Location and capacity allocation for emergency contact points in large-scale power outages

作     者：Truden, Christian Wankmueller, Christian Zehetner, Dominik Gansterer, Margaretha 

作者机构：Univ Klagenfurt Dept Operat Energy & Environm Management Univ Str 65-67 A-9020 Klagenfurt Austria 

出 版 物：《CENTRAL EUROPEAN JOURNAL OF OPERATIONS RESEARCH》 (Cent. Eur. J. Oper. Res.)

年 卷 期：2025年第33卷第1期

页      面：241-276页

核心收录：

学科分类：02[经济学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 

基　　金：University of Klagenfurt 

主　　题：Large-scale power outage Blackout Facility location Resource allocation Demand estimation Integer linear programming 

摘      要：Nowadays, industry and individuals alike are highly dependent on a reliable power supply. A large-scale power outage, commonly known as a blackout is caused by natural disasters, cyber attacks, technical failure, or human errors, and can lead to a variety of severe consequences. The far-reaching dynamics of blackouts can even result in the collapse of critical public service infrastructure reliant on electricity (e.g., communication, water supply, medical services, public safety). Particularly, the loss of information and communication infrastructure essential to reporting medical emergencies, and the collapse of the drinking water supply are two critical stressors for the population to cope with. One attempt to tackle this situation is to install temporary emergency contact points (ECPs) into existing infrastructure. These can be approached by the population to communicate with medical personnel and to receive drinking water. Different types of professional personnel, which is a limited resource, are required to run such ECPs. Our study introduces this tactical decision problem. We formulate it as an integer linear program for the optimal spatial allocation of ECPs, such that multiple types of human resources that are required for operating such locations can be efficiently assigned. A comprehensive numerical study, based on data of the City of Vienna, demonstrates how to reduce the walking distance of inhabitants while increasing the efficiency of resource allocation. Matrix pruning based on an enforced limit of the walking distances together with a decomposition approach is utilized to solve the considered instances.