Personal Electrification Planner Methodology
The savings estimates in the Personal Electrification Planner are for informational and planning purposes only and are based on limited information about your home, occupant usage patterns, and energy prices. They are not a guarantee or a promise of savings. Actual savings will differ based on a variety of factors, including but not limited to your actual energy usage, how much you pay for fuel and electricity, and characteristics of your home, such as your home’s level of insulation, surrounding tree cover, number of rooms, and the age and quality of your existing appliances.
Actual upfront costs for electrification upgrades in your home will differ based on a variety of factors; for example, a heat pump installation may be higher than the costs presented here if the project includes significant modifications to your duct system.
To estimate savings for heating and cooling, cooking, water heating, and clothes drying upgrades:
The savings and energy estimates are derived from simulations of buildings under various upgrade scenarios such as weatherization and swapping out fossil fuel appliances for efficient electric alternatives. These are modeled based on National Renewable Energy Laboratory (NREL)’s publicly available ResStock dataset. This dataset consists of 550,000 simulated residential building models that statistically represent every residential housing unit in the contiguous United States. For each simulated building, EnergyPlus, the Department of Energy’s open-source building energy modeling tool, is used to model energy used by every appliance in the building.
We model several energy efficiency and electrification scenarios, simulating upgrades to each building model and calculating the change in energy usage when the upgrade is applied to estimate savings. For the water heater, range, and dryer upgrades, we use the ResStock simulations as published in the End Use Savings Shape (EUSS) 2022 release. For the heat pump upgrade, our simulations are conducted on the same set of building samples used in EUSS 2022.
We then use your provided home profile to find a similar set of building models in ResStock based on your appliances’ fuel types, your county, and your home’s characteristics such as occupancy and square footage. Your savings estimates are calculated from the savings for similar building models. In situations where there are not enough building models in your county with similar characteristics, we aggregate savings estimates for similar homes in a larger geographic area, such as the state.
To translate methane gas and electric energy consumption to dollar amounts, we use revenues and sales volumes reported by your utility to the U.S. Energy Information Administration (EIA) to calculate an average county price, which we then apply to your estimated consumption. For propane and fuel oil consumption, we use historical energy prices from the EIA for your state. We estimate the greenhouse gas emissions using emissions factors included in ResStock from NREL, projecting emissions into the future in a scenario where 95% of our electricity comes from carbon-free sources by 2050.
To estimate savings for rooftop solar upgrades:
The savings and energy estimates for this upgrade are based on modeled datasets from NREL. We first estimate your potential electricity demand using electricity consumption data from similar homes in ResStock after their appliances have been upgraded to efficient electric alternatives.
Once we have an estimate of how much electricity your home would need if you electrified all major appliances (HVAC, water heater, dryer, and stove), we use NREL’s PVWatts, a tool that provides data on sunlight hours and solar system electricity generation throughout the US, to estimate the solar system size needed to meet your yearly electricity demand after electrification. We also estimate how large a system your roof might be able to support based on the square footage of your home. Using these two potential system sizes, we estimate how much electricity rooftop solar would generate on your home. We compare that potential electricity generation to the current electricity consumption of homes similar to yours to estimate your annual energy savings. We then translate those energy savings to dollar savings and greenhouse gas emissions using EIA data on fuel prices and NREL data on grid emissions described in greater detail above.
To estimate savings for transportation upgrades:
The savings and energy estimates for this upgrade are based on vehicle fuel efficiency data published by the Environmental Protection Agency (EPA). We use this data to estimate the average efficiency of various vehicle sizes and fuel types (for example, gasoline sedans and diesel trucks). We then calculate the average efficiency gains of upgrading from one of these vehicle categories to a similarly sized electric vehicle, like upgrading from a gasoline SUV to an EV SUV. We then use data from the U.S. Department of Transportation (DOT) to estimate how many miles a household in your county drives per year. We combine this mileage data with the efficiency data to estimate how much energy your household would save by switching all driving from your primary vehicle to a similarly sized EV. These estimated household energy savings are then translated to dollar savings and greenhouse gas emissions using EIA data on fuel prices and NREL data on grid emissions described in greater detail above.
To estimate the upfront costs for all upgrades:
The upfront costs of heat pumps, heat pump water heaters, solar panels, and panels & wiring are estimated using publicly available datasets which include project costs for various electrification upgrades. These datasets include the Massachusetts Residential Air-Source Heat Pump Program, Massachusetts Whole Home Pilot, TECH Clean California, and LBNL. For heat pumps, we use these datasets to predict costs based on home square footage, climate zone, ducting configuration, and heat pump efficiency and size (where the heat pumps are sized based on EnergyPlus modeling). For solar panels, we use this LBNL dataset to predict costs based on square footage, which determines both energy demand and rooftop size. The cost for heat pump water heaters reflects median costs from the TECH Clean CA dataset. For panels and wiring, we calculate the median difference in cost between projects that required a panel upgrade or a new circuit and projects that did not. The upfront costs of insulation are determined by matching the measures included in the ResStock insulation packages with measures reported in an LBNL report on the costs of decarbonization. For heat pumps and solar panels, we then use the home characteristics you provide, such as home size, to predict your upfront costs.
We adjust for inflation using a Producer Price Index and adjust for location using RS Means materials & labor cost factors. All costs represent estimated total project costs, including both equipment and installation.
The upfront costs of stoves, dryers, and electric vehicles do not vary by location and are estimated using prices available online. These upfront costs represent an approximate lower bound on what you might spend, though some households may choose to spend more for a higher-end appliance or vehicle.
How your estimates might change over time:
We are constantly improving our savings and upfront cost models, so the savings numbers presented by this tool are likely to change over time. We expect future savings estimates will be more accurate due to improvements such as including local variation in utility rates, expanding our building model dataset, and improving our upfront cost models.