In this paper a control strategy based on predictive control ideas is proposed for reconfiguring on-line the on-load tap changer (OLTC) voltage set-point in electrical medium voltage (MV) power grids in the presence of distributed generation (DG). The idea is that an active management of the set-point can beeffective for maintaining relevant system variables within prescribed operative constraints in response to unexpected adverse conditions, e.g. changing loads or generation failures. The voltage set-point reconfiguration problem is formulated as a constrained optimization problem by imposing that the voltages at certain nodes have, compatibly with all prescribed constraints and changed conditions, minimal deviations from their nominal values. Simulation results show that the proposed approach ensures, under certain conditions, feasible evolutions to the overall network whenever critical events occur.

Voltage regulation in distribution networks in the presence of distributed generation: A voltage set-point reconfiguration approach

CASAVOLA, Alessandro;FRANZE', Giuseppe;MENNITI, Daniele;SORRENTINO, Nicola
2011-01-01

Abstract

In this paper a control strategy based on predictive control ideas is proposed for reconfiguring on-line the on-load tap changer (OLTC) voltage set-point in electrical medium voltage (MV) power grids in the presence of distributed generation (DG). The idea is that an active management of the set-point can beeffective for maintaining relevant system variables within prescribed operative constraints in response to unexpected adverse conditions, e.g. changing loads or generation failures. The voltage set-point reconfiguration problem is formulated as a constrained optimization problem by imposing that the voltages at certain nodes have, compatibly with all prescribed constraints and changed conditions, minimal deviations from their nominal values. Simulation results show that the proposed approach ensures, under certain conditions, feasible evolutions to the overall network whenever critical events occur.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/144853
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