide commercial utility customer day-type/month hourly loads for specific customer characteristics in New York city, allows users to select commercial customer characteristics such as building size, business type and so forth. The Profiler software queries the database and extracts information on buildings that match the query variables presenting average energy use and hourly loads for that customer segment in an Excel workbook. Profiler sofware can also provide individual customer record data which can be exported to other data-analysis software. |
Each Profiler package is custom developed for each application. View the 8-minute Profiler video-demo.
Typical Profiler Applications
Specify any or all building/equipment/occupant characteristics and the Profiler extracts appropriate database records providing you with an Excel workbook containing energy use and hourly loads data reflecting the customer or market segment of interest.
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Specify monthly or partial year electric bill data along with any building/equipment/occupant characteristics available and the Profiler will provide an Excel workbook with hourly load data calibrated to the billing data.
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Let the Profiler extract full database records including day-type/month load profiles and 8,760 hourly load data for any building/equipment/occupant characteristics (or all buildings if you like) for your own analysis.
If you like, we will add analysis and calculation software and even utility rates to the Excel workbook provided by the Profiler to give you a tool that you can immediately apply.
MAISY Individual Customer Data Versus "Prototype or Typical" Data
The MAISY system permits users to select individual customers or customer segments based on dozens customer characteristics. Pick any combination of business type, floor space, operating schedules, space heating fuel, year of construction and many other variables to zero in on a specific customer type or market segment.
What about other load-profiling systems that offer 12, 36 , 75 or some other limited number of fixed customer segments? To represent 13 commercial business types; electric, gas and oil heat; small, medium and large buildings requires 117 prototypes or "typical" buildings. Add in age categories and more than 200 "fixed prototypes" would be required, well beyond the scope of these "fixed" systems. With MAISY, customer and segment selections provide hundreds of possible definitions with nearly unlimited choices of customer characteristics. Only MAISY provides the detail and flexibility required to reflect the extensive customer and segment detail required in todays energy markets.
Relying on "prototype and typical" is similar to analyzing a "typical" family which consists of two adults and 0.6 children - it may reflect an average but it may also provide misleading results when used to understand customers and markets, to develop programs to fit the needs of individual customer segments, to evaluate the profitability of serving these customers or to evaluate markets for new technologies.
Sources of load profile data which rely on fixed customer segments (e.g. large, medium and small offices) typically develop hourly load data with engineering models (e.g., DOE2) of a single "prototype" building. The aggregate nature of these representations misses the variation that exists among individual buildings within these segments, hiding important market information. For instance, a particular electric rate structure may provide a competitive profit based on an entire segment's single prototype load profile; however, analysis of subsets of the segment (which can be performed with MAISY but not with the "prototype or typical" load profile approach) may reveal significant diversity in profit levels across customer sub-segments such that some customers are provided power at a loss while profit margins on other customers result in cream-skimming targets for other suppliers.
Similarly, evaluating markets for new technologies or potentials for energy efficiency initiatives requires consideration of the full range of customers within a market or utility service area. The average load profile may reflect little potential hiding the fact that a significant portion of the market with different load characteristics provides great potential. For more information on this topic see Avoiding "Prototype" and Average Load Data Aggregation Errors.