Intelligent priority based generation control for multi area system

Kumar, Prince; Kumar, Kunal; Bohre, Aashish Kumar; Adhikary, Nabanita

doi:10.1080/23080477.2023.2189628

Cited by 5 publications

(1 citation statement)

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“…The authors propose a control scheme that addresses the challenges posed by the system's dynamics and communication delays. 16 presents a detailed analysis of frequency response in a multi-area system using a PID-TLBO controller. TLBO (Teaching Learning Based Optimization) is employed as a metaheuristic technique for tuning the PID controller, enabling enhanced control performance and stability.…”

Section: Introductionmentioning

confidence: 99%

Intelligent planning of controllers for improved resilience in multi-area system involving nuclear power

Kumar,

Kumar Bohre

et al. 2023

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Increased innovation on finding new ways to generate energy from different sources to meet the growing demand of consumers has led to various challenges in controlling the power network when it faces different disruptions. To address these challenges, a new approach has been proposed in this research paper, which combines a controller with a soft computing technique called Particle Swarm Optimization (PSO). The study considers a power system with four units, where three different energy sources are utilized and distributed across two areas. Each area has two power sources, with one area having a combination of thermal and gas power plants, and the other area consisting of a nuclear power plant and a gas power plant. Transmitting power from the nuclear power plant is particularly complex due to its high sensitivity to disturbances. Therefore, an intelligent and efficient controller is needed to ensure robust control in this type of power network that includes nuclear power. The paper also conducts a thorough analysis of the harmful emissions associated with electricity generation from the different power plants considered. The goal is to reduce the carbon footprint associated with power generation. The proposed work and analysis in the paper are implemented using the MATLAB/SIMULINK environment.

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Section: Introductionmentioning

confidence: 99%