Particle Swarm Optimization Technique Tuned Fuzzy Based PI Controller of Unified Power Quality Conditioner

Arulkumar, S.; Madhavasarma, P.

doi:10.1166/jctn.2017.6647

Cited by 3 publications

(2 citation statements)

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“…In [126], the PSO along with fuzzy based PI control are used to control the solar PV-UPQC. The virus colony search algorithm [127] and flower pollination optimization algorithm [128] are implemented to determine the optimum value of the PI-controller gains to mitigate voltage sag, THD, and improve the power of the hybrid system using the UPQC.…”

Section: P-qmentioning

confidence: 99%

Recent Trends in Power Quality Improvement: Review of the Unified Power Quality Conditioner

Gade

Agrawal

Munje³

2021

ECTI-EEC

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The electrical power sector is currently focusing on power quality (PQ) issues and their mitigation. Industrial automation and the use of power electronic converters for the integration of distributed generation create various PQ problems. This necessitates PQ enhancement, which in turn helps to improve the life span of the equipment as well as the reliability of supply for feeding critical loads within the system. This paper presents a comprehensive review of the Unified Power Quality Conditioner (UPQC) and its widespread application in the distribution system. The UPQC belongs to the family of active power filters. It contributes to the alleviation of voltage and current-related PQ issues along with power factor correction and the integration of renewable energy systems in the distribution network. This paper discusses various topologies, compensation methods, control theories, and the technological developments in recent years. More than 160 research papers have summarized the features of UPQC for further applications. Based on the outcomes of the investigation, the future direction of the UPQC is discussed. This paper is expected to play a major role in guiding research scholars in the application of the UPQC.

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Section: P-qmentioning

confidence: 99%

Recent Trends in Power Quality Improvement: Review of the Unified Power Quality Conditioner

Gade

Agrawal

Munje³

2021

ECTI-EEC

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“…This case applies to fuzzy partitioning. 8 1965, Zadeh finded a new method-Rough set. Rough sets describe the existence of “ambiguous” data objects through membership functions.…”

Section: Introductionmentioning

confidence: 99%

Optimal allocation of higher education resources based on fuzzy particle swarm optimization

Cui

2021

International Journal of Electrical Engineering & Education

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The development concept of higher education will have a direct impact on the development direction of higher education, because the concept usually reflects people's understanding of the law of higher education, and the current education concept restricts the scale, quality, structure and efficiency of higher education to a certain extent. Throughout the evolution of the world's higher education development concept, it has generally experienced the overall coordination of the economic growth, the internal and external laws, and the people-centered sustainable development. This paper hopes to provide effective help by joint intelligent algorithms. In this paper, the particle swarm optimization algorithm in intelligent optimization algorithm and the FCM algorithm in cluster analysis are studied in depth, and the two are merged together to propose a fuzzy clustering algorithm based on improved particle swarm optimization algorithm. The main research contents of this thesis include: Firstly, the PSO algorithm is improved, and the random search step levy flights and PSO algorithm are repeatedly called by the iterative mode by introducing the eagle strategy. After improvement, the ESPSO algorithm can achieve a balance between global search and local development, and make the particles have more satisfactory search ability and convergence effect. Then the improved PSO algorithm is integrated into the FCM algorithm to solve the above problems of the FCM clustering algorithm and improve the clustering effect. The experimental results show that the improved espso algorithm and FCM algorithm are suitable for actual data. The simulation results show that the algorithm has better clustering effect than the traditional clustering algorithm.

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Smart teaching mode based on particle swarm image recognition and human-computer interaction deep learning

Long

Zhao

2020

IFS

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The smart teaching mode overcomes the shortcomings of traditional teaching online and offline, but there are certain deficiencies in the real-time feature extraction of teachers and students. In view of this, this study uses the particle swarm image recognition and deep learning technology to process the intelligent classroom video teaching image and extracts the classroom task features in real time and sends them to the teacher. In order to overcome the shortcomings of the premature convergence of the standard particle swarm optimization algorithm, an improved strategy for multiple particle swarm optimization algorithms is proposed. In order to improve the premature problem in the search performance algorithm of PSO algorithm, this paper combines the algorithm with the useful attributes of other algorithms to improve the particle diversity in the algorithm, enhance the global search ability of the particle, and achieve effective feature extraction. The research indicates that the method proposed in this paper has certain practical effects and can provide theoretical reference for subsequent related research.

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Particle Swarm Optimization Technique Tuned Fuzzy Based PI Controller of Unified Power Quality Conditioner

Cited by 3 publications

References 0 publications

Recent Trends in Power Quality Improvement: Review of the Unified Power Quality Conditioner

Recent Trends in Power Quality Improvement: Review of the Unified Power Quality Conditioner

Optimal allocation of higher education resources based on fuzzy particle swarm optimization

Smart teaching mode based on particle swarm image recognition and human-computer interaction deep learning

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