@ARTICLE{Liberati20203586,
author={Liberati, F. and Di Giorgio, A. and Giuseppi, A. and Pietrabissa, A. and Priscoli, F.D.},
title={Efficient and Risk-Aware Control of Electricity Distribution Grids},
journal={IEEE Systems Journal},
year={2020},
volume={14},
number={3},
pages={3586-3597},
doi={10.1109/JSYST.2020.2965633},
art_number={8966461},
abstract={This article presents an economic model predictive control (EMPC) algorithm for reducing losses and increasing the resilience of medium-voltage electricity distribution grids characterized by high penetration of renewable energy sources and possibly subject to natural or malicious adverse events. The proposed control system optimizes grid operations through network reconfiguration, control of distributed energy storage systems (ESSs), and on-load tap changers. The core of the EMPC algorithm is a nonconvex optimization problem integrating the ESSs dynamics, the topological and power technical constraints of the grid, and the modeling of the cascading effects of potential adverse events. An equivalent (i.e., having the same optimal solution) proxy of the nonconvex problem is proposed to make the solution more tractable. Simulations performed on a 16-bus test distribution network validate the proposed control strategy. © 2007-2012 IEEE.},
author_keywords={Energy storage systems (ESSs);  model predictive control (MPC);  network reconfiguration;  resilient control;  smart grids},
keywords={Data storage equipment;  Electric energy storage;  Electric utilities;  Model predictive control;  Renewable energy resources;  Voltage control, Control strategies;  Distributed energy storage systems;  Electricity distribution;  Network re-configuration;  Nonconvex optimization problem;  On- load tap changers;  Renewable energy source;  Technical constraints, Electric power transmission networks},
document_type={Article},
}

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