2020 journal article

Prevention and Mitigation of Catastrophic Failures in Demand-Supply Interdependent Networks

IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 7(3), 1710–1723.

author keywords: Power system faults; Power system protection; Robustness; Stress; Load modeling; Adaptation models; Resource management; Interdependent networks; demand-supply networks; robustness; resource and load fluctuations; cascading failures
TL;DR: A generic system model for a special category of interdependent networks, demand-supply networks, in which the demand and the supply nodes are associated with heterogeneous loads and resources, which sheds a light on a unique cascading failure mechanism induced by resource/load fluctuations. (via Semantic Scholar)
Source: Web Of Science
Added: September 21, 2020

We propose a generic system model for a special category of interdependent networks, demand-supply networks, in which the demand and the supply nodes are associated with heterogeneous loads and resources, respectively. Our model sheds a light on a unique cascading failure mechanism induced by resource/load fluctuations, which in turn opens the door to conducting stress analysis on interdependent networks. Compared to the existing literature mainly concerned with the node connectivity, we focus on developing effective resource allocation methods to prevent these cascading failures from happening and to mitigate/confine them upon occurrence in the network. To prevent cascading failures, we identify some dangerous stress mechanisms, based on which we quantify the robustness of the network in terms of the resource configuration scheme. Afterward, we identify the optimal resource configuration under two resource/load fluctuations scenarios: uniform and proportional fluctuations. We further investigate the optimal resource configuration problem considering heterogeneous resource sharing costs among the nodes. To mitigate/confine ongoing cascading failures, we propose two network adaptations mechanisms: intentional failure and resource re-adjustment, based on which we propose an algorithm to mitigate an ongoing cascading failure while reinforcing the surviving network with a high robustness to avoid further failures.