Globally Optimal AC Power System Upgrade Planning under Operational Policy Constraints

TL;DR

This paper presents a novel algorithm for power system upgrade planning that guarantees globally optimal solutions by combining heuristics, lower bounds, and operational constraints within a Branch-and-Bound framework.

Contribution

It introduces a deterministic method that efficiently finds globally optimal upgrade plans considering operational policies, improving over heuristic approaches.

Findings

Algorithm finds globally optimal solutions efficiently.

Method incorporates operational policy constraints effectively.

Provides bounds on suboptimality and guarantees optimality.

Abstract

In order to accommodate the increasing amounts of renewable generation in power distribution systems, system operators are facing the problem of how to upgrade transmission capacities. Since line and transformer upgrades are costly, optimization procedures are used to find the minimal number of up- grades required. The resulting design optimization formulations are generally mixed-integer non-convex problems. Traditional approaches to solving them are usually of a heuristic nature, yielding no bounds on suboptimality or even termination. In contrast, this work combines heuristics, lower-bounding pro- cedures and practical operational policy constraints. The resulting algorithm finds both suboptimal solutions quickly and the global solution determinis- tically by a Branch-and-Bound procedure augmented with lazy cuts.