Modeling and seeker optimization based simulation for intelligent reactive power control of an isolated hybrid power system

Banerjee, Abhik; Mukherjee, V.; Ghoshal, Sakti Prasad

doi:10.1016/j.swevo.2013.05.003

Cited by 43 publications

(15 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The variation of the applied sinusoidal load demand may be expressed by (27) [26]

normalΔ P_{normalL} = 0.02 \sin ()(, 4.36 t) + 0.05 \sin ()(, 5.3 t) - 0.1 \sin ()(, 6 t)

The sinusoidal load demand presented in (27) is considered for this case and is applied in area 2. With the application of sinusoidal load demand disturbance to the load side in area 2 at t = 0 s, the transient responses of the different system configurations are depicted in Fig.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

Frequency stabilisation of a hybrid two‐area power system by a novel quasi‐oppositional harmony search algorithm

Mahto

Mukherjee

2015

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…The variation of the applied sinusoidal load demand may be expressed by (27) [26]

normalΔ P_{normalL} = 0.02 \sin ()(, 4.36 t) + 0.05 \sin ()(, 5.3 t) - 0.1 \sin ()(, 6 t)

Section: Simulation Results and Discussionmentioning

confidence: 99%

Frequency stabilisation of a hybrid two‐area power system by a novel quasi‐oppositional harmony search algorithm

Mahto

Mukherjee

2015

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…The proposed controller was used to maintain the required voltage at the load side and eliminating the grid harmonics. Banerjee et al [125] have developed the Seeker optimization algorithm (SOA) based controller to regulate the reactive power of an MG comprising of wind and diesel power generators. The authors have further extended their work and proposed an online reactive power compensation method for wind and diesel generator based islanded MG in [126].…”

Section: Modern Si-based Optimization Techniques In Power Qualitmentioning

confidence: 99%

Swarm Intelligence-Based Optimization Techniques for Dynamic Response and Power Quality Enhancement of AC Microgrids: A Comprehensive Review

et al. 2020

View full text Add to dashboard Cite

The increasing penetration of Microgrids (MGs) into existing power systems and ''plug and play'' capability of Distributed Generators (DGs) causes large overshoots and settling times along with various power quality issues such as voltage and frequency flickers, current harmonics and short current transients. In this context, over the past few years, considerable research has been undertaken to investigate and address the mentioned issues using different control schemes in conjunction with soft computational techniques. The recent trends and advancements in the field of Artificial Intelligence (AI) have led the development of Swarm Intelligence (SI) based optimized controllers for smooth Renewable Energy Sources (RES) penetration and optimal voltage, frequency, and power-sharing regulation. Moreover, the recent studies have proved that the SI-based controllers provide enhanced dynamic response, optimized power quality and improved the dynamic stability of the MG systems as compared to the conventional control methods. Their importance in modern AC MG architectures can be judged from the growing number of publications in the recent past. However, literature, pertaining to SI applications to AC MG, is scattered with no comprehensive review on this significant development. As such, this study provides an overview of 15 different SI optimization techniques as applied to AC MG controls from 43 research publications including a detailed review of one of the elementary and most widely used SI based metaheuristic optimization algorithms called Particle Swarm Optimization (PSO) algorithm. This comprehensive review provides a valuable one-stop source of knowledge for the researchers and experts working on SI controller's applications for AC MG dynamic response and power quality improvements.

show abstract

“…Among these three, ISE is considered as the objective function of the present optimization task [20]. These three performance measures are defined by (15)-(17), in order:…”

Section: Performance Measure and Objective Functionmentioning

confidence: 99%

Evolutionary optimization technique for comparative analysis of different classical controllers for an isolated wind–diesel hybrid power system

Mahto

Mukherjee

2016

Swarm and Evolutionary Computation

Self Cite

View full text Add to dashboard Cite

Modeling and seeker optimization based simulation for intelligent reactive power control of an isolated hybrid power system

Cited by 43 publications

References 37 publications

Frequency stabilisation of a hybrid two‐area power system by a novel quasi‐oppositional harmony search algorithm

Frequency stabilisation of a hybrid two‐area power system by a novel quasi‐oppositional harmony search algorithm

Swarm Intelligence-Based Optimization Techniques for Dynamic Response and Power Quality Enhancement of AC Microgrids: A Comprehensive Review

Evolutionary optimization technique for comparative analysis of different classical controllers for an isolated wind–diesel hybrid power system

Contact Info

Product

Resources

About