Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm

Sulaiman, Mohd Herwan; Rashid, Mamunur; Alfandi, Omar; Mohamed, Mohd Rusllim; Ahmad, Abu Zaharin; Bakar, Mohd Shafie

doi:10.1049/cp.2014.1479

Cited by 13 publications

(12 citation statements)

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“…The performance of CSA has been analyzed with PSO and Gravitational Search Algorithm (GSA), which provides better results in terms of convergence process, robustness, and adjust the parameter. 6 Strength Pareto Multi-Group Search Optimizer (SPMGSO) was developed for solving multi-objective optimal reactive power dispatch (MORPD) problem. Comprehensively, analyzed with other types of algorithm, it provides better results to solve the complicated constrained difficulty with high-dimensional features of search space, better efficiency with more number of objective functions.…”

Section: Introductionmentioning

confidence: 99%

RETRACTED: Pareto-based allocations of multi-type flexible AC transmission system devices for optimal reactive power dispatch using Kinetic Gas Molecule Optimization algorithm

Panthagani¹,

Rao

2020

Measurement and Control

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Optimal reactive power dispatch is one of the key factors to attain cost-effective and stable functioning of power system. It is a complicated non-linear optimization issue with a combination of discrete and continuous control variables. Due to this complex feature of optimal reactive power dispatch, optimization technique has become an efficient method to solve this problem. In this work, Kinetic Gas Molecule Optimization algorithm with Pareto optimality is proposed for solving multi-objective optimal reactive power dispatch problem. The presentation of Kinetic Gas Molecule Optimization is improved by computing inertia weight and acceleration coefficients dynamically rather than a fixed value. Because of this reason, the searching capability of the particles in each iteration is improved. However, to improve the power system performance in optimal reactive power dispatch scenario, additional flexible AC transmission system devices like static VAR compensator, thyristor-controlled series compensator, and unified power flow controller are introduced to provide stable results when compared to conventional output because flexible AC transmission system devices are capable of controlling the flow of real power and reactive power. These details are implemented and tested on IEEE 30-bus test system with various objectives. The performance of proposed method is validated from MATLAB, which shows the value of power loss as 4.3583 and voltage deviation as 0.26499 with cost of US$469.6417 per MVAR, which shows considerably superior results when compared with implemented particle swarm optimization results. The proposed method provides an efficient result for solving multi-objective optimal reactive power dispatch issues.

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Section: Introductionmentioning

confidence: 99%

RETRACTED: Pareto-based allocations of multi-type flexible AC transmission system devices for optimal reactive power dispatch using Kinetic Gas Molecule Optimization algorithm

Panthagani¹,

Rao

2020

Measurement and Control

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“…The development and the exploitation in metaheuristic approach are further exposed to improve the results while resolving the optimal reactive power dispatch problems (ORPD) such as; particle swarm optimization [11], harmony search algorithm [12], improved harmony search algorithm [13] gray wolf optimizer [14], cuckoo search algorithm [15], backtracking search algorithm [16], gravitational search algorithm [17], seeker optimization algorithm [18], gaussian bare-bones water cycle algorithm [19], colliding bodies optimization algorithm [20], chaotic krill herd algorithm [21], moth-flame algorithm [22], chaotic particle swarm optimization [23], bacterial colony chemotaxis algorithm [24], whale optimization algorithm [25], adaptive chaotic symbiotic organisms search algorithm [26], imperialist competitive algorithm [27], invasive weed optimization [28] and firefly algorithm [29]. Moreover, some other meta-heuristic approaches in support are discussed in [30][31][32][33][34][35].…”

Section: B Literature Reviewmentioning

confidence: 99%

“…With run the power flow. 12), ( 13) and (15) Step 5: Updating Velocity: Updating velocity of FPSOGSA-Entropy by ( 24):…”

Section: Start Fpsogsa-entropymentioning

confidence: 99%

Application of Shannon Entropy Implementation Into a Novel Fractional Particle Swarm Optimization Gravitational Search Algorithm (FPSOGSA) for Optimal Reactive Power Dispatch Problem

et al. 2021

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Optimal reactive power dispatch (ORPD) intended for reducing the real power losses of the transmission scheme remains one of the supreme concerns for the research community to explore the competence of power schemes. Numerous systems have been deliberate to increase the performance of the optimization method in tunning the operational variables as well as explored through estimating the final results. The research offering a novel approach based on the entropy evolution technique implemented into Fractional PSOGSA algorithm to solve the optimal reactive power dispatch problem. To alleviate the drawback of PSOGSA the fractional and entropy techniques are implemented into the algorithm which enhanced memory effect, stability and robustness of the algorithm. The novel design of FPSOGSA-Entropy is further tested for the optimal reactive power dispatch problems on IEEE-30 and IEEE-57 bus standards to find the two objective functions; minimization of power line losses and voltage deviation. The superior performance of the proposed FPSOGSA-Entropy is further verified with the results of simple FPSOGSA for both single and multiple runs through comparative analysis study with state of art counterparts for each scenario of optimal reactive power dispatch problems.

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“…Sulaiman et al uses a nature-inspired swarm technique called Cuckoo Search Algorithm (CSA) to minimize the transmission line power loss in IEEE-57 bus network. The technique proves to be the most effective when compared with PSO and DE algorithms [42]. Whereas Lenin et al use a modified shuffled frog-leaping (MSFL) algorithm to solve ORPD problem [43].…”

Section: Introductionmentioning

confidence: 99%

Distribution Network Reconfiguration for Transmission Loss Minimization and Voltage Profile Improvement Using Salp Swarm Optimization Algorithm

Shanono

Abdullah

Noh

et al. 2021

Lecture Notes in Electrical Engineering

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The increased human population along with the advancements and demand for electrical appliances has led to the continuous overstretch of the existing power transmission lines. This tends to overload the transmission system, which results in an excessive power loss and subsequent system outage. Optimal reactive power dispatch (ORPD) is a mechanism deployed to ensure a secured operation as well as an economically viable power system network. ORPD is an optimal power dispatch technique that minimizes transmission line losses while adhering to both equality and non-equality constraints. This research study employed Salp Swarm Algorithm (SSA) to obtain the best vector control variables that give the minimal total active power loss on a standard IEEE 30-bus system network. The result obtained was compared against Particle Swarm Optimization (PSO), where SSA proves to be superior over PSO in the field ORPD.

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Loss Minimisation by Optimal Reactive Power Dispatch Using Cuckoo Search Algorithm

Cited by 13 publications

References 0 publications

RETRACTED: Pareto-based allocations of multi-type flexible AC transmission system devices for optimal reactive power dispatch using Kinetic Gas Molecule Optimization algorithm

RETRACTED: Pareto-based allocations of multi-type flexible AC transmission system devices for optimal reactive power dispatch using Kinetic Gas Molecule Optimization algorithm

Application of Shannon Entropy Implementation Into a Novel Fractional Particle Swarm Optimization Gravitational Search Algorithm (FPSOGSA) for Optimal Reactive Power Dispatch Problem

Distribution Network Reconfiguration for Transmission Loss Minimization and Voltage Profile Improvement Using Salp Swarm Optimization Algorithm

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