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Reinforcement Learning for Computing Power Grid Network Operating Functions

  • Shivam SharmaEmail author
  • Pinki Gupta
  • Laxminarayan Das
Conference paper

Abstract

High voltage electric power grid physical nature learning is rarely a deterministic process rather it is a stochastic process in nature. Markov decision process and reinforcement learning algorithms are available to learn the quantitative and numerical estimation of the electric power generation, transmission, transformation, and distributing line physical measurement. Power grid managers use reinforcement learning process to regulate or control the parameters within a coded programming and computerized instrumentation. In this paper, we emphasize reinforcement algorithms to simplify medium level power grid problems.

Keywords

Reinforcement learning Power grid physical nature learning Electric power physical measurement Laplace transform and reinforcement learning 

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.United Health GroupBangaloreIndia
  2. 2.AxtriaGurgaonIndia
  3. 3.Department of Applied MathematicsDelhi Technological UniversityNew DelhiIndia

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