Using simulated predictive load curves to improve DSO’s network development planning methods integrating smart grids functionalities

Aurélie Ferrage (1) , Maxence Bocquel (1) , Nicolas Kong (1) , Thibaut Barbier (2) , Robin Girard (2)

1 ERDF
2 PERSEE - Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques

The actors in the electrical system face significant challenges related to new uses (electric vehicles, net-zero energy building...) and new EU energy objectives. The Distribution System Operator (DSO) must adapt network planning methods to support the energy transition. Therefore ERDF and Mines ParisTech have developed a new Bottom-Up method to forecast electricity consumption needs at the local level. This approach named MOSAIC has been successfully tested through field experiments and developed in a collaborative partnership with the Administration of Urban Community of Lyon. It opens interesting perspectives for the development of credible estimations of local energy planning schemes using smart grid solutions. The paper describes the model principles and presents the results and comparison with measurements

Mots clés: smart grids; Distribution System Operator

Domaines: Sciences de l'ingénieur [physics]; Energétique

Aurélie Ferrage, Maxence Bocquel, Nicolas Kong, Thibaut Barbier, Robin Girard. Using simulated predictive load curves to improve DSO’s network development planning methods integrating smart grids functionalities. 23rd International Conference on Electricity Distribution - CIRED 2015, Jun 2015, Lyon, France. ⟨hal-01174679⟩