Periodic Reporting for period 1 - REWAM (Next generation renewable energy portfolio asset management based on predictive analytics)
Reporting period: 2017-08-01 to 2018-01-31
The maturity of renewable generation technologies is a reality where new players such as investment funds and utilities are taking central stage as assets owners. Portfolio managers, handle hundreds of facilities with diverse technologies with thousands of generation equipment’s and several GW of installed power with the duality goal of maximize generation and the extension of life of the renewable asset. Since renewable energy plants generate large number of data quick and continuously, there is a great opportunity here to turn the renewable data into profit. The main barrier found in the market for this chance, relies on the fact that the time consumed for analysis is too long due to the large amount of information to be processed, and the results are obtained too late to act effectively. The next challenge that the sector is facing is that the relations between variables are not always simple. The process for discovering them is not only about managing large amount of information, but discovering complex interrelations between large number of variables to identify a degradation or loss of production, and consequently identify main possible cause to suggest an action plan.
Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far
In response, the REWAM team, has developed a strategy for, an early diagnosis, with enables conservative, improving or preventive actions to contain the advancement of the power output degradation & non optimal operation, thus increasing the revenues at managing large renewable generation portfolios. Interviews with Key Actors have confirmed interest from the field and have confirmed the need for demo and piloting validation.
Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)
The selection and validation of the algorithms will be performed via piloting phases with Key Actors (KA) and the validated algorithms will be integrated in a SaaS solution, based on Machine Learning and Artificial Intelligence. In order to provide and early payback investment and to ease the adoption of the SaaS solution an asset performance diagnosis report will be piloted together with KA (utilities, investments funds). Then it will be first launched to the market via limited period report service. After validation via KA, the service will be offered as a SaaS ICT solution as a standard decision support tool. In the best case scenario in four year projections, we expect to achieve an IRR of 20% and an NPV of 467.4 k€. In the long term, society will be benefits from electricity billing reduction thanks to the O&M competitiveness of renewable assets.