Optimal Allocation of Solar-PV and STATCOM Using PSO with Multi-Objective Approach to Improve the Overall System Performance

Kumar, Prince; Bohre, Aashish Kumar

doi:10.1007/978-981-16-6970-5_49

Cited by 7 publications

(1 citation statement)

References 14 publications

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“…Hybrid controllers combine different control strategies to achieve improved performance in regulating the frequency of the power system. Authors in 5 , 6 discuss the design and optimization of fitness or cost functions. These functions play a crucial role in determining the optimal control strategies and parameters for power system operation.…”

Section: Introductionmentioning

confidence: 99%

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

Kumar,

Kumar Bohre

et al. 2023

Sci Rep

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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%