Resilience-Oriented Design of Distribution Systems

TLDR

Climatic hazards such as hurricanes and ice storms threaten power distribution systems, and challenges include modeling spatio‑temporal correlations of resilience‑oriented design decisions, capturing the full failure‑recovery‑cost process, and solving the resulting large‑scale mixed‑integer stochastic problem efficiently. The study proposes a resilience‑enhancing strategy that aims to minimize investment and expected loss‑of‑load, generator operation, and repair costs while improving resilience to climatic hazards. The authors formulate a two‑stage stochastic mixed‑integer linear program that models spatio‑temporal correlations of uncertainties via a hybrid stochastic process, and solve it with a dual decomposition algorithm with branch‑and‑bound, incorporating line hardening, backup DGs, and automatic switches. Case studies on the IEEE 123‑bus test feeder demonstrate that the proposed approach improves system resilience at minimal cost.

Abstract

Climatic hazards, such as hurricanes and ice storms, pose a top threat to power distribution systems. This paper proposes a resilience-enhancing strategy to make distribution systems more resilient to climatic hazards. The proposed strategy consists of three resilience-oriented design (ROD) measures, namely line hardening, installing backup distributed generators (DGs), and adding automatic switches. The main challenges of this problem are modeling the spatio-temporal correlation among ROD decisions and uncertainties, capturing the entire failure-recovery-cost process, and solving the resultant large-scale mixed-integer stochastic problem efficiently. To deal with these challenges, we propose a hybrid stochastic process with deterministic casual structure to model the spatio-temporal correlations of uncertainties. A new two-stage stochastic mixed-integer linear program is formulated to capture the impacts of ROD decisions and uncertainties on system's responses to climatic hazards. The objective is to minimize the ROD investment cost in the first stage and the expected costs of loss of load, DG operation, and damage repairs in the second stage. A dual decomposition algorithm with branch-and-bound is developed to solve the proposed model with binary variables in both stages. Case studies on the IEEE 123-bus test feeder show the proposed approach can improve the system resilience at minimum costs.