Resilience based Electric Sector Optimization in Response to Extreme Weather Conditions with Distributed Generation Systems

TL;DR

This paper proposes a stochastic optimization framework to enhance electric power system resilience against extreme weather events caused by climate change, utilizing distributed generation and scenario-based analysis.

Contribution

It introduces a novel framework that integrates climate data, socio-economic factors, and system interdependencies to optimize resilient electric sector design under uncertainty.

Findings

Optimized system designs improve resilience to extreme weather events.

Scenario-based simulations demonstrate robustness of the proposed approach.

Incorporating distributed generation enhances system adaptability.

Abstract

Extreme weather events stemming from climate change can cause significant damage and disruption to power systems. Failure to mitigate and adapt to climate change and its cascading effects can lead to short and long term issues. The profound costs of outage in power systems, integrated with the impacts on individual safety and security from loss of critical services, necessitate an urgent need to guarantee resilience in electric power systems. This article proposes a framework to optimize the electricity sector design to be more resilient to climate change and extreme weather events by using distributed generators. The proposed framework considers components dynamic behavior and interdependencies under an uncertain environment. The climate data and socio economic factors are used to generate demand and supply pattern scenarios. The generated scenarios are simulated and utilized in a stochastic optimization model to find the optimal resilience based system design.