Symbiotic organism search algorithm applied to load frequency control of multi-area power system

Guha, Dipayan; Roy, Provas Kumar; Banerjee, Subrata

doi:10.1007/s12667-017-0232-1

Cited by 96 publications

(60 citation statements)

References 41 publications

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“…The responses of ∆ F 1 /∆ F 2 /∆Ptie 12 /∆P g1 /∆P g2 at area 1 SLP of 1% are given in Figure A to F. The responses of FPIDF‐(1 + PI) with CES/CES‐RFB, FPIDF with/without CES, and some other existing controllers like FA‐optimised PI/PID, SOS/ABC‐optimised PID, and SMO‐optimised FPID are presented in Figure A to F and Table . The inspection of the results shown in Figure A to F/Table demonstrates that FPIDF‐(1 + PI) with CES as well as with CES‐RFB exhibits superior performance in respect to other methods.…”

Section: Two‐area Reheat Thermal Systemmentioning

confidence: 99%

“…[4][5][6]8 During the last decades, multiple researches and novel approaches have been incorporated in the literature for multiarea traditional/restructured AGC PS with/without DSTS/WTS. 1,[4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] Some control strategies are stochastic fractal search (SFS)-optimised integral minus PDF (proportional derivative with filter) (I-PDF), 1 sine cosine algorithm (SCA)-optimised PI, 4 whale optimisation algorithm (WOA)-optimised integral derivative with filter-fractional order PD (IDN-FOPD), 5 SCA-optimised cascade FOPI-FOPD, 6 biogeography-based optimisation (BBO)-optimised I/PI/PIDF, 7 WOA-optimised cascade PIDN-FOID, 8 nondominated sorting genetic algorithm-II (NSGA-II)-optimised PI/PIDF, 9 hybrid bacterial foraging optimisation algorithm-particle swarm optimisation (hBFOA-PSO)-optimised PI, 10 craziness-based particle swarm optimisation (CRAZYPSO)-optimised PI, 11 differential evolution (DE)-optimised PI/PID, 12,13 oppositional krill herd (OKH)-optimised PID, 14 disrupted oppositiongravitation search algorithm (DOGSA)-optimised PID, 15 teaching-learning-based optimisation (TLBO) algorithm-optimised two-degree freedom PID (2DOFPID), 16 artificial-bee colony (ABC)-optimised PI/PID, 17 firefly algorithm (FA)-optimised PI/PID, 18,19 symbiotic-organism-search (SOS)-optimised PID, 20 ICA-optimised PID, 21 and hybridised SFS-local unimodal sampling (hSFS-LUS) optimised PDF-(1 ...…”

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confidence: 99%

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Effect of energy storage systems on automatic generation control of interconnected traditional and restructured energy systems

Arya¹

2019

Int J Energy Res

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Summary During major disturbances in electric power system (PS) penetrated with renewable energy sources, primary and supplementary automatic generation control (AGC) strategies usually show inefficiency in mitigating the frequency and power oscillations because of sluggish control action. The frequency and power deviations should be controlled to retain the generation‐demand balance, which reinforce the quality and stability of overall PS. The fast‐acting energy storage systems (ESSs) having very small time constants like capacitive energy storage (CES) and redox flow battery (RFB) are utilised in this study to improve these dynamic responses. To conduct the analysis, initially, a two‐area nonreheat thermal PS with extra generations from wind turbine system (WTS) and dish‐stirling solar thermal system (DSTS) is explored extensively, and then to validate the efficacy of the method, the approach is tested on two‐area nonreheat thermal system having governor deadband (GDB) nonlinearity, reheat thermal, and restructured multisource thermal gas systems. An imperialist competition algorithm (ICA) optimised fuzzy PID‐filter‐(1 + PI) controller named as FPIDF‐(1 + PI) is utilised as supplementary controller, and its performance with CES/CES‐RFB is compared with ICA‐optimised FPIDF with/without CES and existing optimal PI/PID/PIDF/FPID controller without CES. Investigation of dynamic responses for sudden variation in power demand unveils the superiority of the control approach compared with others regarding settling time, peak undershoot, and performance index. Analysing the impact of ESSs on the responses divulges that the amalgamation of CES‐RFB in PS imparts better system dynamics. The robustness analysis suggests that ICA‐optimised controller with ESSs performs excellently and robustly for ±25% variation in PS parameters, random load disturbances, and nonlinearities.

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Section: Two‐area Reheat Thermal Systemmentioning

confidence: 99%

mentioning

confidence: 99%

Effect of energy storage systems on automatic generation control of interconnected traditional and restructured energy systems

Arya¹

2019

Int J Energy Res

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“…Abd-Alazim et al have used firefly algorithm based PI controller for LFC of a system including PV grid [4]. Guha et al have used symbiotic organism search based PID controller for the LFC of a two area thermal reheat system [5]. Mostly researchers have focussed on single, two or three area systems having conventional or non-conventional generation sources to study the LFC problem in different environments [6] [7] [8][9] [10].…”

Section: Introductionmentioning

confidence: 99%

Firefly Optimization Based Control Strategies for Combined Load Frequency Control and Automatic Voltage Regulation for Two-Area Interconnected Power System

Sahani¹,

Raj²,

Shankar³

et al. 2019

ijeei

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In this research work the combined Load Frequency Control (LFC) and Automatic Voltage Regulation (AVR) of a two-area interconnected power system has been considered. Each control area consists of linearized model of thermal and hydropower system. PID controller has been used as the secondary controller for the combined LFC-AVR of the proposed system. A powerful meta-heuristic algorithm Firefly optimisation technique is used for the optimisation of the proposed controller. Comparison of the system dynamics with and without proposed controller is investigated to show effectiveness of the proposed control scheme. Also, a comparison of the proposed control scheme with other popular meta-heuristic techniques shows the superiority of the proposed control scheme. Moreover, small signal stability analysis of the proposed system has been done using the state space representation of the proposed system.

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“…Banerjee and Chattopadhyay [67] proposed a modified SOS to design an improved 3 dimensional turbo code. SOS a novel powerful MH optimization technique is also proposed for the first time to solve the load frequency control problem [68]. Results show that the dynamic stability of the concerned power system effective enhancement with SOS.…”

Section: Introductionmentioning

confidence: 99%

Modified symbiotic organisms search for structural optimization

Kumar

Tejani²,

Mirjalili

2018

Engineering with Computers

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The structural dynamic response predominantly depends upon natural frequencies which fabricate these as a controlling parameter for dynamic response of the truss. However, truss optimization problems subjected to multiple fundamental frequency constraints with shape and size variables are more arduous due to its characteristics like non-convexity, nonlinearity, and implicit with respect to design variables. In addition, mass minimization with frequency constraints are conflicting in nature which intricate optimization problem. Using meta-heuristic for such kind of problem requires harmony between exploration and exploitation to regulate the performance of the algorithm. This paper proposes a modification of a nature inspired Symbiotic Organisms Search (SOS) algorithm called a Modified SOS (MSOS) algorithm to enhance its efficacy of accuracy in search (exploitation) together with exploration by introducing an adaptive benefit factor and modified parasitism vector. These modifications improved search efficiency of the algorithm with a good balance between exploration and exploitation, which has been partially investigated so far. The feasibility and effectiveness of proposed algorithm is studied with six truss design problems. The results of benchmark planar/space trusses are compared with other meta-heuristics. Complementarily the feasibility and effectiveness of the proposed algorithms are investigated by three unimodal functions, thirteen multimodal functions, and six hybrid functions of the CEC2014 test suit. The experimental results show that MSOS is more reliable and efficient as compared to the basis SOS algorithm and other state-of-the-art algorithms. Moreover, the MSOS algorithm provides competitive results compared to the existing meta-heuristics in the literature.

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Symbiotic organism search algorithm applied to load frequency control of multi-area power system

Cited by 96 publications

References 41 publications

Effect of energy storage systems on automatic generation control of interconnected traditional and restructured energy systems

Effect of energy storage systems on automatic generation control of interconnected traditional and restructured energy systems

Firefly Optimization Based Control Strategies for Combined Load Frequency Control and Automatic Voltage Regulation for Two-Area Interconnected Power System

Modified symbiotic organisms search for structural optimization

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