Analytical Approach for Active Distribution Network Restoration Including Optimal Voltage Regulation

TL;DR

This paper introduces an analytical, optimization-based method for restoring active distribution networks that integrates reconfiguration, load management, and voltage regulation, enhancing grid reliability and efficiency.

Contribution

It presents a novel MISOCP formulation for distribution network restoration that reduces binary variables and incorporates practical self-healing actions and load dependencies.

Findings

Effective restoration plan minimizes deenergized nodes

Method reduces computational complexity compared to existing models

Validated on a real 83-node distribution network

Abstract

The ever increasing utilization of sensitive loads in the industrial, commercial and residential areas in distribution networks requires enhanced reliability and quality of supply. This can be achieved thanks to self healing features of smart grids that already include the control technologies necessary for the restoration strategy in case of a fault. In this paper, an analytical and global optimization model is proposed for the restoration problem. A novel mathematical formulation is presented for the reconfiguration problem reducing the number of required binary variables while covering more practical scenarios compared to the existing models. The considered self healing actions besides the network reconfiguration are the nodal load rejection, the tap setting modification of voltage regulation devices (incl. OLTCs, SVR, and CBs), and the active or reactive power dispatch of DGs. The voltage dependency of loads is also considered. Thus, the proposed optimization problem determines the most efficient restoration plan minimizing the number of deenergized nodes with the minimum number of self healing actions. The problem is formulated as a Mixed Integer Second Order Cone Programming (MISOCP) and solved using the Gurobi solver via the MATLAB interface YALMIP. A real 83 node distribution network is used to test and verify the presented methodology.