Comparison of performances of several FACTS devices using Cuckoo search algorithm optimized 2DOF controllers in multi-area AGC

Dash, Puja; Saikia, Lalit Chandra; Sinha, Nidul

doi:10.1016/j.ijepes.2014.10.015

Cited by 123 publications

(77 citation statements)

References 23 publications

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“…The total capacity of placed IPFC in the optimal location can be expressed by the multi-objective function as [21]: (12) where PQ is the capacity of each VSCs of IPFC. The eqn.…”

Section: Minimization Of Total Capacity Of Ipfcmentioning

confidence: 99%

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Optimal Location of IPFC for Improving Power System Performance Using Cuckoo Search Algorithm

S¹,

Chellaswamy²

2016

IOSR

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“…The total capacity of placed IPFC in the optimal location can be expressed by the multi-objective function as [21]: (12) where PQ is the capacity of each VSCs of IPFC. The eqn.…”

Section: Minimization Of Total Capacity Of Ipfcmentioning

confidence: 99%

“…The obligatory brood parasitism with levy flight is a unique behavior of CS algorithm [12]. Comparison of several FACT devices using CS algorithm for three unequal areas of thermal systems has been studied in [13].…”

Section: Introductionmentioning

confidence: 99%

Optimal Location of IPFC for Improving Power System Performance Using Cuckoo Search Algorithm

S¹,

Chellaswamy²

2016

IOSR

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“…Likewise, Dash et al used flower pollination algorithm for tuning PID controller for AGC control. In recent time, some other type of soft algorithm also playing very important role like cuckoo search is used to tune the parameters of PID and PI controller for AGC control . Shankar et al have used harmony search algorithm in deregulated power system considering nonlinearity like the dead band and GRC using energy storage system.…”

Section: Introductionmentioning

confidence: 99%

Fruit fly algorithm-based automatic generation control of multiarea interconnected power system with FACTS and AC/DC links in deregulated power environment

Shankar

Kumar

Raj

et al. 2018

Int Trans Electr Energ Syst

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Summary This paper focuses on automatic generation control (AGC) in deregulated environment for the multiarea interconnected power system. Each area consists of different kind of generating sources like thermal, hydro, and gas, each having different characteristics with physical constraint likes governor dead band and generation rate constraint. Loads are divided among different generator using the concept of economic load dispatch. The AC/DC links has been installed in all areas as well as unified power flow controller (UPFC) in tie lines to mitigate the effect of oscillation and to improve the system response. Thus, a more systematic and synchronized control of AGC with UPFC and AC/DC links has been proposed. Small signal stability of each area has been analyzed for finding out the oscillation states of the studied system. The proposed controller is optimized through Fruit Fly Algorithm, and its promising results reveal that the proposed controller is more efficient and effective in all different power transaction modes of restructured scenario.

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“…Firefly algorithm (FA) employed for LFC of multi-area interconnected power system [2,3]. Cuckoo search algorithm (CSA) was proposed for AGC of two area power system [4,5], while, Beta Wavelet Neural Network (BWNN) approach was conducted for LFC of interconnected power system [6]. Teaching-learning-based optimization (TLBO) algorithm has been implemented in AGC of multi-area power system [7,8].…”

Section: Introductionmentioning

confidence: 99%

Application of flower pollination algorithm in load frequency control of multi-area interconnected power system with nonlinearity

Jagatheesan¹,

Anand

Samanta

et al. 2016

Neural Comput & Applic

110

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This work presents an application of bio-inspired flower pollination algorithm (FPA) for tuning proportional-integral-derivative (PID) controller in load frequency control (LFC) of multi-area interconnected power system. The investigated power system comprises of three equal thermal power systems with appropriate PID controller. The controller gain [proportional gain (K p ), integral gain (K i ) and derivative gain (K d )] values are tuned by using the FPA algorithm with one percent step load perturbation in area 1 (1 % SLP). The integral square error (ISE) is considered the objective function for the FPA. The supremacy performance of proposed algorithm for optimized PID controller is proved by comparing the results with genetic algorithm (GA) and particle swarm optimization (PSO)-based PID controller under the same investigated power system. In addition, the controller robustness is studied by considering appropriate generate rate constraint with nonlinearity in all areas. The result cumulative performance comparisons established that FPA-PID controller exhibit better performance compared to performances of GA-PID and PSO-PID controller-based power system with and without nonlinearity effect.

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Comparison of performances of several FACTS devices using Cuckoo search algorithm optimized 2DOF controllers in multi-area AGC

Cited by 123 publications

References 23 publications

Optimal Location of IPFC for Improving Power System Performance Using Cuckoo Search Algorithm

Optimal Location of IPFC for Improving Power System Performance Using Cuckoo Search Algorithm

Fruit fly algorithm-based automatic generation control of multiarea interconnected power system with FACTS and AC/DC links in deregulated power environment

Application of flower pollination algorithm in load frequency control of multi-area interconnected power system with nonlinearity

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