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The United States and Canada had the worst power outage in North American history on August 14, 2003. A large power outage struck sections of the northeastern United States and eastern Canada, affecting around 50 million people. The outage was caused by a breakdown of monitoring and diagnostic systems of the FirstEnergy company, as well as communication issues between their operators, as well as utility operators lack of knowledge and planning of systems (Johansen & Tien, 2018).
Multilayered obligations necessary for the proper running of such a complicated system have not been fulfilled. On a personal level, if the primary and backup computer systems fail, operators must manually monitor their networks and, if required, activate pre-planned contingencies. Because the IT team was aware of the system failures but was unable to alert the monitoring centers promptly, this was not done (Johansen & Tien, 2018). After obtaining conflicting data, the operators realized there was an issue (Johansen & Tien, 2018). Obligations were also broken at the agency level since the controlling agencies and corporations had little awareness of what was occurring at the macro level. This was reflected in the absence of sufficient operator training to work in major interference scenarios. Furthermore, FirstEnergys studies and simulations of long-term operational planning undertaken in 2002 and 2003 were insufficient (Johansen & Tien, 2018). Due to the fact that it is the mixture of the unfulfilled responsibilities, the blame perhaps can be put on both agential and individual levels actors.
Following the power outage, FirstEnergy took a number of actions to cope with the repercussions. They replaced the software system with a new one that had better alarm features and diagnostic modules that were faster (Johansen & Tien, 2018). It also updated the functionality to assist operators in swiftly identifying faults (Johansen & Tien, 2018). The development of the clearinghouse system and training programs for operators and other crucial people became perhaps the most important in handling the outcomes.
References
Johansen, C., & Tien, I. (2018). Probabilistic multi-scale modeling of interdependencies between critical infrastructure systems for resilience. Sustainable and Resilient Infrastructure, 3(1), 1-15.
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