Restoration model for unbalanced distribution networks considering renewable sources uncertainties

Abstract

Extreme events cause blackouts, resulting in the distribution network being unable to obtain power from the upstream transmission system. In this situation, local distributed resources can be fully utilized to improve system resilience. A distribution service restoration model is proposed in this paper, where three-phase unbalance condition and renewable sources uncertainty have been considered. The network reconfiguration strategy based on traditional tie switch operation is adopted to isolate faults. To cope with uncertainty, the chance-constrained method is introduced to enable renewable sources to participate in restoration, improving load recovery level. The proposed distribution service restoration model is essentially a mixed-integer nonlinear programming problem (MINLP) with probability constraints. To this end, linearization method is introduced to convert original MINLP into a deterministic mixed-integer linear programming problem. Simulation tests based on IEEE 33-bus network is carried out to demonstrate the feasibility of proposed distribution service restoration model.

Keywords

• Service restoration
• Distribution network
• Three-phase unbalanced
• Uncertainties
• Mixed-integer linear programming