Data Analysis Applications in Optimizing the Smart Grid System

Nikolay Belyaev (), Nikolay Korovkin, Vladimir Chudny () and Olga Sokolova ()
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Nikolay Belyaev: Federal State Budgetary Organization “Russian Energy Agency” (REA) by the Ministry of Energy of the Russian Federation
Nikolay Korovkin: Peter the Great St. Petersburg Polytechnic University
Vladimir Chudny: Peter the Great St. Petersburg Polytechnic University
Olga Sokolova: Peter the Great St. Petersburg Polytechnic University

A chapter in Handbook of Smart Energy Systems, 2023, pp 1345-1376 from Springer

Abstract: Abstract The growth of population and economic development shift the energy consumption toward a higher share of electric power. New technologies and associated process development result in higher cost of electricity undersupply. Moreover, the society expects an increased reliability of power supply and a reduced restoration time. Overall, risk management process consists of continuously repeated four phases named as preparedness, response, recovery, and prevention. A novel apparatus for data analysis toward optimal power grid operation is introduced in this chapter. It allows direct representation of the studied functions using fractional-polynomial dependences. The introduced dependences establish a direct relationship between any power system state parameter and FACTS device parameters. Its efficient implementation affects all four phases of risk management process. The real case of data analysis application for power grid optimization is performed on St. Petersburg and Leningradskaya region power grid, Russia.

Keywords: Critical infrastructure; Clustering; Control; Natural hazard; Multi-criteria decision analysis; Optimization; Power system; Reliability; Stability (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_44

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DOI: 10.1007/978-3-030-97940-9_44

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