Constrained optimal power flow and optimal TCSC allocation using hybrid cuckoo search and ant lion optimizer

Mahapatra, Sheila; Malik, Nitin; Raj, Saurav; Srinivasan, Mohan Krishna

doi:10.1007/s13198-021-01334-1

Cited by 12 publications

(4 citation statements)

References 32 publications

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“…For instance, [37] presents a Hybrid Gradient-Based Optimizer with Moth-Flame Optimization Algorithm, while [38] proposes a Modified Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA). Additionally, [39] introduces a Hybrid Cuckoo Search algorithm and Ant-Lion Optimizer (CS-ALO) for identifying the optimal location of TCSC using CS and determining the optimal size using ALO. Furthermore, [40] presents the Grey Wolf Optimizer (GWO) as a solution for the OPF problem that takes into account FACTS devices.…”

Section: Literature Reviewmentioning

confidence: 99%

CAVOA: A chaotic optimization algorithm for optimal power flow with facts devices and stochastic wind power generation

Mohamed,

Kamel,

Hassan

et al. 2023

IET Generation Trans & Dist

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The study proposes a modified version of African Vultures Optimization Algorithm (AVOA) to address the optimal power flow (OPF) issue. The developed optimizer is called Chaotic AVOA (CAVOA). Prior to applying CAVOA to the problem at hand, its accuracy is evaluated using 23 benchmark functions. The production powers of WTs that are interrupted are predicted using Weibull probability density functions (PDFs). Two additional costs, namely penalty cost and reserve cost, are incorporated into the goal function of the OPF. The simulation results of CAVOA are compared with those of the original AVOA to solve the OPF. The proposed OPF technique and its solution methodology are verified on the IEEE 30‐bus test system, taking into account the flexible alternating current transmission systems (FACTS) devices, which have several benefits such as reducing active power transmission loss, regulating power flow, and improving voltage stability/profile. The research's simulation results demonstrate that CAVOA is more effective in identifying the OPF's optimal solution by reducing the overall power cost and power losses. The results indicate that the CAVOA algorithm outperforms AVOA as a metaheuristic optimization algorithm due to its superior capability in addressing challenging OPF problems with a minimal convergence rate. For example, when comparing the two algorithms, CAVOA achieved a significant improvement. It successfully reduced the cost function by approximately 0.023% in Case I and 0.035% in Case II, while also decreasing power loss by 2.57% in Case II and 0.57% in Case I. Additionally, CAVOA exhibited a remarkable reduction of 5.36% in voltage deviation compared to AVOA in Case I. Furthermore, in Case III, CAVOA demonstrated a decrease of 0.64% in gross cost when compared to AVOA.

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Section: Literature Reviewmentioning

confidence: 99%

CAVOA: A chaotic optimization algorithm for optimal power flow with facts devices and stochastic wind power generation

Mohamed,

Kamel,

Hassan

et al. 2023

IET Generation Trans & Dist

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“…VSIs are not only competent in identifying the critical lines and buses under both online and offline modes through static analysis or phasor measurement units, but also provide information on voltage instability or the proximity of a collapse under various loading conditions and contingencies, such as loss of generators or lines, and indicate real-time information for voltage instability through phasor measurement unit wide area measurement system (PMU-WAMS) [6][7][8][9]. The indices are also widely used as the objective function to solve various applications, such as determining the optimal location and sizing reactive power compensation (RPC) [10][11][12][13], optimal distributed generation allocation (DG) [14][15], optimal power flow [16][17][18][19], optimal reactive power dispatch in [20], optimal network reconfiguration [21], and optimal locations of PMUs [22]. The reviewed works on various applications of VSIs can be found in [23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

New Line Voltage Stability Index (BVSI) for Voltage Stability Assessment in Power System: The Comparative Studies

et al. 2022

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Modern power utilization has been forced to operate close to their stability limits, which may lead to voltage instability or collapse owing to the stressed operating conditions of networks. This raises the need to develop a new technique to predict the level of voltage security under different operating conditions to detect critical lines or buses that operate close to its stability limit. This study proposes a new line voltage stability index (BVSI) to identify weak lines and buses for various loading conditions and network configurations. Comparative studies between the existing voltage stability indices (VSIs) and the proposed index have been performed to comprehensively highlight the indices' foundation, performance, and overall behavior for several different IEEE benchmark test systems; 14-bus, 30-bus, 118-bus test systems and 33bus radial distribution system. The sensitivity towards different loading conditions due to variables such as active power, reactive power, angular difference between sending and receiving bus voltage, line resistance, and shunt admittance, which have been neglected in the formulation of VSIs, are briefly discussed. The findings of this work are aimed to provide a general guideline for other researchers in selecting the appropriate VSIs for various applications, particularly in solving optimization problems such as distributed generation (DG) and reactive power compensation (RPC) placement, optimal power flow, optimal reactive power dispatch, optimal network reconfiguration for various loading occasions, and different networks. Lastly, the application of the proposed index has been adopted as an analytical approach for solving optimal location and sizing of DG(s) problems. The results prove the effectiveness of the proposed index in accessing the voltage stability state and stress condition of lines. Besides, the proposed approach also capable of determining the potential candidate bus for single DG location and sizing effectively.

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“…In general, a huge count of researchers was undergone to develop optimal algorithms and methods for computing ATC. [7][8][9] Among them, sensitivity analysis is one the projected solution for enriching ATC and it was based on the linear incremental power flow, which is trouble-free to illustrate and compute. [10][11][12] Apart from this, it suffers from drawbacks like lack of consideration of the nonlinear effects of reactive power and voltage.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of available transfer capability using TCSC with hybridized model: Combining lion and moth flame algorithms

Singh

Yadav

Gupta

2022

Concurrency and Computation

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The practical computations of enhancing available transfer capability (ATC) are evolving in the recent times. Most of the presently available techniques for enhancing ATC are being implemented; however, in many cases, they do not consider the impact of communications taking place in between the "power transfers, loop flows, non-linearities, operating policies, and most importantly voltage collapse blackouts," respectively. Thus, the current research work aims to introduce a new hybrid method to solve the chaos in ATC in power system. The thyristor-controlled series compensation (TCSC) that belongs to series flexible alternating current transmission system device is utilized for enhancing ATC. The introduced algorithm is termed as Lion Updated Moth

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Constrained optimal power flow and optimal TCSC allocation using hybrid cuckoo search and ant lion optimizer

Cited by 12 publications

References 32 publications

CAVOA: A chaotic optimization algorithm for optimal power flow with facts devices and stochastic wind power generation

CAVOA: A chaotic optimization algorithm for optimal power flow with facts devices and stochastic wind power generation

New Line Voltage Stability Index (BVSI) for Voltage Stability Assessment in Power System: The Comparative Studies

Enhancement of available transfer capability using TCSC with hybridized model: Combining lion and moth flame algorithms

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