|MAISY Energy & Emissions AI Applications|
MAISY AI-Powered Web and API applications provide energy use, costs, emissions, building and occupant data
for one or even millions of individual US residential or commercial utility customers or customer segments.
These applications use a variable number of household/dwelling unit or business characteristics
(depending on available customer input data) in either a standalone Web or API application to
estimate energy use and emissions and other data for any dwelling unit/commercial business in the US.
Example ApplicationsCustomer Segment Data. A solar panel retailer wants to estimate average energy cost and solar rooftop savings of residential energy customers in a specific ZIP code for dwelling units with more than 800 square feet of roof space using electric space heating. Inputting this data in an online MAISY Web form will quickly provide the answer. If the retailer wants to estimate this information for 900 ZIP codes in Florida to identify ZIP target markets, the MAISY API provides an easy batch processing option to generate these data all at once. Queries can be refined to present information for any potential customer segment based on income, householder age, business category, and dozens of other characteristics.
Individual Customer Data. The MAISY API can be used by financial firms to develop Scope 3 emissions data ( for a description of Financed Scope 3 data click here ) for residential and commercial real estate (CRE) customers. The API batch processing application can generate energy use and carbon emissions for each residential and CRE customer in the firm’s loan portfolio.
Input data range from a minimum of a ZIP code (providing ZIP-level averages for each customer) to as many as several dozen customer characteristics (e.g, household income, household members, floor space, building age, business category) providing more detailed energy use and emissions estimates.
The power of MAISY AI Apps. The new age of artificial intelligence has opened an analytic toolbox that offers significant advantages in estimating energy use and emissions of households and businesses compared to traditional tools. click here
The Web and API MAISY applications apply an AI k-nearest neighbor (KNN) analysis along with regression refinements where dwelling units or businesses from MAISY master databases are identified as belonging in the user’s “neighborhood” with a weighted distance measure that includes household/dwelling unit or business characteristics. Additional analysis of energy use and emissions from the nearest neighbors provides estimates of the energy use and emissions. The master databases includes energy use and emissions for more than 7 million households and businesses across the US.
For a related example using the MAISY KNN process click here. This online App provides energy cost and benchmarking for any residential or commercial utility customer using the AI KNN process described here.
MAISY Energy Use and Hourly Loads Database Background. MAISY database information has been used by utilities, energy service providers, energy service companies, equipment manufacturers, research organizations, regulators, government agencies and other energy-related organizations. MAISY data have also been used to support US Department of Energy appliance and equipment efficiency standards development. Click here to see a partial list of JA Clients and applications.
MAISY 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 or engineering model-based results.
MAISY Energy Apps and APIs provide easy access to individual customer and customer segment energy use and emissions provided in MAISY master databases without having to rely on “big data” projects to process and analyze results of a 63+ billion data item database.
Click here for additional MAISY Database information
MAISY Web and API App Data ResultsMAISY Web applications provide the following detailed energy use and emissions data in online sessions.
Data Items: Emissions Databases
|VARIABLE GROUPING||DATA ITEMS|
County & State
|Attribution Factor (Optional)||
Used For Financed Scope 3 Emissions Consolidated Report. Attribution factor is the ratio of the outstanding
loan balance at the time of GHG accounting to the property value at loan origination
|Annual Energy Use Data||
Optional: End-Use Energy Use and Hourly Loads Data
|RESIDENTIAL AND COMMERCIAL EMISSIONS DATA||
Total Annual Emissions (CO2e) (including emissions generated by household/FIRM electricity,
natural gas, fuel oil and propane use)
|DATA ITEMS USED IN THE NEAREST NEIGHBOR ESTIMATION PROCESS||
These are data items provided by the user for each energy customer or customer segment used
in the AI-KNN statisitical process to estimate energy use and emissions - these are optional
data inputs. Any of the MAISY Residential
Customer Database items can be specified
Example input data items are given below.
Dwelling Unit Age
Dwelling Unit Floor Space
... Other Residential Database Variables ****
... Other Commercial Database Variables ****
Data Items: Consolidated Emissions Data for Batch Processes
(Sum of all customer-level data )
|VARIABLE GROUPING||DATA ITEMS|
Total Number of Residential Customers
Total Number of Commercial Customers
|RESIDENTIAL AND COMMERCIAL CUSTOMER EMISSIONS DATA||
Total Annual Emissions (CO2e) (including emissions generated by household electricity,
natural gas, fuel oil and propane use; uses optian attrition data if included in input files )
Optional: Customized GHG Intensity Data (see the whitepaper Scope 3 Financed Emissions Reporting: How Good Intentions Can Lead to Bad Outcomes )
Other MAISY Financed Emissions Accounting Data and Services Topics