Optimal Risk Management of Electric Power Systems with CLOUD Simulation and Security Meter Algorithms

Mehmet Sahinoglu ()
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Mehmet Sahinoglu: Troy University

A chapter in Handbook of Smart Energy Systems, 2023, pp 761-815 from Springer

Abstract: Abstract This review chapter studies a discrete event simulator (DES), CLOURAM: CLOUD Risk Assessor and Manager that quantitatively estimates and manages risk with optimal mitigation targets within an Electric Power CLOUD computing framework. The 2-state (UP, DOWN) units are assumed to fail and recover with a Negative Exponential density for simplicity and as a result of goodness-of-fit studies. The ultimate goal is to manage risk and improve the operational quality of Power CLOUD by optimizing the number of servers for capacity addition, and optimizing the maintenance repair crew count. One also optimizes the generating unit repair rates and consumer load cycle by using Linear Programming (LP)-based optimization schemes with proper objective functions and constraints. Authentic Electric Power Systems are simulated with cost and benefit comparisons for optimality. As an alternative, Security Meter (SM) algorithm is applied to mitigate a nation’s overall risk studying the vulnerabilities, threats, and countermeasures of electric power networks with cost parameters. Various alternatives to electric power sector optimization are surveyed.

Keywords: DES; LOLP; Reliability; UP; DOWN; LP; Operational quality (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-97940-9_85

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DOI: 10.1007/978-3-030-97940-9_85

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