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2026
Presentation
Title
De-risking Industrial Energy Efficiency. Evidence from Europe’s Largest Project Database
Title Supplement
Presentation at eceee Zero Carbon Industry 2026, Rome, 04.02.-05.02.2026
Abstract
The Energy Efficiency Financial Institutions Group (EEFIG), established by the European Commis-sion’s Directorate-General for Energy and United Nations Environment Program Finance Initiative (UNEP FI) in 2013, fosters dialogue between financial institutions, industry, and experts on long-term financing of energy efficiency. One of its central outcomes is the support for the De-risking Energy Efficiency Platform (DEEP), launched in 2016 and today the largest pan-European open-source database of energy efficiency projects.
DEEP currently contains detailed technical and financial data on more than 37.000 projects in in-dustry and buildings, contributing by 32 data providers. The database covers projects from the European Union as well as the United States. The platform enables robust benchmarking of in-vestment performance, using in particular two key metrics: avoidance cost and payback time. This evidence base supports both investors and policymakers in assessing the risks and profitability of energy efficiency measures.
In this contribution, we analyze the industrial segment of the DEEP database, which represents a significant share of the total projects. We consider influencing factors such as company size, sec-tor and type of measure. We discuss the distribution of projects across countries and the role of dominant contributors. Our analysis of industrial projects illustrates typical ranges of payback times and avoidance costs, underlining the high cost-effectiveness of many measures while also revealing persistent gaps in data quality and coverage.
In addition, we discuss remaining challenges in data collection and coverage, including the limited information on co-benefits beyond energy and cost savings. By shedding light on both strengths and limitations, the paper aims to support the use of DEEP as a reliable evidence base for scaling up energy efficiency investments in industry and buildings.
DEEP currently contains detailed technical and financial data on more than 37.000 projects in in-dustry and buildings, contributing by 32 data providers. The database covers projects from the European Union as well as the United States. The platform enables robust benchmarking of in-vestment performance, using in particular two key metrics: avoidance cost and payback time. This evidence base supports both investors and policymakers in assessing the risks and profitability of energy efficiency measures.
In this contribution, we analyze the industrial segment of the DEEP database, which represents a significant share of the total projects. We consider influencing factors such as company size, sec-tor and type of measure. We discuss the distribution of projects across countries and the role of dominant contributors. Our analysis of industrial projects illustrates typical ranges of payback times and avoidance costs, underlining the high cost-effectiveness of many measures while also revealing persistent gaps in data quality and coverage.
In addition, we discuss remaining challenges in data collection and coverage, including the limited information on co-benefits beyond energy and cost savings. By shedding light on both strengths and limitations, the paper aims to support the use of DEEP as a reliable evidence base for scaling up energy efficiency investments in industry and buildings.
Author(s)
Conference
Language
English