Islanded Microgrid Restoration Studies with Graph-Based Analysis

TL;DR

This paper introduces a graph-based optimization method for restoring islanded microgrids after blackouts, integrating demand response, distributed generation constraints, and a MILP model for efficient restoration planning.

Contribution

It presents a novel graph analysis approach to determine minimal restoration steps and formulates a comprehensive MILP model incorporating various operational constraints.

Findings

Graph analysis reduces restoration steps

Demand response improves restoration efficiency

MILP model effectively coordinates microgrid resources

Abstract

The need to restore and keep the grid running or fast restoration during emergencies such as extreme weather conditions is quite apparent given the reliance of other infrastructure on electricity. One promising approach to electricity restoration is the use of locally available energy resources to restore the system to form isolated microgrids. In this paper, we present a black start restoration method that forms islanded microgrids after a blackout. The master DGs in the formed microgrids are coordinated to work together through droop control. Several constraints, including incentive-based demand response (DR) with direct load control (DLC) and distributed generator (DG) operation constraints, were formulated and linearized to realize a mixed-integer linear programming (MILP) restoration model. To improve compactness and to ensure that the model is neither under-sized nor over-sized, a pre-processing graph analysis approach was introduced which helps to characterize the least number of restoration steps needed to optimally restore the microgrid. Studies were performed on a modified IEEE 123 node test feeder to evaluate the effects of demand response, non-dispatchable DGs, and choice of restoration steps on the quality of the restoration solution.