The following example notes and white papers illustrate MAISY database and model applications.
Apply Extended RECS Hourly Loads Databases to Develop Excel Agent-Based Energy
and Hourly Load Forecasting Models
Energy and hourly load forecasting typically requires statistical knowledge applied in econometric models or in-depth appliance engineering data and market information used in end-use models. Agent based models apply an intuitive framework that models individual households, i.e., agent, behavior. This approach requires neither a statistical background nor detailed appliance engineering knowledge to produce model forecasts that, in many ways, are preferable to traditional econometric and end-use models.
This paper describes the development and application of an easy-to-use agent-based Excel model that applies an extended version of The Department of Energy’s 2020 Residential Energy Consumption Database (RECS, final release, June 2023). The RECS Database has been extended by Jackson Associates to include whole-building and end-use 8,760 hourly kW loads for each of the 18,400+ households in its national survey.
Agent based models have been used in a variety of industry applications for decades to provide valuable insights not available with econometric and end use models. RECS Extended Hourly Loads Databases provide a relatively simple agent-based easy-to-use Excel framework to forecast future energy demands and hourly loads. Model forecasts reflect impacts of electric price, income and equipment efficiency increases along with various demand management initiatives and other factors on individual households.
This paper presents average state-level variations in whole building hourly kW load profiles along with an example that highlights the benefits of examining individual household load profiles in more detail. A comparative analysis of a single state’s average water heating hourly load profile and hourly loads for individual households illustrates the advantages of focusing on individual household characteristics to target the most appropriate households for smart gird, demand response and load control program development and analysis.
New RECS Whole Building and End-Use Hourly Loads Data Provide Insights on 18,400+ US Households to Support
Smart Gird, Demand Response and Load Control Analysis and Programs, February 6 2024
The Department of Energy’s 2020 Residential Energy Consumption Database (RECS, final release, June 2023) has recently been extended to include whole-building and seven end-use 8,760 hourly kW loads and emissions data for each of the 18,400+ households in the national survey.
This brief two-page note presents average state-level variations in whole building hourly kW load profiles along with an example that highlights the benefits of examining individual household load profiles in more detail. A comparative analysis of a single state’s average water heating hourly load profile and hourly loads for individual households illustrates the advantages of focusing on individual household characteristics to target the most appropriate households for smart gird, demand response and load control program development and analysis.
Avoid ESG Reputational Risk with Indexed Emissions Intensity Measures:
A 2-Page Primer, July 18 2023
I recently downloaded a bank’s ESG report that revealed an unexpected annual increase in Scope 3 financed emissions intensity. The report narrative suggested that a change in one of the data inputs could be to blame. In fact, the increase was a result of a faulty emission intensity calculation, a result likely to befall other organizations that ignore complexities in calculating accurate emissions intensities.
Emissions intensities (e.g., emission/mortgagor) are the most critical component of reported emissions. Annual comparisons provide stakeholders with a measure of an organization’s success in achieving emissions reductions targets. Inaccurate emissions intensity calculations can sabotage a firm’s public image by reflecting increased emissions intensity when the opposite is true. Or, in a worst-case scenario, result in an external audit showing that reported emissions intensity data are overestimating emissions improvements.
Reporting annual emissions intensity data based on simple aggregated emissions is guaranteed to provide misleading results as illustrated in this note. While this discussion is oriented to financial institutions, recommendations for calculating unbiased emissions intensities apply to all ESG emissions intensity calculations.
Mortgagor & CRE Emissions Calculations: A 3-Page Summary, June 21 2023
Financial institutions are facing increasing pressure to report Scope 3 financed emissions – that is, emissions of their mortgage and commercial real estate (CRE) customers. A soon-to-be issued SEC rule will likely require mid-to-large financial institutions to report these data.
Since these emissions can account for 90 – 95 percent of all financial institution emissions, a reliable calculation of current emissions is important. More critical are the year-to-year emissions intensity estimates (e.g., emissions/mortgagor) presented for investors to evaluate emissions improvements over time. Inaccurate emissions calculations and emissions intensity statistics can sabotage a financial institution’s public image by reflecting increased emissions intensities when the opposite is true. Or, in a worst-case scenario, result in an external audit showing that reported emissions intensities are overestimating emissions improvements.
This paper spares readers working through the 400+ pages of the SEC’s proposed rule documentation and 150+ page PCAF recommendations. The PCAF (Partnership for Carbon Accounting Financials) is an international organization of financial institutions that provides a guide to Scope 3 calculation methodologies sanctioned by the SEC. The methodologies presented here are the most accurate and up-to-date recommendations available consistent with PCAF and likely SEC guidelines.
Scope 3 Financed Emissions Reporting: Beware - How Good Intentions Can Lead to Bad Outcomes
April 18, 2023
A proposed SEC rule will soon (May?) likely require mid-to-large publicly traded financial institutions to
calculate and report emissions of their residential mortgagors and commercial real estate (CRE) loan customers
(so-called downstream or Scope 3 emissions).
This proposed rule creates a huge new reporting requirement, reputational risk, reporting pitfalls and a challenging data
development effort for financial firms.
While many financial institutions have already made a commitment to reporting Scope 3 emissions the new rule will prompt
more to embark on this process, even if the final rule is delayed by legal challenges The road to emissions reporting is
filled with hazards.
Results of this study using actual mortgagor data show that initial emission estimates with aggregate data can
set financial firms up for disappointing year-to-year emissions reductions reports that show increasing
emissions per mortgagor when mortgagor emission are actually declining.
Study results show that:
• accurately estimating emissions and year-to-year emissions changes requires at the least ZIP-level detailed data and
• unbiased annual emissions intensities require the application of economic price index methodologies to reflect changes in mortgagor population characteristics.
Will Increasing Utility Generation Renewables Make Natural Gas Bans Attractive in More States in the Future? Ten
Year Forecasts Identify 5 States as a Yes and 31 States as a No, March 28, 2023
Two weeks ago, we presented results of a study (see the publication below) that showed that bans on natural gas/propane (NG/P) water
heaters would increase both CO2e levels and consumer costs in 36 states. We decided to extend our analysis to reflect CO2e
impacts ten years in the future assuming the percent of solar and wind resources in each state increases at an annual rate observed
from 2019-2022 based on EIA-923 Report on Electric Utility Generation data. This study identifies the number of years, at the current
rate of utility renewables investment, that would be required to make a NG/P bans an attractive option for reducing CO2e levels.
See Data for all 48 continential states here
Be Careful What You Wish For: Natural Gas/Propane Water Heater Bans Would Increase Both Carbon Emissions and Energy Costs in 36 States, March 16, 2023
Laws passed in California, New York, and several other states to ban natural gas and propane water heating are
often presented as models for the rest of the nation. However, an independent study finds that this
policy would increase carbon emissions in 36 states by an average of 6 % and increase household energy
cost by $176 per year. Annual cost increases in all 48 states average $200.
See emissions and cost impacts for all states here
New Study Shows 2020 - 2022 State Homeowner Energy Cost Inflation Ranges from 24% to 62%, Februrary 16, 2023
New Hampshire is the bigest energy inflation looser. ME, VT, CT, MA, RI, NY, NJ CA and IL round
out the top ten hardest hit states. See all state rankings here
Inflation Will More Than Double “Seriously Delinquent” Mortgages in 2023.
January 24, 2023
Estimated 2023 90+ day delinquencies caused by 40 year-high inflation are provided by
state and county.
Avoiding Scope 3 Financed Emissions Data Development Pitfalls, June 2022
Indiana Electricity Projections:
The 2021 Forecast Indiana State Utility Forecasting Group, December 2021
- SCE Electric Vehicle (EV) Virtual Power Plant Analysis Shows $5,600 10-Year Savings Per EV Customer, October, 2019
- Reducing Customer Acquisition Costs and Sales Cycles in the Commercial Battery Storage/PV Market with Marketing Analytics, January 2016
- Maximizing Competitive Advantage in Storage and PV Markets, White Paper, October 2015
- Utility Planning for Disruptive Solar PV Impacts, White Paper, July 2015
Future Energy: Improved, Sustainable and Clean Options for our Planet,
Elsevier Science; 2nd edition, 2014
Indiana State Utility Forecasting Group Electricity Projections (Purdue University):
December, 2013 Forecast Using MAISY Agent-Based Models
Promoting energy efficiency investments with risk management
Energy Policy, 2010
Improving Energy Efficiency and Smart Grid Program Analysis With Agent-Based End-Use forecasting Models,
Energy Policy, 2010
White Paper: Are Smart Grids a Smart Investment?
Hourly Load Analysis of 800,000 Utility Customers at 200 of the Largest
US Utilities, 2009
- White Paper: Shining the Light on Smart Grid Investments:A Duke Energy Case Study, 2009
- White Paper: Top 10 Energy Efficient States, 2008
- Energy Budgets at Risk (EBAR) (J Jackson, Wiley, 2008) Provides New Energy-Efficiency Investment Evaluation Tools
Ensuring Emergency Power for Critical Municipal Services With Natural gas-fired Combined Heat and
Power (CHP) Systems, Energy Policy, 2007
- Are US Standby rates inhibiting Diffusion of Customer-Owned Generating Systems? Energy Policy, 2007
For Additional Information Contact:
Jerry Jackson, President
37 N. Orange Avenue, Suite 500
Orlando, Fl 32801