Gas Task Force

Modeling and Analytical Tools

This section provides an overview of the quantitative tools used to evaluate the natural gas system, or specific components of the system, to estimate future conditions, effectiveness of different technologies, and options for meeting targeted outcomes. The tools below are essential for evaluating planning options that improve affordability, clean energy, economic development, or reliability outcomes while maintaining integrity of the gas distribution system. 

Tools discussed include: 

  1. Life Cycle Analysis
  2. Hydraulic Modeling
  3. Pathways Analysis
  4. Demand Forecasting
  5. Techno-Economic Analysis
  6. Benefit Cost Analysis
  7. Bill Impact Analysis
  8. Energy Wallet Analysis

1. Life Cycle Analysis (LCA): LCA provides emissions and environmental impacts of different technologies, fuels, and energy systems. LCAs are useful for comparing different emissions reductions strategies (alternative fuels, carbon capture, etc.) and their associated benefits.  

  • Types: There are several different types of approaches to LCA depending on the scope, boundaries, and purpose of the analysis.
    • Cradle-to-Grave: Considers the entire lifecycle from production (cradle) through distribution to end-use (grade).
    • Cradle-to-Gate: Includes all production processes up until the energy leaves the production area (gate).
  • Examples: 
    • Argonne National Laboratory’s GREET model can be used to perform life cycle analysis to “assess the environmental impacts associated with technologies, fuels, products, and energy systems across various stages of the supply chain”. CenterPoint Energy in Minnesota developed a modified version to measure the lifecycle GHG emissions associated with programs proposed under its Natural Gas Innovation Plan.
    • National Renewable Energy Laboratory’s Materials Flows through Industry (MFI) modeling tool tracks models material and energy use, along with related greenhouse gas emissions, across manufacturing supply chains.
    • The Government of Canada's Fuel LCA Model can be used to calculate the life cycle carbon intensity of fuels and energy sources used or produced in Canada. 
    • The US EPA’s Tool for Reduction and Assessment of Chemicals and Other Environmental Impacts (TRACI) is an environmental assessment resource that provides characterization factors for LCA, industrial ecology, and sustainability metrics. It can be applied across processes, products, facilities, companies, and communities. 
  • Opportunities and limitations: LCA provides an opportunity to perform holistic emissions accounting of different technologies, fuels, and energy systems. LCAs also provide a common framework to evaluate different technologies. However, care needs to be taken to ensure that the inputs are carefully considered and appropriate for the jurisdiction and context for which they are being used. Further, the choice of system boundaries (what is included or excluded in the supply chain) can greatly influence results.

2. Hydraulic Modeling: Hydraulic modeling studies volumetric flows along the gas system and is used for evaluating system pressure, temperature, and composition throughout a pipeline system. Used for gas system planning and optimization, hydraulic modeling is important for identifying potential reliability issues or expansion to support growth. It can also reveal opportunities to decommission parts of the gas system with low throughput and feasibility to switch to an alternative fuel (e.g., electricity, propane).

  • Types: There are several types of hydraulic modeling analyses that can be employed for different purposes such as planning, operations, design, and emergency responses. Examples include:
    • Capacity modeling determines the maximum load that the system can accommodate without violating pressure limits.
    • Design models support engineering design of new pipelines, regulators, metering stations, etc.
    • Integrated supply-demand modeling combines hydraulic modeling with market or dynamic forecasting tools.
    • Contingency scenario modeling simulates abnormal or emergency conditions
  • Examples: 
  • Opportunities and limitations: Hydraulic modeling is a widely adopted tool in the natural gas utility industry to inform design, planning, supply, and contingency planning decisions. However, hydraulic modeling is often time-intensive and is not dynamic (i.e., can evaluate only one scenario at a time). Hydraulic modeling has not traditionally been used for decarbonization or non-pipeline alternative planning, so tools likely need to be adapted to be used in these contexts. 

3. Pathways Analysis: Pathways analyses create different scenarios that evaluate potential future outcomes given a range of varying assumptions including load forecasts, technology deployment, costs, and other variables. In gas LDC planning, these analyses have been used to evaluate optimal portfolios of strategies for achieving climate and energy policy goals.

  • Types: The scope of pathways analyses will depend on the context for performing the analyses and/or regulator requirements. There many variables that can be studied, such as:
    • Types of technologies evaluated (electrification, network geothermal, low-carbon fuels, etc.)
    • Infrastructure constraints (geographical or technical constraints, no new infrastructure, targeted investments for certain customers, etc.)
    • Regulatory structures and rate design (regulatory assets, depreciation timelines, novel rate designs, etc.)
    • Emissions constraints (target date goal, glide path over analysis period)
  • Examples:
    • The Massachusetts D.P.U. Docket 20-80 assesses the future role of gas LDCs in helping the state achieve its goal of net-zero greenhouse gas emissions by 2050. The state previously used pathway analysis to develop its Clean Energy and Climate Plans for 2025 and 2030 and 2050. 
    • A future of gas proceeding organized by the Rhode Island Public Service Commission examines the future of the regulated gas distribution business in Rhode Island in light of the state's Act on Climate, which mandates significant greenhouse gas (GHG) emissions reductions: 45% by 2030, 80% by 2040, and net-zero by 2050 compared to 1990 levels.
    • Several New York gas LDCs have used pathway analysis as a tool to inform the development of the utilities’ long-term plans. 
  • Opportunities and limitations: Pathways analysis is a valuable tool for evaluating how different regulatory and policy targets or objectives can affect the achievement of a stated goal or objective over a long analysis horizon. This kind of analysis can identify the sets of technologies and solutions needed to achieve a desired outcome, but many pathway models capture static or simplified snapshots rather than fully dynamic interactions, feedback loops, or evolving uncertainties in real-world systems over time. Further, pathway analyses often do not treat uncertainties or variability in key inputs, leading to point estimates or deterministic conclusions rather than probabilistic risk assessments.

4. Demand Forecasting: Load forecasts estimate how much load will exist in the future, based on assumptions such as total customer count, weather, and usage per customer. These forecasts are often inputs for other models like pathways analysis 

  • Types: There several different types of demand forecasting models depending on the time horizon and forecasting objectives. They may include one or more of the following elements:
    • Short-term forecasting for operating planning and load scheduling
    • Medium-term forecasting for seasonal planning and gas supply planning
    • Long-term forecasting for infrastructure plans, decarbonization, IRPs
    • Time series models rely on historic demand patterns to predict future demand
    • Weather-normalized models rely on regression analyses to adjust depend forecast based on temperature (i.e., heating degree day) sensitivity
    • Econometric models account for economic and demographic drivers
    • End-use-modeling build up aggregate demand from appliance, building, neighborhood, etc. to system-level demand
  • Examples:
    • As part of the company’s Integrated Capacity and Delivery Plan, Atlanta Gas Light relies on a regression analysis tool to develop demand forecast over the next 10 years
    • As part of the future-of-gas proceedings and long-term gas planning proceedings such as the ones identified above, gas LDCs are required to develop short-term and long-term demand for natural gas in their service territories. 
  • Opportunities and limitations: Demand forecasting is a standard and widely used analysis in the natural gas industry for operational, gas supply, and infrastructure planning. Demand forecasting can also be used within the context of developing strategies to achieve a stated goal (i.e., integrated energy planning, pathways analysis, etc.). Long-term demand forecasts must account for whether historical data accurately reflects the conditions expected in the medium- to long-term gas system. For instance, shifts in customer preferences or changes in climatic patterns may warrant updates to design day parameters.

    5. Techno-Economic Analysis (TEA): Serves to evaluate the technical and economic feasibility of emerging technologies (like hydrogen and renewable natural gas), usually in comparison with incumbent counterparts (like natural gas).

    • Types: There are different types of techno-economic analyses:
      • Technology feasibility and cost analyses evaluate whether and when a new or alternative technology is technically viable and cost-effective.
      • Fuel-switching analyzes the economics and system impacts of switching from natural gas to an alternative fuel (e.g., electricity, alternative fuels, etc.)
      • Infrastructure investment planning support decision making for long-term investments in pipeline infrastructure, storage, or other assets
    • Examples:
      • Pacific Northwest National Laboratory Laboratory has developed TEA tools to assess the techno-economics of conversion of biomass to fuels for various feedstocks and pathways including Hydrothermal Liquefaction and Upgrading TEA (HTL Upgrading TEA), PNNL Biological TEA (BC-TEA), Pyrolysis TEA (FP-TEA), and Syngas TEAs (IDL).
      • Argonne National Laboratory has developed several TEA tools to evaluate the costs of hydrogen delivery, including the Hydrogen Carrier Scenario Analysis Model (HCSAM) which is TEA  model comprising state-of-the-art data covering the entire supply chain of ammonia (NH3) as a hydrogen carrier and the Hydrogen Delivery Scenario Analysis Model (HDSAM) model that can estimate the levelized cost [dollars per kilogram] of hydrogen delivery via pipeline, gaseous truck, and liquid truck, including refueling.
      • NREL’s Hydrogen Financial Analysis Scenario Tool (H2FAST) provides in-depth financial analysis for hydrogen and nonhydrogen systems and services.
      • Energetic’s DOE-funded Techno-economic, Energy, & Carbon Heuristic Tool for Early-Stage Technologies (TECHTEST) Tool is a spreadsheet tool that integrates both the lifecycle assessment and techno-economic assessment methods to evaluate the carbon, energy and cost impacts of a new technology. 
    • Opportunities and limitations: Techno-economic analyses are useful for quantifying trade-offs between cost, performance, emissions, and reliability across different technologies or pathways. Another strength of this type of analysis is that it  incorporates engineering and technical feasibility. However, like many analytical tools, techno-economic analysis is highly sensitive to underlying inputs. Important parameters such as levelized cost, payback period, or return on investment are all highly sensitive to underlying assumptions and scenario choices. Further, techno-economic analyses often assume static consumer behaviors and market dynamics.

    6. Benefit Cost Analysis (BCA): BCAs are commonly used to estimate the effectiveness of programs, like energy efficiency and non-pipeline alternatives, by compiling costs and benefits and evaluating if the benefits outweigh its costs.

    • Types: There are several different types of BCAs which have different scopes, depending on the prospective from which benefits and costs are being evaluated and the desired outcome being incentivized. See below for examples:
      • Societal Cost Test: Considers the broader benefits to society, including externalities like avoided emissions
      • Utility Cost Test: Evaluates costs and benefits directly attributable and observed by the utility administering a program.
      • Total System Benefit: Considers costs and benefits to all stakeholder, not just the program participants.
      • Total Resource Cost: Considers the total costs of a project/program such as administrative, ratepayer, out-of-pocket costs, etc.
      • Ratepayer Impact Measure: Evaluates how rates for non-participating customers will change due to a utility program 
    • Examples and resources: 
    • Opportunities and limitations: Standard BCA frames have been developed by practitioners (e.g., CA, NY) and can be used to evaluate proposed programs or investments, relative to an alternative, centered on meeting a specific objective, like affordability or clean energy goals. Jurisdiction-specific BCAs have also been developed (e.g., MassSave in Massachusetts). While a BCA can help inform whether the benefits of a proposed program outweigh its costs, a regulator may need to evaluate additional factors not considered in the BCA (e.g., feasibility) when evaluating a program. In fact, some non-monetizable or hard-to-monetize benefits such as ecosystem services are difficult to incorporate into BCAs.

    7. Bill Impact Analysis: Bill impact analysis for gas utility customers involves quantifying how changes in utility rates, programs, or capital investments will affect the total bills paid by residential, low-income, and commercial/industrial customer classes. This analysis goes beyond rate increases alone—it incorporates changes in consumption (from efficiency programs), changes in rate structure, and any resulting avoided costs or benefits. The goal is to provide a comprehensive understanding of both the costs and benefits to customers under different scenarios. 

    • Opportunities and limitations: Bill impact analysis is helpful for identifying how bills for customers or specific customer classes might change as a result of a behavioral or programmatic change. Bill impact analyses are limited in that they do not consider other energy and non-energy bills paid by customers.
    • Examples:
      • The Brattle Group assessed the effectiveness of New Jersey’s utility bill assistance programs (LIHEAP, USF, Lifeline, and New Jersey SHARES) by examining their impact on reducing energy burdens for participating households, using a dataset of more than 200,000 households that received assistance during 2023–2024. 
      • Advanced Energy United and Strategen modeled how updated rate designs and energy efficiency programs by Consumers Energy in Michigan would impact average gas bills across customer classes, including projections over multiple years showing bill volatility, customer savings from efficiency, and the allocation of infrastructure costs. 

    8. Energy Wallet Analysis: An energy wallet analysis evaluates a customer’s total energy costs including electricity, heating fuels, etc. and how that changes with certain decisions (i.e. electrification)

    • Types: Energy wallet analyses can change depending on the context with which they are used. In addition to those discussed above under bill impact analyses, the following are specific to energy wallet analysis:
      • Household-level energy wallet analysis provides a comprehensive look at all energy costs incurred by a single household
      • Comparative technology wallet analyses compares the lifecycle costs for different technologies for a household or business
      • Income-stratified energy wallet analysis evaluates energy wallet by income level often to evaluate equity impacts
    • Examples:
      • EPRI recently conducted an energy wallet analysis for each state, evaluating how much an average household spends on electricity, natural gas, gasoline, and other fuels in each state.
    • Opportunities and limitations: The energy wallet analysis improves upon a bill impact analysis in that takes a more comprehensive account of customer’s energy costs. This new type of analysis can provide more holistic insights into bill burdens that different customers may face. However, energy wallet analyses are limited by data availability and quality to accurately measure income, demographic, and housing data. Energy wallet analysis can also over-simplify household economic factors, for example by not considering other recurring non-energy bills that may affect affordability.