What is the challenge that is being addressed?

Energy efficiency projects are often fragmented, with high transaction costs, while with no evidence-based platform that would allow investors and financial institutions to assess the risk-, the financial performance of the investments, as well as the impact on energy efficiency. The capability offered by emerging AI analytics to integrate cross-domain financial and energy consumption is the key for building the necessary market confidence in energy efficiency projects and making them an attractive investment asset class. The use of historical data pooled from major market segments can encourage more energy efficiency investments and de-risk investments.

What is the AI solution the project plans to implement?

This pilot will demonstrate I-NERGY framework through cross-domain integration of a variety of heterogeneous historical and live data on financial performance, underlying energy efficiency impact of the investments, through historical extensive smart meters data integration. The aim is to collect and process data from smart meters, and apply machine learning algorithms, through ML algorithms, in order to better predict energy consumption and calculate and monitor the energy savings achieved. As a result, Energy Performance Contracting (EPC) and other energy investments will be more reliable, cost-effective, and of better quality.

The pilot will reduce the uncertainty linked to energy efficiency investments, which can be attributed to the lack of relevant skills and ability to assess investments. It will strengthen debt and equity financing of energy efficiency projects. AI models will provide investors / financiers and project developers the opportunity to: evaluate quickly and easily key performance indicators for projects (analysis and assessment techniques for projects and companies, benchmark tools, financial performance indicators for investors, special indicators ‘Green barometer’, written analysis); Explore past and future projects (project history, synopsis, projects/companies more attractive to investors); Make a profound risk measurement and evaluation (implement key indicators, such as debt service coverage ratio, integrate a cross-check for legal requirements of environmental laws and regulations).

Who will help implement this solution?

This pilot is implemented within the framework of the “I-NΕRGΥ: Artificial Intelligence for Next Generation Energy” Project. The I-NERGY Project has received funding from the European Union's Horizon 2020 Research and Innovation programme under grant agreement No. 101016508.

The responsible partner for this Use Case is REA (https://rea.riga.lv/en).

Learn more about I-NERGY pilots here: https://i-nergy.eu/pilots