Abstract:

With the increasing frequency and severity of extreme weather events, it is essential to evaluate the resilience of power grids during such events. This paper proposes a method for evaluating the resilience of distribution networks under extreme weather conditions based on three factors: network topology, component capacity, and operational strategies. The proposed method can provide insights into how different design and operational choices impact the resilience of power grids.

Introduction:

Extreme weather events such as hurricanes, tornadoes, floods, and wildfires have become increasingly frequent in recent years. These events can cause significant damage to power grids, leading to widespread power outages that can last for days or even weeks. To ensure the continuity of critical infrastructure and services during extreme weather events, it is essential to assess the resilience of power grids under such conditions.

Resilience refers to the ability of a system to withstand and recover from adverse events. In the context of power grids, resilience refers to their ability to maintain electricity supply during extreme weather events and quickly restore service after disruptions occur. Resilience depends on various factors such as network topology, component capacity, operational strategies, and external factors like environmental conditions.

In this paper, we propose a method for evaluating the resilience of distribution networks under extreme weather conditions. We focus on three main factors that influence grid resilience: network topology, component capacity, and operational strategies.

Methodology:

Our method involves four steps: (1) defining scenarios; (2) modeling network topology; (3) simulating component failures; and (4) analyzing results.

Step 1: Defining Scenarios

The first step in our methodology is to define scenarios that represent different types of extreme weather events that may affect a particular region or area. For example, we may consider scenarios such as hurricanes with high winds and heavy rain or snowstorms with heavy snowfall.

Step 2: Modeling Network Topology

The second step involves modeling the distribution network’s topology using graph theory. We represent the network as a graph, where nodes represent substations, transformers, and other components, and edges represent transmission lines and other connections between components.

Step 3: Simulating Component Failures

In this step, we simulate component failures that may occur during extreme weather events. We consider various types of component failures such as transformer failures due to overloading or damage caused by high winds or fallen trees on power lines.

Step 4: Analyzing Results

The final step involves analyzing the simulation results to assess the resilience of the distribution network under different scenarios. We evaluate resilience based on factors such as the number of customers affected, outage duration, restoration time, and cost of repairs.

Results:

Our method provides insights into how different design choices and operational strategies impact grid resilience under extreme weather conditions. For example, we can use our method to compare the resilience of networks with underground vs. overhead transmission lines or networks with distributed vs. centralized generation.

Conclusion:

The proposed method provides a systematic approach for evaluating the resilience of distribution networks under extreme weather conditions. Our approach considers multiple factors that influence grid resilience and can help decision-makers identify design and operational choices that improve grid resilience during extreme weather events. Further research could focus on incorporating external factors such as climate change projections into our methodology to improve its accuracy in predicting future extreme weather events’ impacts on power grids.