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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
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ISO Certification: 9001:2015
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License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 05

Published on: May 2026

INTELLIGENT HYBRID OPTIMIZATION FRAMEWORK FOR POWER FLOW SCHEDULING AND GRID CONGESTION MANAGEMENT

Mukul Kumar Dhariwal Sharad Kumar Ashutosh Singh Sushil Kumar Jha

School of Engineering & Technology,  Shri Venkateshwara University,  Gajraula , U.P. India
DOI:https://doi.org/10.55041/ijcope.v2i5.787

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Abstract

Renewable energy sources are becoming integrated into traditional electrical infrastructures at an ever-increasing rate. Smart grids are also expected to be very different than existing power systems due to the continuing introduction of electric vehicles, distributed generating systems, communication technologies, and other developments. The integration of these technologies has greatly increased the complexity and interconnections between the various traditional electrical networks; therefore, the need for the development of new methods to control and manage these increasingly complicated interconnections, especially in relation to power flows and their associated congested conditions, will become even more critical. Congestion control and power flow management on the current electric network is relatively inefficient and suffers from a number of issues related to computational complexity and time delays in performance during dynamic operation (e.g., real-time). The purpose of this article is to describe a Hybrid Optimization Framework for Power Flow Control and Congestion Management in Smart Grids that integrates intelligent optimization algorithms, real-time monitoring systems, and adaptive control methods to assist in their optimum operation. A Hybrid Optimization Framework that integrates several of the different optimization methodologies to provide an optimum power dispatch for the equipment used within an interconnected electrical grid, reduce power transmission congestion, minimize power losses, and improve voltage stability within interconnected grids is proposed. This framework will enable the continuous monitoring of network conditions, load demand fluctuations, and transmission line utilization via intelligent control modules to provide for real-time decision making and adaptive (intelligent) mitigation of transmission network congestion.

Keywords—Smart Grids, Power Flow Control, Congestion Management, Hybrid Optimization, Renewable Energy Integration, Distributed Energy Resources, Voltage Stability, Intelligent Energy Management, Power System Optimization, Transmission Network Efficiency.

How to Cite this Paper

Dhariwal, M. K., Kumar, S., Singh, A. & Jha, S. K. (2026). Intelligent Hybrid Optimization Framework for Power Flow Scheduling and Grid Congestion Management. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05). https://doi.org/10.55041/ijcope.v2i5.787

Dhariwal, Mukul, et al.. "Intelligent Hybrid Optimization Framework for Power Flow Scheduling and Grid Congestion Management." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i5.787.

Dhariwal, Mukul,Sharad Kumar,Ashutosh Singh, and Sushil Jha. "Intelligent Hybrid Optimization Framework for Power Flow Scheduling and Grid Congestion Management." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i5.787.

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References


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  • •All submissions are screened under plagiarism detection.
  • •Review follows editorial policy.
  • •Authors retain copyright.
  • •Peer Review Type: Double-Blind Peer Review
  • •Published on: May 27 2026
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