TillÀmpad AI-forskning en viktig pusselbit för att klara omstÀllning till förnybar el
De punkter som Daniel Badman frÄn Svensk Vindenergi propagerar för Àr rimliga men det behövs en till punkt för att stÀlla om energisystemet, att optimera energianvÀndningen med hjÀlp av AI. Det skriver Jonas Forsman som bland annat Àr AI-expert pÄ CGI.
Hela artikeln pÄ Aktuell HÄllbarhet
Publications in Peer-Reviewed Conferences
| Integration of AI, IoT and Edge-Computing for Smart Microgrid Energy Management, A. Nammouchi, P. Aupke, A Kassler, A. Theocharis, V. Raffa, M. Di Felice, In: IEEE EEEIC, Bari, September 2021. Quantifying Uncertainty for Predicting Renewable Energy Time Series Data using Machine Learning, Phil Aupke, Andreas Kassler and Andreas Theocharis, In: 7th International conference on Time Series and Forecasting, Gran Canaria, Spain, 19â21 July 2021. In: Eng. Proc. 2021, 5(1), 50; https://doi.org/10.3390/engproc2021005050. |
Open Datasets
Glava Data-Set
This repository contains a demo version of weather and PV-Station information from the Glava Energy Center (https://www.glavaenergycenter.se/). This data-set contains information of four weather features for two months together with the energy produced by the MicroGrid.
Student Thesis
| Phil Aupke, Uncertainty in Renewable Energy Timeseries Prediction using Neural Networks, MSc thesis, HT 2020, together with Hochschule OsnabrĂŒck and Glava Energy Center. Viviana Raffa, Edge/Cloud Virtualization Techniques and Resource Allocation Algorithms for IoT-based Smart Energy Applications, MSc, thesis, HT 2020, together with Unievrsity of Bologna and Glava Energy Center |