Periodic Reporting for period 1 - TEIIF (TRACKING ENERGY INNOVATION IMPACTS FRAMEWORK)
Reporting period: 2020-04-01 to 2021-09-30
To date, the focus has been on the gathering of data on inputs into the innovation process. There has been substantially less activity trying to define meaningful metrics to track the impacts – or outputs – from clean energy technology innovation. Such metrics would allow for a more rigorous comparative analysis of the relative performance of innovation support for different technologies. Crucially, having metrics to track innovation outputs is a prerequisite to link impact of innovation inputs to the progress of clean energy technology innovation. Without the two datasets it is challenging to understand impact, which is important to assess support mechanisms and inform decision making on funding and support.
The objective of the TEIIF project was to provide insights into the impact that innovation, particularly through RD&D, is having on progress in clean energy technologies and the transformation of energy systems globally. Please note, progress in energy technology is driven by many factors, of which RD&D is one. The project did not attempt to assess the level of causality between inputs and outputs. That type of analysis would require additional metrics that affect several technologies simultaneously but also the impact of economies of scale in manufacturing, demand-pull policies, etc. The approach explored does not address RD&D policies or RD&D funding, nor does it attempt to prove a causal link between progress made and RD&D funding or policies. It does explore what innovation and market dynamics have achieved together and highlights areas for additional research.
- Existing data sets are updated to include the latest data for renewable power generation technologies – solar PV (utility and rooftop), onshore and offshore wind, and concentrating solar power (CSP)
- Data sets are expanded to include cost and performance data for two example technologies that are enabling the increased use of renewable energy i.e. battery storage for behind the meter applications, and hydrogen production using electrolysers, including where possible, historical data for the last 5 years.
- The geographical coverage of the data sets for the above technologies is expanded to ensure it includes data from as many EU member states and Mission Innovation member countries as possible.
WP 2 explored the use of patents and international technical standards. In ensured that:
- Datasets are expanded to include patents and international technical standards for two technologies: offshore wind and hydrogen electrolyser, including historical data for the last 10 years.
- The geographical coverage of the data sets for these technologies is expanded to ensure it includes data from EU member states and Mission Innovation member countries.
- The use of patents and international technical standards is evaluated to help understand innovation impacts.
WP 3 analysed clean energy innovation progress and trends based on data collected. In ensured that:
- A methodology is developed for policy makers to better measure and understand factors that impact technology progress, inform innovation-related decisions, and design RD&D activities and innovation policies.
- The methodology was piloted on offshore wind technology.
- Outputs were a case study ‘Tracking the impacts of innovation: Offshore wind as a case study’ available on the IRENA publication page and an online dashboard that provides a visual presentation of indicators, showcases trends and the geographical distribution of activities in offshore wind technology in the period between 2010-2019 with some exceptions of shorter and longer periods.
- Improved understanding of innovation progress and successes and provided insights on the impact of energy innovation inputs on measurable outputs.
- Stimulated discussions on clean energy innovation on the success factors in clean energy innovation, which contributes to maximize the impact of future investments in clean energy RD&D.
- Supported public-sector bodies in the development of energy RD&D policies, roadmaps and programmes that unlock clean energy potential through country-level and global insights.
- Provided quantitative evidence that can be used by stakeholders to enhance the decision-making processes of the public and private sector and inform clean energy innovation programming priorities. Doing so helps maximise the impact of public and private sector investments in clean energy RD&D – including national-level programmes and multi-national programmes such as Horizon Europe.
- Reinforced collaboration and knowledge exchange through international networks such as Mission Innovation and promoted the acceleration of clean energy innovation.
- Supported a strong, concerted effort from the EU to sustain technological and economic leading position in renewable technologies and catch up in areas where the EU lags behind.
- Provide robust, comprehensive and timely data on the outputs of energy innovation in the public domain to ensure stakeholders can make decisions on innovation policy.
- Created a dataset that will facilitate stakeholders to conduct their own analysis on drivers of success in innovation and inform the next stage of the European and global energy transition.
While the project has generated some major impacts (e.g. during Mission Innovation Insights Module, Glasgow Breakthrough Agenda – to allow countries to utilise the results from the TEIIF project and the Insights module to help shape their R&I policies and programmes), the impact of this project will continue, and its value will remain intact in the future due to the historical data it provides to policy-makers, researchers and academics that can be used to support new and original analysis. IRENA will continue with its analysis based on collected data for more tailor-made advice to target governments. Providing access to datasets and the insights from this project will also enable stakeholders to use data in future and develop targeted analysis to policy-makers and other data-driven processes, which will increase the impacts of the results.