Journal of Computer Technology & Applications

Journal of Computer Technology & Applications Review Article

Intelligent Planning of Transmission Networks: Addressing Uncertainties Through Artificial Intelligence

  1. Saleem Malik Department of Computer Science, P.A. College of Engineering, Mangaluru
  2. Abdul Basith Department of Computer Science, P.A. College of Engineering, Mangaluru
  3. Mahammad Ramzeen Department of Computer Science, P.A. College of Engineering, Mangaluru
  4. Mahammad Razeen Department of Computer Science, P.A. College of Engineering, Mangaluru
  5. Mahammad Junaid Department of Computer Science, P.A. College of Engineering, Mangaluru

Abstract

Power grid planning is a critical aspect of power grid topology, traditionally relying on manual methods that are prone to various uncertainties. These uncertainties, both subjective (stemming from human judgment) and objective (resulting from data limitations), can significantly affect the reliability and efficiency of the planning process. This paper presents an artificial intelligence (AI) method aimed at improving the smart planning of transmission networks. By utilizing AI, the proposed method systematically analyzes and optimizes the factors contributing to uncertainties in traditional planning methods. The AI-based model processes and evaluates topology data comprehensively, leading to more accurate and reliable planning outcomes. Furthermore, continuous monitoring is integrated into the system to ensure that the planning process remains dynamic and responsive to real-time changes. The final planning results are generated with a high degree of precision, effectively minimizing the uncertainties that plagued earlier methods. Consequently, AI-driven techniques not only meet the stringent requirements of intelligent transmission grid planning but also facilitate the continuous evolution and optimization of transmission network planning. This approach is well-suited to support the ongoing development and complexity of modern power grids, ensuring more resilient and efficient grid topology.

Keywords

  • artificial intelligence
  • grid planning
  • grid topology
  • planning process
  • transmission network planning

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