Comparative study of Pareto optimal multi objective cuckoo search algorithm and multi objective particle swarm optimization for power loss minimization incorporating UPFC

Nartu, Tejeswara Rao; Sankar, Matta Mani; Rao, Surapu Prasada; Rao, Boddepalli Srinivasa

doi:10.1007/s12652-020-02142-4

Cited by 14 publications

(6 citation statements)

References 18 publications

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“…The algorithm aims to obtain the Pareto Optimal with respect to some switch changes and power loss with the highest voltage stability limit. This algorithm is improved for Pareto Optimal from the MOCS algorithm in [18]. The algorithm steps are:…”

Section: Proposed Algorithm and Pareto Optimalmentioning

confidence: 99%

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Optimal Distribution Network Reconfiguration Using Multi-Objective Cuckoo Search Algorithm

Saedi

Hanifah

Ladin

et al. 2022

IIUMEJ

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In power system electricity delivery, the distribution system has the most electricity loss as the system has the highest R/X ratio and has a radial network at one time. Optimal reconfiguration of the distribution network is needed in order to reduce power losses. However, as it is also involved with multiple objectives and constraint problems such as switching frequency, voltage, and current limits, it is difficult to find the optimal solution. Hence, this paper proposes the Multi-objective Cuckoo Search (MOCS) algorithm to find the optimal reconfiguration of distribution networks by considering minimizing power losses and switch operations. Based on the simulation results on the IEEE-33 bus system, the performance of the MOCS-based scheme has been found to be significantly better than the single-objective algorithm thereby reducing approximately 33% of the power losses. ABSTRAK Melalui sistem penghantaran jana kuasa elektrik, sistem pengagihan mempunyai pembaziran tenaga elektrik terbesar kerana sistem ini mempunyai nisbah R/X paling tinggi dan mempunyai satu rangkaian radial pada tiap-tiap satu masa. Konfigurasi semula rangkaian pengedaran yang optimum diperlukan bagi mengurangkan pembaziran tenaga. Walaubagaimanapun, oleh kerana ia melibatkan objektif dan kekangan masalah yang pelbagai seperti kadar peralihan, had voltan serta arus, adalah sukar bagi mendapatkan bacaan yang optimum. Oleh itu, kajian ini mencadangkan Carian Cuckoo Pelbagai Objektif (MOCS) bagi mencari konfigurasi semula yang optimum bagi sistem pengagihan tenaga dengan mengambil kira pengurangan pembaziran tenaga dan kadar peralihan. Berdasarkan keputusan simulasi pada sistem bas IEEE-33, pretasi MOCS telah menunjukkan peningkatan yang ketara berbanding algoritma objektif tunggal dan pengurangan sebanyak 33% tenaga.

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Section: Proposed Algorithm and Pareto Optimalmentioning

confidence: 99%

“…MOCS is the extended version of the cuckoo search algorithm developed by Yang and Deb [14]. It has been tested against relevant test functions and then successfully applied to numerous problems [15][16][17][18]. This study uses MOCS to solve the DNR optimization problem focusing on power loss reduction and switching operations.…”

Section: Introductionmentioning

confidence: 99%

Optimal Distribution Network Reconfiguration Using Multi-Objective Cuckoo Search Algorithm

Saedi

Hanifah

Ladin

et al. 2022

IIUMEJ

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“…Minimizing power losses is one of the primary goals of installing FACTS devices in power grids; therefore, almost all articles dealing with these devices have addressed this issue [5]- [9]. Numerous authors have looked into the advantages of UPFC placement on system performance.…”

Section: Introductionmentioning

confidence: 99%

Loss reduction of transmission lines using PSO-based optimum performance of UPFC

2023

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Transmission line losses are one of the essential topics and issues in power systems research. Several methods and techniques have been used to reduce these losses, and one of these modern techniques is flexible alternating current transmission systems (FACTS). In this paper, one of the most important types of this technology, the unified power flow controller (UPFC), was used to reduce losses in the Iraqi national grid (ING) 400 kV. This paper presents an efficient method for minimizing losses of transmission lines in the ING system (400 kV) 46-bus approach. A particle swarm optimization (PSO)-based optimum proportional-integral (PI) controller with UPFC was proposed to obtain the optimal location of UPFC and optimum parameters of the PI controller to achieve the objective function of the research. MATLAB coded the algorithm. The Newton-Raphson method was employed to perform load flow analysis. The results showed that the best place for UPFC is buses (14-17) named BGE4 (Baghdad)-AMN4 (Baghdad), and the total active power and reactive power losses decreased from 727.4593 to 579.3874 MW and from 5155.9 to 3971.1 MVAR, respectively and also led to voltage regulation.

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“…However, the problem of integrating these into the power system is quite complicated where achieving maximum effectiveness is through proper sizing and siting of SVCs. For this reason, many authors have tried to resolve this problem by using various optimization techniques, such as differential evolution (DE) [3], whale optimization algorithm (WOA) [4], simulated annealing (SA), and particle swarm optimization (PSO) [5], multi-objective genetic algorithm (MOGA) [6], multi-objective cuckoo search (MOCS) [7], imperialistic competitive algorithm (ICA) [3], harmony search (HS) [8].…”

Section: Introductionmentioning

confidence: 99%

Sizing and Sitting of Static VAR Compensator (SVC) Using Hybrid Optimization of Combined Cuckoo Search (CS) and Antlion Optimization (ALO) Algorithms

et al. 2022

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Worldwide, due to the abrupt growth of population, the load demand has been rising dramatically in the last few years. This led to an increase in branch overloads, voltage deviations, and power losses. These problems may result in line outages or the occurrence of blackouts. Flexible AC transmission system (FACTS) devices can be installed in the power system to ensure increased power flow capability and flexible voltage control to address these issues. In this paper, one of the most used FACTS is utilised. It is called Static VAR Compensator (SVC). This controller is one of the most commonly used shunt FACTS controllers due to its low cost in comparison to others, ease of operation, and integration into the power grid. Two Optimization algorithms are combined to form a hybrid optimization approach: Cuckoo Search (CS) and Antlion Optimization (ALO). This hybrid approach employs the exploration of ALO to adjust the optimum allocation and size for SVCs in the power system. This study proposes the IEEE 57 bus scheme as a fairly large structure, with the 50 and 41 branch outages considered the worst-case scenarios for line outages in this system. The simulation results show that the proposed methodology balances exploring the research space and exploiting the best existing solutions compared to some of the other introduced approaches in the literature.

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Comparative study of Pareto optimal multi objective cuckoo search algorithm and multi objective particle swarm optimization for power loss minimization incorporating UPFC

Cited by 14 publications

References 18 publications

Optimal Distribution Network Reconfiguration Using Multi-Objective Cuckoo Search Algorithm

Optimal Distribution Network Reconfiguration Using Multi-Objective Cuckoo Search Algorithm

Loss reduction of transmission lines using PSO-based optimum performance of UPFC

Sizing and Sitting of Static VAR Compensator (SVC) Using Hybrid Optimization of Combined Cuckoo Search (CS) and Antlion Optimization (ALO) Algorithms

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