Efficient and Risk-Aware Control of Electricity Distribution Grids

• Published in: IEEE systems journal Vol. 14; no. 3; pp. 3586 - 3597
• Main Authors: Liberati, Francesco, Di Giorgio, Alessandro, Giuseppi, Alessandro, Pietrabissa, Antonio, Delli Priscoli, Francesco
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computer simulation; Control systems; Distributed generation; Economic analysis; Economic models; Electric power distribution; Energy storage; Energy storage systems (ESSs); Indexes; model predictive control (MPC); network reconfiguration; Optimization; Predictive control; Real-time systems; Reconfiguration; Renewable energy sources; resilient control; Risk management; smart grids; Storage systems; Substations; Tap changers; Voltage control
• ISSN: 1932-8184; 1937-9234
• DOI: 10.1109/JSYST.2020.2965633

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.