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Data Analysis Applications in Optimizing the Smart Grid System

In: Handbook of Smart Energy Systems

Author

Listed:
  • 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)

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.

Suggested Citation

  • Nikolay Belyaev & Nikolay Korovkin & Vladimir Chudny & Olga Sokolova, 2023. "Data Analysis Applications in Optimizing the Smart Grid System," Springer Books, in: Michel Fathi & Enrico Zio & Panos M. Pardalos (ed.), Handbook of Smart Energy Systems, pages 1345-1376, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-97940-9_44
    DOI: 10.1007/978-3-030-97940-9_44
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