Engineering topics

Hoffman, Ian M.

Publications and source records attributed to Hoffman, Ian M..

4 records

DOE OSTI2020

Applying Non-Energy Impacts from Other Jurisdictions in Cost-Benefit Analyses of Energy Efficiency Programs: Resources for States for Utility Customer-Funded Programs

Avoided energy and capacity costs are the primary yardstick utilities use to determine which energy efficiency programs are cost-effective for their customers. But sometimes "non-energy impacts" — not commonly recognized as directly associated with energy generation, transmission and distribution — represent substantial benefits, such as improving comfort, air quality and public health. Considering whether and how to include non-energy impacts is an important part of cost-benefit analyses for these programs. This report offers practical considerations for deciding which non-energy impacts to include and how to apply values or methods from other jurisdictions. Researchers reviewed studies quantifying non-energy impacts used in 30 states and applied a five-point system to indicate transferability of a value or method from each study for 16 categories of non-energy impacts: Water resource costs and benefits; Other fuels costs and benefits; Avoided environmental compliance costs; Environmental impacts; Productivity; Health and safety; Asset value; Energy and/or capacity price suppression effects; Avoided costs of compliance with Renewable Portfolio Standard requirements; Avoided credit and collection costs; Avoided ancillary services; Comfort; Economic development and job impacts; Public health impacts; Energy security impacts; Increased reliability. The U.S. Department of Energy’s Building Technologies Office supported this work.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Cost of saving natural gas through efficiency programs funded by utility customers: 2012–2017

This study estimates the cost of saving a therm of natural gas from energy efficiency programs funded by utility customers during the period 2012 to 2017. Berkeley Lab researchers compiled and analyzed efficiency program data reported by investor-owned utilities and other program administrators in a dozen states representative of the four U.S. Census regions — Arkansas, California, Connecticut, Iowa, Massachusetts, Michigan, Minnesota, New Jersey, New York, Oklahoma, Rhode Island and Utah. Depending on the year, the dataset accounts for about 50 percent to 70 percent of annual national spending on natural gas efficiency programs. The estimated cost of saving natural gas during the study period is $0.40 per therm. The analysis also includes estimates of the program administrator cost of saved energy for three core sectors for natural gas: commercial and industrial, residential, and low-income households. It aggregates these sectors to provide regional and national values. Our metrics include savings-weighted averages, unweighted medians, and interquartile ranges (25th and 75th percentiles) of the levelized program administrator cost of saving gas, in constant 2017 dollars. In addition, the study analyzes cost trends during the study period, finding that average program costs trended downward. The U.S. Department of Energy’s Building Technologies Office supported this work.

03 NATURAL GAS↗

DOE OSTI2019

Cost of Saving Electricity Through Efficiency Programs Funded by Customers of Publicly Owned Utilities: 2012–2017

This report finds that energy efficiency programs for customers of publicly owned utilities saved electricity at an average cost of 2.4 cents per kilowatt-hour (kWh) from 2012 to 2017. Utilities use such cost performance metrics to assess effectiveness of efficiency program portfolios, determine what programs to offer customers, and, more broadly, ensure electricity system reliability at the most affordable cost as part of electric utility resource adequacy planning and resource procurement processes. The study analyzed efficiency program data reported by 111 program administrators for 219 publicly owned utilities in 14 states — about 90 percent of the municipal utilities and public utility districts that report the data to the Energy Information Administration (EIA). The data represent 88 percent of all spending and 75 percent of all savings that publicly owned utilities reported to EIA in those years. Berkeley Lab used data from several sources, including data provided directly by American Public Power Association members, publicly available annual reports and regional data collections.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

Peak Demand Impacts From Electricity Efficiency Programs

Quantification of the costs and benefits of electricity efficiency programs have focused largely on the economic value of annual energy reductions. State public utility commissions PUCs and utilities are increasingly interested in assessing peak demand impacts of these programs. The U.S. Energy Information Administration defines peak demand as "The maximum load during a specified period of time." In practice, utilities and grid operators use a wide range of definitions for peak demand. With increasing need for a more flexible and resilient electricity system, and changing costs for generation, utilities and other efficiency program administrators must take into account all characteristics of efficiency programs — including peak demand reduction — to ensure a reliable system at the most affordable cost. In this study, Berkeley Lab explored a new metric, the program administrator (PA) cost of saving peak demand (PA CSPD). We collected data on costs, energy savings and peak demand savings for electricity efficiency programs for 36 investor-owned utilities and other PAs in nine states (Arizona, Arkansas, California, Colorado, Illinois, Massachusetts, Maryland, New York and Texas) for 2014 to 2017. While some utilities report demand reductions for their electricity efficiency programs, there has been little sustained effort in the United States to gather peak demand reduction data or benchmark the cost of achieving peak demand impacts. As a first of its kind analysis, we developed a framework for analyzing peak demand savings across utilities and states and begin to quantify the cost of saving peak demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗