Cities Partner with NREL to Forge Pathways from Energy Data to Decision Making

This is a guest post by Megan Day, AICP, Project Leader at the National Renewable Energy Lab. It was originally published on the National Renewable Energy Laboratory’s Solar Technical Assistance Team (STAT) Blog for the U.S. Department of Energy’s Cities Leading through Energy Analysis and Planning (Cities-LEAP) and State and Local Energy Data (SLED) projects.

Cities are increasingly interested in pursuing a clean energy future. Many are setting ambitious goals to use clean, renewable energy or reduce air pollution from energy consumption. The challenge lies in establishing metrics, prioritizing actions, and targeting scarce resources in the most cost effective and strategic ways.

That’s where the U.S. Department of Energy’s Cities Leading through Energy Analysis and Planning (Cities-LEAP) and State and Local Energy Data (SLED) projects come in. With an often-overwhelming amount of data and analysis available, many cities are challenged when it comes time to advance from goal setting to taking action. To help create a clear pathway for cities to progress, NREL set out to understand the most pressing energy-related questions cities are asking, and then identify how available data and analysis could help inform their energy planning processes and decision making.

Cities-LEAP addresses all sectors

The Cities-LEAP and SLED projects teamed up with ten city partners to demonstrate how cities can use the wealth of city-specific energy data and analysis now available on the SLED site, coupled with new city policy analysis and other resources, to inform strategic decisions.

For each collaboration, NREL provided “micro” technical assistance to the partner city in the form of a short summary of the city’s energy profile and a response to the city’s specific energy questions.

Cities asked a range of questions, such as how the city could reduce its peak electricity demand to avoid building a new fossil-fueled generation plant, or what steps the city could take to build electric vehicle (EV) charging infrastructure to support a high penetration EV future. Others were curious to learn to what extent rooftop solar photovoltaic energy generation could contribute toward a 100% renewable electricity goal. Many of the cities also wanted to know how they could target their energy actions to benefit low- and moderate-income households.

The city energy profile data available on SLED—available for more than 23,400 cities—can fill data gaps, provide a high-level overview of a city’s energy context, and help cities identify the most effective energy actions to achieve their clean energy goals. The City Energy: From Data to Decisions series presents actual methods for using SLED data, which other cities can use to inform their individual strategic energy decisions for a clean energy future.

A bar chart showing the SLED results of small building rooftop PV potential analysis for San Jose, California.

The San Jose, California, “Data to Decisions” case study includes a small building rooftop PV potential analysis that is available for every U.S. city on SLED.

A bar chart showing the SLED results of a commercial buildings analysis for New Haven, Connecticut.

The New Haven, Connecticut, “Data to Decisions” case study includes a commercial buildings analysis that is available for all U.S. cities on SLED. This information can help cities estimate the potential scope and impact of commercial building energy benchmarking policies or programs.

A pie chart showing the SLED results of energy-related greenhouse gas emissions estimates for Columbia, Missouri.

The Columbia, Missouri, “Data to Decisions” case study shows energy-related greenhouse gas emissions estimates available for every U.S. city on SLED.

For more information, see the full City Energy: From Data to Decisions series.

AAEAAQAAAAAAAAvZAAAAJDhmY2RjZmZlLTA5Y2EtNDZiOC1iZjE4LTlkNDZjZGQ0MjgxMwAbout the Author: Megan Day, AICP, serves as the Project Leader for Solar Markets at the National Renewable Energy Lab.