REEE 2020


REEE 2020-virtual conference | Lisbon, Portugal | August 16-18, 2020 


REEE 2020 proceedings are published online. (Click) Indexed by Ei Compendex & Scopus already.

Due to the impact of COVID-19, interactive conferences involve a serious risk for this virus to spread among the participants. Meanwhile, in order to protect the local citizens, the government of many countries implemented a policy to restrict entry and exit. And the holding of large and medium-sized meetings is also prohibited by local government in many countries.REEE2020 has to be held as a virtual conference temporarily. We'd like to sincerely thanks for the supports from all the authors and committee members.

With your understaning and highly support, REEE2020 was held successfully online even we don't have the enough number of participants than before. Concerns relating to global warming, caused by green house gas (GHG) emissions from various sources, have raised general awareness among the governments and the public of the need to produce energy, in particular energy in the electrical form, from renewable energy sources that do not produce GHGs. Various aspects of advanced energy sources of the future will be the focus of the conference. We hope the virus situation will be totallu controlled soon and we can meet you face to face next year.


Conference Photo Screenshots



Best Presentation Winners


S1-PT007: The simulation analysis of composite parabolic concentrator to improve the performance of thermoelectric devices
Zeming He, Institute of Engineering Thermophysics, Chinese Academy of Sciences, Chinese


S2-PT009: Optimization of the electrical connection topology of a tidal farm network
Eyman FAKHRI, Caen University, France


S3-PT010: Evaluation and techno-economic analysis of packed bed scrubber for ammonia recovery from drying fumes produced during the thermal drying of sewage sludge
Ali Saud, LUT University, Finland


S4-PT014: Acid activation of bentonite clay for recycled automotive oil purification
Víctor H. Guerrero, Escuela Politécnica Nacional, Ecuador


S5-PT4002: Application and machine learning methods for dynamic load point controls of electric vehicles (xEVs)
Danting Cao, University of Applied Sciences Esslingen, Germany




@2024 The 7th International Conference on Renewable Energy and Environment Engineering