Flexibility Management For Enhanced Distribution Grid Control And Operation - The Case of FEVER Project

The constant increase of renewable energy sources, microgrids, non-linear loads and electronic devices imposed a new set of challenges for distribution system operators to maintain operational stability. To address these challenges, the FEVER project was conceived to propose solutions based on energy flexibility. In this paper, the authors introduce three applications developed within the project. First, the energy forecaster uses smart-meter data and machine learning to provide demand and generation forecast. The voltage compensation application runs time-series power flows to detect voltage deviations, also performing a sensitivity analysis to assess the impact of flexibility of available assets to voltage correction. Lastly, the power quality service uses machine learning to forecast the state of the grid in terms of harmonics and phase unbalances, with the purpose of estimate a power capacity reserve of flexible assets.