Breaks down how Mass households heat by fuels including comparison to rest of New England.

Estimate of energy prices for heating fuels for the 2025/26 Winter Heating Season

In 2009, National Grid started a DER pilot program that offered technical support and financial incentives to qualified Massachusetts homeowners who planned and successfully completed a retrofit that incorporated the performance requirements and goals of the National Grid DER measures package. This DER measures package, developed through collaboration with Building Science Corporation (BSC), includes specific thermal and airtightness goals for the enclosure components as well as health, safety, durability, and indoor air quality requirements. By providing measures that can be included with common renovation activities such as roof replacement, window replacement, re-siding, basement remediation, and remodeling, this DER measures package is expected to have widespread application for existing homes in the New England area. The post-retrofit performance and cost ranges provided by this research project can provide concrete input for homeowners who are considering a DER. Field test data available for air tightness measured using blower door test. House 1 - Address Belchertown, MA 01007, Notes: Energy Savings: 75%, Company: Clark House 2-1 and 2 - Address (1) Brownsberger, MA 02478 and (2) Belmont, MA 02478, Notes Energy Savings: 73%, Company: Brownsberger House 3 - Address Millbury, MA 01527, Notes Energy Savings: 31%, Company: Tweedly House 4 - Address Milton, MA 02186 Notes Energy Savings: 42%, Company: Koh House 5 - Address Quincy, MA 02169, Notes Energy Savings: 57%, Company: Hall House 6-1 and 2 - Address Arlington, MA 02476, Notes Energy Savings: 55%, Company: Venable-Hwang House 7 - Address Newton, MA 02459, Notes Energy Savings: 42%, Company: Lavine House 8-1, 2, and 3 - Address Jamaica Plain, MA 02130, Notes Energy Savings: 43%, Company: Buhs House 9 - Address Northampton, MA 01060, Notes Energy Savings: 49%, Company: Wick House 10 - Address Lancaster, MA 01523, Notes Energy Savings: 40%, Company: Habitat for Humanity of North Central Massachusetts House 11 - Address Brookline, MA 02445, Notes Energy Savings: 27%, Company: Aquiline House 12 - Address Westford, MA 01886, Notes Energy Savings: 30%, Company: Atkins House 13 - Address Gloucester, MA 01930, Notes Energy Savings: 35%, Company: Cunningham

TO4 Task 3.1 - K Hovnanian Chicago, IL DOE Challenge Home Program Certified Home Constructed and Verified Specifications DOE Challenge Home Building envelope Ceiling R-49 blown fiberglass, Grade I Walls 2x4 framing @ 16 o.c. with R-13 fiberglass batts, Grade I and 1"" R-5 extruded polystyrene (XPS) insulating sheathing Frame Floors R-38 blown fiberglass, Grade I Basement Walls R-19 fiberglass batts draped full height, Grade I Basement Slab uninsulated Windows Above Grade: ENERGY STAR certified, U=0.29, SHGC=0.28 Basement: Non ENERGY STAR certified, U=0.29, SHGC=0.24 Infiltration 2 ACH 50 Mechanical systems Heat 95% AFUE sealed combustion natural gas furnace in conditioned space Goodman GMH950703BXAF Cooling 13 SEER split system Goodman GSX130301BC DHW AO Smith Vertex 100 0.96 EF natural gas tank water heater in 2nd floor utility closet Hot Water Distribution Redesigned trunk and branch Compliant with EPA WaterSense Efficient Distribution Requirements Ducts Located 100% in conditioned space via floor joists leak free to outside (5% or less) Ventilation Central Fan Integrated Supply (CFIS) ventilation with 6"" insulated outside air duct Fan Controller: Air Cycler FRV, with 6"" motorized damper 50 CFM outside air flow, 33% duty cycle (10 minutes on, 20 minutes off); ASHRAE 62.2-2010 compliance via an exhaust fan - Panasonic FV-08VQ5 WhisperCeiling Rerturn Pathways Active Return at Master Bedroom Transfer Grilles in Secondary Bedrooms Appliances, Lighting, MELs Lights 80% ENERGY STAR certified CFL Appliances ENERGY STAR certified refrigerator, dishwasher, and clothes washer; Natural gas range/oven and clothes dryer" STRUCTURE - Test House Lot 145 - 2013 DOE Challenge Test House Task 3.1 Bolingbrook, IL 60490 House is constructed and is DOE Challenge Verified by Don Nelson, a local rater. The purpose of this project was to evaluate integrated packages of advanced measures in individual test homes to assess their performance with respect to Building America Program goals, specifically compliance with the DOE Challenge Home Program. To that end, Building Science Corporation (BSC) consulted on the construction of five test houses by three cold climate production builders in three separate U.S. cities. (1) K. Hovnanian Homes, Chicago, Illinois (2) David Weekley Homes, Denver, Colorado (3) Transformations, Inc., Devens, Massachusetts. Overall, the builders have concluded that the energy related upgrades (either through the prescriptive or performance path) represent reasonable upgrades. The builders commented that while not every improvement in specification was cost effective (as in a reasonable payback period), many were improvements that could improve the marketability of the homes and serve to attract more energy efficiency discerning prospective homeowners. However, the builders did express reservations about the associated checklists and added certifications. An increase in administrative time was observed with all builders. The checklists and certifications also inherently increase cost due to: (1) Adding services to the scope of work for various trades, such as HERS Rater and heating, ventilation, and air conditioning contractor. (2) Increased material costs related to the checklists, especially the U.S. Environmental Protection Agency Indoor airPLUS and WaterSense Efficient Hot Water Distribution requirement. Ceiling - 18" cellulose Walls - 12" open cell spray foam in double stud walls Foundation - R-10 under slab, 3 1/2" closed-cell spray foam at walls Windows - Harvey U=0.20, SHGC=0.22 Infiltration - 1.0 sq in per 100 sq ft Heating - Mini split heat pump, 10.6 HSPF, 23 SEER Cooling - Mini split heat pump, 10.6 HSPF, 23 SEER DHW - 0.97 EF instantaneous propane water heater Ventilation - bathroom exhaust fans as basic option, HRV upgrade option Adams Circle Devens MA 01434 Cavite Street Devens, MA 01434

Morocco MA: Renewable Energy Consumption: % of Total Final Energy Consumption data was reported at 11.317 % in 2015. This records a decrease from the previous number of 11.719 % for 2014. Morocco MA: Renewable Energy Consumption: % of Total Final Energy Consumption data is updated yearly, averaging 16.290 % from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 23.505 % in 2004 and a record low of 11.317 % in 2015. Morocco MA: Renewable Energy Consumption: % of Total Final Energy Consumption data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Energy Production and Consumption. Renewable energy consumption is the share of renewables energy in total final energy consumption.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted Average;

Heating oil price in the United States has peaked in winter 2022/23 at 4.31 U.S. dollars per gallon and has decreased ever since. Heating oil is a liquid petroleum product that is, among other things, used in residential buildings as a fuel oil in furnaces or boilers. Chemically, most heating oils are similar to motor diesel fuels and are often sold interchangeably. Forecast heating price in the U.S. The average price of heating oil in the United States in the winter of 2024/25 is expected to reach 3.44 U.S. dollars per gallon. Energy prices are projected to see a decrease this winter, because of increased production of heating fuels. The number of heating degree days, which are the days in which the average temperature is below 18 degrees Celsius (65 degrees Fahrenheit), also helps quantify the energy demand required to heat a building. What determines heating oil price? Generally, heating oil prices are collected during the heating season between October and March. In the U.S., the greatest determining factor for heating oil prices is the WTI crude oil price. Consumers can lower heating oil bills by considering when they purchase, reducing consumption, and through government assistance programs.

The Department of Energy Resources (DOER) tracks the number of electric and natural gas utility customers switching to competitive supply services. Now including Community Choice Electricity Aggregation (CCEA) data.

Morocco MA: Access to Electricity: Rural: % of Population data was reported at 100.000 % in 2016. This records an increase from the previous number of 99.562 % for 2015. Morocco MA: Access to Electricity: Rural: % of Population data is updated yearly, averaging 51.300 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 100.000 % in 2016 and a record low of 10.151 % in 1990. Morocco MA: Access to Electricity: Rural: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Energy Production and Consumption. Access to electricity, rural is the percentage of rural population with access to electricity.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;

This dataset consists of summer temperature metrics for Boston, MA. These heat metrics summarize six CAPA Urban Heat Watch program temperature and heat index datasets using geographical boundaries from the Hexagons (Hexagons_25ha) layer. Heat datasets were created by Museum of Science, Boston, and the Helmuth Lab at Northeastern University. Heat metrics are presented in the attribute table as mean values of each Heat Watch program dataset for all hexagon features. The six heat values included in this table are July 2019 temperature and heat index in degrees Fahrenheit for each of 3 1-hour periods -- 6 a.m., 3 p.m., and 7 p.m. EDT. The geographic boundaries used to summarize the heat metrics are current as of 2019.

Morocco MA: Access to Electricity: Urban: % of Population data was reported at 100.000 % in 2016. This records an increase from the previous number of 99.602 % for 2015. Morocco MA: Access to Electricity: Urban: % of Population data is updated yearly, averaging 94.600 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 100.000 % in 2016 and a record low of 84.700 % in 1992. Morocco MA: Access to Electricity: Urban: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Energy Production and Consumption. Access to electricity, urban is the percentage of urban population with access to electricity.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted average;

The CFD (computational fluid dynamics) results for the Mass of Water Turbine (MOWT) current energy converter from MWNW Consulting (formerly Ecosse IP). Each case is self-contained in its own tar.gz archive file. The archive contains the scripts required to perform a full simulation using OpenFOAM v1906. The scripts to process the output and plot forces are included in "Plotting Scripts", and all computational meshes generated are included in "Computational Grids". Project is part of the TEAMER RFTS 2 (request for technical support) program.

Morocco MA: Energy Intensity Level of Primary Energy: MJ per PPP of(GDP) Gross Domestic Product2011 Price data was reported at 3.155 MJ in 2015. This records a decrease from the previous number of 3.239 MJ for 2014. Morocco MA: Energy Intensity Level of Primary Energy: MJ per PPP of(GDP) Gross Domestic Product2011 Price data is updated yearly, averaging 3.450 MJ from Dec 1990 (Median) to 2015, with 26 observations. The data reached an all-time high of 3.744 MJ in 2005 and a record low of 3.155 MJ in 2015. Morocco MA: Energy Intensity Level of Primary Energy: MJ per PPP of(GDP) Gross Domestic Product2011 Price data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank: Energy Production and Consumption. Energy intensity level of primary energy is the ratio between energy supply and gross domestic product measured at purchasing power parity. Energy intensity is an indication of how much energy is used to produce one unit of economic output. Lower ratio indicates that less energy is used to produce one unit of output.; ; World Bank, Sustainable Energy for All (SE4ALL) database from the SE4ALL Global Tracking Framework led jointly by the World Bank, International Energy Agency, and the Energy Sector Management Assistance Program.; Weighted Average;

The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low- and moderate-income (LMI) communities they serve. The LEAD Tool provides estimated LMI household energy data based on income, energy expenditures, fuel type, housing type, and geography, which stakeholders can use to make data-driven decisions when planning for their energy goals. From the LEAD Tool website, users can also create and download customized heat-maps and charts for various geographies, housing, energy characteristics, and population demographics and educational attainment.

Datasets are available for 50 states plus Puerto Rico and Washington D.C., along with their cities, counties, and census tracts, as well as tribal areas. The file below, "01. Description of Files," provides a list of all files included in this dataset. A description of the abbreviations and units used in the LEAD Tool data can be found in the file below titled "02. Data Dictionary 2022". A list of geographic regions used in the LEAD Tool can be found in files 04-11.

The Low-Income Energy Affordability Data comes primarily from the 2022 U.S. Census American Community Survey 5-Year Public Use Microdata Samples and is calibrated to 2022 U.S. Energy Information Administration electric utility (Survey Form-861) and natural gas utility (Survey Form-176) data. The methodology for the LEAD Tool can viewed below (3. Methodology Document).

For more information, and to access the interactive LEAD Tool platform, please visit the "10. LEAD Tool Platform" resource link below.

For more information on the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA), please visit the "11. CELICA Website" resource below.

Accurate dynamic energy simulation is important for the design and sizing of district heating and cooling systems with geothermal heat exchange for seasonal energy storage. Current modeling approaches in building and district energy simulation tools typically consider heat conduction through the ground between boreholes without flowing groundwater. While detailed simulation tools for subsurface heat and mass transfer exist, these fall short in simulating above-surface energy systems. To support the design and operation of such systems, the study developed a coupled model including a software package for building and district energy simulation, and software for detailed heat and mass transfer in the subsurface. For the first, it uses the open-source Modelica Buildings Library, which includes dynamic simulation models for building and district energy and control systems. For the heat and mass transfer in the soil, it uses the TOUGH simulator. The TOUGH family of codes can model heat and multi-phase, multi-component mass transport for a variety of fluid systems, as well as chemical reactions, in fractured porous media. The study validated the coupled modeling approach by comparing the simulation results with one from the g-function based ground response model. It then looked into effects when the water table and the regional groundwater flow are considered in the ground, from the perspective of heat exchange between borehole and ground, and the electrical consumption of the district heating and cooling systems. To access the simulation models, please find the links in the submission: -- For coupled approach validation: see model Buildings.Fluid.Geothermal.Borefields.Examples.BorefieldsWithTough and Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from the "Modelica Building Library" resource, branch issue1495_tough_interface, commit a2667c0. -- For the study of the effect of water table: see model Buildings.Examples.DistrictReservoirNetworks.Examples.Reservoir3Variable_TOUGH from he "Modelica Building Library" resource, branch issue1495_tough_interface_moreIO, commit 760de49. The coupling interface script "GrounResponse.py" can be found from the above links in the folder Buildings/Resources/Python-Sources. Also, the needed files for TOUGH simulation are in the folder Buildings/Resources/Python-Sources/ToughFiles that can be accessed through the above links. A brief description of these files is given below; detailed specifications for the first three files may be found in the TOUGH3 Users Guide (Jung et al., 2018) https://tough.lbl.gov/documentation/tough-manuals/. (1) INCON - initial conditions for each grid block (2) INFILE - main input file with material properties and control parameters (3) MESH - description of the computational grid (4) readsave - Modelica/TOUGH interface program: read the final output of TOUGH simulation after TOUGH time step and prepare for transfer to Modelica for next Modelica time step (5) readsave.inp - input parameters for program readsave (6) writeincon - Modelica/TOUGH interface program: write the output of Modelica after Modelica time step and prepare for transfer to TOUGH as initial conditions for the next TOUGH step (7) writeincon.inp - input parameters for program writeincon

View lists of all the electricity generating facilities that have been qualified for the RPS and APS Programs by DOER.

This dataset consists of summer temperature metrics for Boston, MA. These heat metrics summarize six CAPA Urban Heat Watch program temperature and heat index datasets using geographical boundaries from the Census Tract (CT) layer. Heat datasets were created by Museum of Science, Boston, and the Helmuth Lab at Northeastern University. Heat metrics are presented in the attribute table as mean values of each Heat Watch program dataset for all hexagon features. The six heat values included in this table are July 2019 temperature and heat index in degrees Fahrenheit for each of 3 1-hour periods -- 6 a.m., 3 p.m., and 7 p.m. EDT. The geographic boundaries used to summarize the heat metrics are current as of 2019.