Artificial Intelligence Techniques based Congestion Management in Restructured Power Systems: A Review

In the restructured power system, where uncertainties are common, managing congestion becomes a crucial aspect of power system operation and control. Congestion management aims to alleviate the power system transmission line congestion while meeting the system constraints at minimal cost. This research introduces a generation rescheduling method for congestion management in the electricity market, leveraging an innovative nutcracker optimizer algorithm. The nutcracker optimizer algorithm, inspired by nutcrackers’ food accumulation mechanisms, is a recently developed nature-inspired algorithm. The efficacy of this proposed approach is assessed across modified IEEE 30-bus, and IEEE 118-bus test systems, considering the system parameters. The effectiveness of the proposed congestion management with the nutcracker optimizer algorithm is analyzed by comparing its results with those generated by other recent optimization techniques. Results demonstrated that the nutcracker optimizer algorithm surpasses other comparative methods, requiring fewer fitness function evaluations, avoiding local optima, and displaying encouraging convergence traits. Implementing this approach can assist the system operators in swiftly addressing contingencies, ensuring secure and reliable power system operation within a deregulated environment.

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Artificial Intelligence Techniques based Congestion Management in Restructured Power Systems: A Review

Cited by 3 publications

References 29 publications

Impact of electrical power congestion and diverse transmission congestion issues in the electricity sector

Impact of electrical power congestion and diverse transmission congestion issues in the electricity sector

Load Flow Algorithm for Variable Economical Power Dispatch of Electricity Generation including Demand Response

A novel nature-inspired nutcracker optimizer algorithm for congestion control in power system transmission lines

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