Power, Control, and Data Processing Systems

Power, Control, and Data Processing Systems

Optimal planning of Transmission line charging mode during black start of a hydroelectric unit

Document Type : Original Research

Authors
Mohammad Reza Esmaili 1
Ehsan Heydarian-Forushani 2
1 Deputy of Operation, Esfahan Regional Electric Company, Isfahan, Iran
2 Department of Electrical and computer engineering, Qom University of Technology, Qom, Iran
10.30511/pcdp.2025.2050366.1015
Abstract
After the occurrence of blackouts the most important subject is that how fast the electric service is restored. Power system restoration is an immensely complex issue and there should be a plan to be executed within the shortest time period. This plan has three main stages of black start, network reconfiguration and load restoration. In the black start stage, operators and experts may face with several problems; for instance, the unsuccessful connection of the long high voltage transmission line connected to the electrical source. In this situation, the generator may be tripped because of the unsuitable setting of its line charging mode or high absorbed reactive power. In order to solve this problem, the line charging process is defined as a nonlinear programming problem, and it is optimized by using MATLAB software in this paper. Therefore, the line charging mode of a hydro power plant is defined as an optimization problem. A nonlinear programming problem with considering the effect of transmission line parameters and installed shunt reactors in sending and receiving end buses is formulated. An iterative procedure is applied for solving the proposed problem. The optimized process is performed on a small part of a large grid which includes a 250 MW hydroelectric unit and a 400 KV transmission system. Simulations and field test results show the effectiveness of the optimal planning.
Keywords
Power System restoration
Black start
Line charging mode
nonlinear programming

Subjects

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Power, Control, and Data Processing Systems
Volume 2, Issue 1
Winter 2025
Pages 30-34

  • Receive Date 10 January 2025
  • Revise Date 27 January 2025
  • Accept Date 31 January 2025
  • First Publish Date 31 January 2025
  • Publish Date 01 March 2025