Jackson Associates MAISY End-Use Forecasting System

CEDMS (Commercial) / REDMS (Residential) / IEDMS (Industrial) End Use Model Systems

Background

The genesis of the MAISY End-Use Forecasting System began in 1976 at Oak Ridge National Laboratory where the first commercial sector end use model was developed by Jerry Jackson, now the president of Jackson Associates. The model was used by the US Department of Energy and other federal agencies in energy forecasting and conservation analysis in support of the Carter Administration's National Energy Plan. This model, which for the first time, integrated engineering and econometric analysis in a single consistent methodology, served as the basis for a variety of end-use models beginning in the late 1970's including the California Energy Commission end use models.

While head of the Applied Research Division at Georgia Institute of Technology, Dr. Jackson and his team extended the model and provided the initial version of the COMMEND model to EPRI for distribution to its member utilities.

Jackson Associates (JA) was established in 1982 to provide proprietary commercial, residential and industrial end-use models, CEDMS , REDMS and IEDMS. Since 1982, JA has extended end-use modeling methodologies and customer database development to address a variety of energy, hourly loads, conservation, efficiency, DSM, demand response, new energy technology, market analysis, and new product development issues for more than eighty energy-related organizations. Current JA models employ the latest agent-based modeling techniques to more accurately reflect the impact of utility and other efficiency-related programs on technology choice and energy use.

End-use modeling is sometimes referred to as "bottom-up" modeling reflecting the fact that energy forecasts are developed from the sum of detailed components. For instance, residential energy use is modeled as the sum of energy use in end uses such as space heating, water heating, air conditioning, and other end uses for single family, multifamily, and mobile homes. This explicit representation of the basic determinates of energy use in each demand sector provide forecasts based on verifiable inputs and also supports the direct representation of conservation and demand response programs, building and equipment standards, new technologies and other important factors.

End-use models are the appropriate modeling methodology for applications that must reflect utility, state and federal energy efficiency initiatives and other activities that impact energy use. The end use modeling methodology is also applied in the US Department of Energy's NEMS model that is used to generate the US Department of Energy's Annual Energy Outlook forecast to the year 2025.

The MAISY Connection

In the mid-1990s interest in end-use modeling came to a screeching halt. Competitive electric markets appeared likely in nearly all states, and regulatory and utility accommodations postponed rate cases for years. JA quickly found a new market for its energy data, information and modeling expertise. JA developed and provided the only commercially available utility customer databases based on statistically representative information from a sample of utility customers. Both state and utility databases are provided in the MAISY utility customer databases. This Information on utility customer energy use and hourly loads took on added value as electricity providers considered new markets. In addition, technology companies including United Technologies, Ingersoll Rand, Toyota, Aisen and others have utilized this data and JA modeling support for market analysis and product development.

When attention returned in the early 2000s to utility and state energy efficiency programs, demand response and other DSM programs, JA incorporated the vast resources of the MAISY databases in its end-use modeling process. More than one-million US and Canadian utility customer records now support the JA residential, commercial and industrial end-use models. The importance of this data resource is described below in the discussion of the agent based modeling approach currently employed in the models.

JA End-Use Forecasting System Summary

End-use modeling practices have changed considerably since their development and introduction by Dr. Jackson more than thirty years ago. JA's state-of-the-art End-Use Forecast System (EUFS) includes the following characteristics:

An easy-to-use Microsoft Excel software container (all input, model equations and output are customized for each client and provided in a comprehensive Excel Workbook)
A simplified end-use structure reflecting needs and resources of energy forecasters and analysts in today's energy markets
A comprehensive modular structure with individual demand, supply and environmental modules which can be assembled to meet the needs of individual clients.
Parameters and characteristics developed from the MAISY utility customer databases reflecting more than one million customers in the US and Canada
Econometric and engineering relationships in a single comprehensive modeling framework
Energy use forecasts based on behavioral responses to price signals and changes in equipment and building shell efficiencies
Day-type and 8760 hourly loads, annual and monthly electricity, natural gas and oil use by end use and markets segment
Detailed utility efficiency and demand response programs and state incentives
Modeling methodologies and databases of equipment, DSM and customers developed in more than thirty years of applications.

A typical electric utility end-use model application is shown in the following schematic.

A schematic including modules in the full EUFS including environmental analysis is illustrated below.

The modular nature of the EUFS and the extensive utility customer database resources available in the MAISY databases permit Jackson Associates to meet individual client needs in economical modeling applications.

Agent-Based Model Extensions

Significant advances in policy-oriented models have occurred over the last decade (energy policy models include models where household, firm or government energy-using behavior is influenced by utility programs, tax incentives, information programs and so forth). Jackson Associates CEDMS, REDMS and IEDMS end-use energy demand models, were extended in the late 1990s and early 2000s to incorporate MAISY® Utility Customer Databases information and to reflect current utility, retail energy provider, equipment manufacturer and regulator forecasting and analysis needs. The

Agent-based microsimulation forecasting models have great conceptual appeal. A statistically representative sample of residential, commercial or industrial customers for any geographic area is developed from the MAISY Utility Customer Databases. Information on building, equipment, operating hours, end-use energy use and other data (including option hourly load data) are available for each customer. Current year energy use can be calculated by applying weights to each of the sample customers and summing across all customers in the sample.

Energy, hourly load and equipment forecasts for future years are provided by updating the sample of customers for the first forecast year. A sample of new utility customers is added to the process to reflect new construction; customer weights in the existing sample are adjusted to reflect demolitions of existing buildings. The new customer sample reflects recently new customers drawn from the MAISY databases. The same process is completed for each year in the forecast period.

Energy use and equipment characteristics of each sample customer can change in each forecast year. Existing equipment wears out and is replaced. The efficiency and energy use for these end uses is changed to reflect new equipment. For new construction, efficiency and energy use and fuel choices are incorporated in individual sample customer records. Energy price changes cause changes in utilization of most end-use equipment (e.g., increasing natural gas prices result in thermostat changes). Utilization and fuel choices are modeled with econometrically derived parameters and efficiency changes are modeled with econometrically derived parameters and with information on efficiency possibilities and appliance and building standards.

Customized Applications Provide Flexibility

Jackson Associates models begin with a comprehensive, basic characterization of energy use at the customer level. This comprehensive representation allows the models to reflect nearly any issue of interest to model users. Specific equipment sales, day-type and 8760 hourly load profiles, end-use energy use and hourly loads and more traditional energy forecasts can all be provided within JA model framework.

Jackson associates works with clients to identify specific forecasting and analysis needs and provides customized models to meet these needs.

JA End Use Model Advantages

JA residential, commercial and industrial agent-based microsimulation forecasting models provide a number of advantages compared to other approaches and other end-use models. The models:

Use a statistically-representative sample of customers in a transparent way to determine energy use at any desired level of aggregation
Apply technology and customer-detailed analysis of building and energy-using systems in a process that simulates choices actually made by individual customers. This process also avoids "double counting" problems common with other approaches.
Explicitly represents technology-detailed impacts of DSM , demand response and efficiency program measures
Use stratified customer samples to support the evaluation of user-specified customer segments and to accomplish vintaging of buildings, equipment and program impacts
Incorporate modeling and customer analysis methodologies developed in DSM, demand response, efficiency program, integrated resource planning, forecasting, market and technology analysis applications over the last twenty years
Apply a scalable structure which can easily be modified or extended to incorporate new analysis requirements
Provide an extension of widely-accepted analysis methodologies used by electric and gas utilities, states, regional organizations and federal government and other organizations
Provide customized applications to meet specific needs of clients
Take advantage of utility customer data available in the widely-used MAISY utility customer databases
Provide more targeted information at less cost than alternative approaches
Have been used in regulatory hearings and filings throughout the US and Canada

Building and End-Use Energy Detail

Building and end-use detail is also customized to meet specific client needs. Typical detail is shown in the following table.

Modeling Methodology Summary

The concept of microsimulation is intuitively appealing in that results are based on technology-level analysis performed on individual customers comprising a statistically representative sample of all utility customers. Analysis results are statistically expanded to the population of customers to develop an accurate estimate of energy use and hourly loads. This process is similar to that used in surveys where responses from a sample of customers are used to develop reliable estimates of responses that would be provided if all customers were surveyed.

The sample of individual utility customers is drawn from the MAISY Utility Customer Databases which have been developed with more than one million residential, commercial and industrial utility customers throughout the US and Canada.

In each year of a model forecast period:

Some customers are removed from the sample reflecting the demolition of buildings and customers who leave the service area.
New customers are added to the sample to reflect service area growth in the customer population.
Each customer's equipment holdings, building thermal characteristics and equipment operation are modified, as required, to reflect end-use equipment replacement, new equipment purchase, building shell upgrades and price-induced changes in equipment operation.
Each customer's day type and /or 8760 hourly loads are determined by summing across end-uses where end-use loads reflect changes identified in the previous item.
A robust sample of customers is used in the models to support analysis and forecasts at any level of detail from technology-specific to total system results. Customer samples are stratified by psychographic and firmographic variables (including building vintage) as well as by rate class and climate zone. Sample weights associated with each sample customer will, when applied to customer characteristics, provide accurate estimates of number of customers, customer building, equipment and operating characteristics, energy use, and 8760 hourly electric loads.

When run without any DSM, efficiency programs, demand response, technology product or other inputs, the models provide baseline energy use forecasts reflecting market-driven changes in equipment efficiency, equipment and fuel choice and equipment utilization.

JA models are applied to evaluate traditional utility DSM, demand response and efficiency program costs and benefits . Replacing existing equipment or building thermal measures with those that are technically feasible reflects technical potential. An economic potential run makes changes in individual customer equipment and building characteristics that are economically justified, and so on. Traditional cost/benefit tests and analysis at societal, utility and customer level are also provided as standard model outputs.

JA models provide energy use forecasts at detailed end-use, building and sector (residential, commercial, industrial) level. The models can also provide hourly load forecasts that range from peak demand to full 8,760 hourly loads. Additional energy, building and equipment detail (e.g., installations of small combined heat and power systems) can also be provided.

As schematic of the JA modeling process is shown below:

JA Modeling System Schematic

Application Areas

JA end-use models have been applied in the following application areas

Utility service area electricity and natural gas forecasts including peak demand and hourly loads
Utility service area cost/benefit analysis of alternative DSM, energy efficiency and demand response programs
Individual DSM program design
Detailed rate structure analysis
DG and combined heat and power market penetration and impact analysis
Penetration and energy use impact of of individual DSM and energy efficiency programs
DSM and energy efficiency technology market penetration potential analysis

JA Clients

JA database and custom end-use modeling systems have been applied by more than one hundred clients. A sample of JA clients is included in the scrolling window at the top left of this Web page. Clients range from small utilities and new technology start-up companies to the country's largest utilities and corporations.

The JA Value Proposition

Jackson Associates provides customized modeling and support services to each of its clients. Jerry Jackson, serves as principle investigator on all end-use modeling project and provides primary client contact. Prior to initiating each project, we discuss current client needs, resource constraints, potential future needs, data availability and other issues to design a custom end-use modeling project that provides required information, maximum flexibility and future scalability at minimum cost.

We take pride in having maintained a leadership role in the field of end-use energy modeling and policy analysis for more than thirty years. We view current challenges created by rising energy prices, increased importance of energy efficiency, demand response and other DSM programs as an exciting time to assist our clients in forecasting energy use and peak demand, evaluating energy efficiency and other DSM potential, evaluating carbon emission program options and meeting corporate social responsibility goals at minimum cost.

Model Options and Costs

Each of our projects is customized to meet our client's needs. Consequently we do not have a standard "list price" for our model applications. We are happy to discuss modeling options with potential clients and provide cost estimates. Model implementation costs are based on our data development, model parameter development, and model validation costs. We provide model application training and free telephone support to all clients. Our principal contact information is proved below.

Dr. Jerry Jackson is also a professor at Texas A&M University. The ability to use graduate student support along with support from world-renowned experts on an "as needed" basis to address current forecasting and analysis needs of utility, state and other organizations provides project resources unmatched by other organizations.

Contact

Jerry Jackson, President
Jackson Associates
P.O. Box 12340
College Station, Texas 77842
979-204-7821
jjackson@maisy.com