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Journal articles on the topic 'Power Loss Minimization and GTO Algorithm'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Ram, Prasad Kannemadugu, Adhimoorthy V, and Lakshmi Devi A. "Optimal Allocation of Combined DG and DSTATCOM for Enhancement of Voltage Stability in Radial Distribution Networks." Indian Journal of Science and Technology 16, no. 35 (2023): 2845–55. https://doi.org/10.17485/IJST/v16i35.1042.

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Abstract <strong>Objectives:</strong> To improve the voltage profile, minimize the network power loss and enhance the stability of the Redial Distribution Systems (RDS). <strong>Methods:</strong> A novel and successful meta-heuristic method of Group Teaching Optimization (GTO) algorithm is proposed to evolve the solution of voltage stability in RDS. The effective compensating devices of DG and DSTATCOM are used for increasing the voltage profile and reducing the system losses. The VSI is also calculated to predetermine the best position of the two compensating devices <stro

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Reddy, N. Madhusudhan, Dr T. Vamsee Kiran, I. Kranthi Kumar, Karri Ravikumar Reddy, Chodagam Srinivas, and K. Divya. "Optimizing Capacitor Placement in Distribution Systems Under Variable Loading Conditions with Golden Jack Optimization (GJO)." International Journal of Electrical and Electronics Research 12, no. 2 (2024): 338–44. http://dx.doi.org/10.37391/ijeer.120202.

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In modern society, the demand for electricity is ever-growing, making the minimization of power losses in distribution systems paramount. One significant aspect contributing to these losses is the strategic placement of capacitors within the distribution network. Efficient capacitor placement not only reduces power losses but also enhances the overall performance and reliability of the system. In today's world, where electricity is indispensable, minimizing power losses in the distribution system holds significant importance. This research introduces the Golden Jack Optimization (GJO) algorith

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NAWAS, AHAMED HUSSAIN ASIF NOORUL, and SELVAPERUMAL SUNDARAMOORTHY. "GIANT TREVALLY OPTIMIZED CONGESTION MANAGEMENT USING FACTS CONTROLLER ALLOCATION IN DEREGULATED ELECTRICITY MARKETS." REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE 69, no. 4 (2024): 377–82. http://dx.doi.org/10.59277/rrst-ee.2024.69.4.2.

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One of the technical issues arising from deregulation is transmission line congestion. The size and location of FACTS controllers like thyristor-controlled series compensators (TCSCs) and static VAR compensator (SVC) devices significantly affect their efficiency in congestion management problems. As a nonlinear problem, locating and sizing these devices in a power network is difficult. To solve this issue, this paper presents the technique for optimal FACTS placement using the giant trevally optimizer (GTO) algorithm for congestion management (CM). Three objective functions are considered to r

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In, Sokvan, Sovann Ang, Chivon Choeung, Sokun Ieng, Horchhong Cheng, and Vichet Huy. "Optimal Reactive Power Dispatch Using Artificial Gorilla Troops Optimizer Considering Voltage Stability." International Journal of Electrical and Electronics Research 12, no. 3 (2024): 1000–1008. http://dx.doi.org/10.37391/ijeer.120334.

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The power system has been expanded to supply and fulfil the consumers’ requirements for reliability, affordability, and power quality. Power loss reduction and voltage stability enhancement are important points and have been considered interesting subjects for researchers and utilities. Furthermore, reactive power plays an important role in power system stability, security, and voltage improvement, and it is known as reactive power dispatch (RPD). In this paper, a newly developed meta-heuristic optimization technique that inspired the gorilla troop’s social intelligence in nature is applied. I

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Lenin, K. "ENHANCED SPIDER ALGORITHM FOR MINIMIZATION OF REAL POWER LOSS." International Journal of Research -GRANTHAALAYAH 6, no. 4 (2018): 301–11. http://dx.doi.org/10.29121/granthaalayah.v6.i4.2018.1665.

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In this paper Enhanced Spider (ES) algorithm is proposed to solve reactive power Problem. Enthused by the spiders, a new Enhanced Spider (ES) algorithm is utilized to solve reactive power problem. The composition is primarily based on the foraging approach of social spiders, which make use of of the vibrations spread over the spider web to choose the position of prey. The simulation results demonstrate high-quality performance of Enhanced Spider (ES) algorithm in solving reactive power problem. The projected Enhanced Spider (ES) algorithm has been tested in standard IEEE 57,118 bus systems and

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Dr., K. Lenin *1. "ENHANCED SPIDER ALGORITHM FOR MINIMIZATION OF REAL POWER LOSS." International Journal of Research - Granthaalayah 6, no. 4 (2018): 301–11. https://doi.org/10.5281/zenodo.1248184.

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In this paper Enhanced Spider (ES) algorithm is proposed to solve reactive power Problem. Enthused by the spiders, a new Enhanced Spider (ES) algorithm is utilized to solve reactive power problem. The composition is primarily based on the foraging approach of social spiders, which make use of of the vibrations spread over the spider web to choose the position of prey. The simulation results demonstrate high-quality performance of Enhanced Spider (ES) algorithm in solving reactive power problem. The projected Enhanced Spider (ES) algorithm has been tested in standard IEEE 57,118 bus systems and

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7

T., Nireekshana, Upadhyay Poonam, Bhavani J., and Krishna Kumari N. "Comparative Analysis of Multi Objective Optimal Power Flow in Power Systems." Journal of Recent Trends in Electrical Power System 3, no. 2 (2020): 1–12. https://doi.org/10.5281/zenodo.3988980.

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<em>This paper consists of the comparative analysis of different methods applied to loss minimization in power system. The objective is to minimize the total power loss and keep the power outputs of generators; bus voltages, shunt capacitors/reactors and transformer tap setting in their specified limits. By maintaining the whole system power loss as minimum there by minimum cost allocation can be achieved. This project explains a comparative analysis between Gradient methods, Search methods and Genetic Algorithm Approach (GA). The Gradient and Search methods are the iterative local optimizatio

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Lenin, K., B. Ravindhranath Reddy, and M. Surya Kalavathi. "IMPROVED BABOON ALGORITHM FOR MINIMIZATION OF REAL POWER LOSS." International Journal of Research -GRANTHAALAYAH 5, no. 1 (2017): 33–42. http://dx.doi.org/10.29121/granthaalayah.v5.i1.2017.1690.

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This paper projects Improved Baboon Algorithm (IBA) for solving the Reactive Power dispatch problem. The key feature in this problem is reduction of real power loss and to keep voltage profiles within limits. This algorithm is inspired from the tree climbing procedures of Baboons, where the Baboons look for the highest tree by climbing up from their positions. The simulation results expose amended performance of the IBA in solving an optimal reactive power dispatch problem. In order to evaluate up the performance of the proposed algorithm, it has been tested on Standard IEEE 30 bus system and

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K.Lenin, Reddy B.Ravindhranath, and Kalavathi M.Surya. "IMPROVED BABOON ALGORITHM FOR MINIMIZATION OF REAL POWER LOSS." International Journal of Research -GRANTHAALAYAH 5, no. 1 (2017): 33–42. https://doi.org/10.5281/zenodo.259549.

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This paper projects Improved Baboon Algorithm (IBA) for solving the Reactive Power dispatch problem. The key feature in this problem is reduction of real power loss and to keep voltage profiles within limits. This algorithm is inspired from the tree climbing procedures of Baboons, where the Baboons look for the highest tree by climbing up from their positions. The simulation results expose amended performance of the IBA in solving an optimal reactive power dispatch problem. In order to evaluate up the performance of the proposed algorithm, it has been tested on Standard IEEE 30 bus system and

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10

Lenin, K. "REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM." International Journal of Research -GRANTHAALAYAH 5, no. 5 (2017): 88–98. http://dx.doi.org/10.29121/granthaalayah.v5.i5.2017.1840.

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This paper presents a Mutual Mammal Behavior (MM) algorithm for solving Reactive power problem in power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization is taken is taken as main objective. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. A Meta heuristic algorithm for global optimization called the Mutual Mammal Behavior (MM) is introduced. Mammal groups like Carnivores, African lion, Cheetah, Dingo Fennec Fox, Moose, Polar Bear, Sea

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Dr.K.Lenin. "REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM." INTERNATIONAL JOURNAL OF RESEARCH- GRANTHAALAYAH 5, no. 5 (2017): 88–98. https://doi.org/10.5281/zenodo.583889.

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This paper presents a Mutual Mammal Behavior (MM) algorithm for solving Reactive power problem in power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization is taken is taken as main objective. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. A Meta heuristic algorithm for global optimization called the Mutual Mammal Behavior (MM) is introduced. Mammal groups like Carnivores, African lion, Cheetah, Dingo Fennec Fox, Moose, Polar Bear, Sea

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Lenin, K. "Minimization of Real Power Loss by River Progression Algorithm." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 6 (2017): 696–701. http://dx.doi.org/10.23956/ijarcsse/sv7i5/0196.

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Lenin, K. "MINIMIZATION OF REAL POWER LOSS BY ENHANCED GREAT DELUGE ALGORITHM." International Journal of Research -GRANTHAALAYAH 5, no. 8 (2017): 207–16. http://dx.doi.org/10.29121/granthaalayah.v5.i8.2017.2215.

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This paper presents Enhanced Great Deluge Algorithm (EDA) for solving reactive power problem. Alike other local exploration methods, this Enhanced Great Deluge Algorithm (EDA) also swap general solution (fresh_Config) with most excellent results (most excellent_Config) that have been found by then. This deed prolong until stop conditions is offered. In this algorithm, new solutions are selected from neighbours. Selection strategy is different from other approaches. In order to evaluate validity of the proposed Enhanced Great Deluge Algorithm (EDA) algorithm, it has been tested on standard IEEE

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Dr.K.Lenin. "MINIMIZATION OF REAL POWER LOSS BY ENHANCED GREAT DELUGE ALGORITHM." International Journal of Research - Granthaalayah 5, no. 8 (2017): 207–16. https://doi.org/10.5281/zenodo.886353.

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This paper presents Enhanced Great Deluge Algorithm (EDA) for solving reactive power problem. Alike other local exploration methods, this Enhanced Great Deluge Algorithm (EDA) also swap general solution (fresh_Config) with most excellent results (most excellent_Config) that have been found by then. This deed prolong until stop conditions is offered. In this algorithm, new solutions are selected from neighbours. Selection strategy is different from other approaches. In order to evaluate validity of the proposed Enhanced Great Deluge Algorithm (EDA) algorithm, it has been tested on standard IEEE

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15

Lenin, Kanagasabai. "True power loss reduction by augmented mine blast algorithm." International Journal of Informatics and Communication Technology (IJ-ICT) 9, no. 2 (2020): 83. http://dx.doi.org/10.11591/ijict.v9i2.pp83-91.

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In this paper, Mine Blast Algorithm (MBA) has been intermingled with Harmony Search (HS) algorithm for solving optimal reactive power dispatch problem. MBA is based on explosion of landmines and HS is based on Creativeness progression of musicians – both are hybridized to solve the problem. In MBA Initial distance of shrapnel pieces are reduced gradually to allow the mine bombs search the probable global minimum location in order to amplify the global explore capability. Harmony search (HS) imitates the music creativity process where the musicians supervise their instruments’ pitch by searchin

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Kanagasabai, Lenin. "True power loss reduction by augmented mine blast algorithm." International Journal of Informatics and Communication Technology (IJ-ICT) 9, no. 2 (2020): 83–91. https://doi.org/10.11591/ijict.v9i2.pp83-91.

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In this paper, Mine Blast Algorithm (MBA) has been intermingled with Harmony Search (HS) algorithm for solving optimal reactive power dispatch problem. MBA is based on explosion of landmines and HS is based on Creativeness progression of musicians-both are hybridized to solve the problem. In MBA Initial distance of shrapnel pieces are reduced gradually to allow the mine bombs search the probable global minimum location in order to amplify the global explore capability. Harmony search (HS) imitates the music creativity process where the musicians supervise their instruments’ pitch by sear

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17

Lenin, K. "MINIMIZATION OF REAL POWER LOSS BY ENHANCED GRAVITATIONAL SEARCH ALGORITHM." International Journal of Research -GRANTHAALAYAH 5, no. 7 (2017): 623–30. http://dx.doi.org/10.29121/granthaalayah.v5.i7.2017.2171.

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In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. Gravitational search algorithm (GSA) results are improved by using artificial bee colony algorithm (ABC). In GSA, solutions are fascinated towards each other by applying gravitational forces, which depending on the masses assigned to the solutions, to each other. The heaviest mass will move slower than other masses and pull others. Due to nature of gravitation, GSA may pass global minimum if some solutions stuck to local minimum. ABC updates the positions of the best solutions that hav

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Dr.K.Lenin. "MINIMIZATION OF REAL POWER LOSS BY ENHANCED GRAVITATIONAL SEARCH ALGORITHM." International Journal of Research - Granthaalayah 5, no. 7 (2017): 523–30. https://doi.org/10.5281/zenodo.844717.

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In this paper, Enhanced Gravitational Search (EGS) algorithm is proposed to solve the reactive power problem. Gravitational search algorithm (GSA) results are improved by using artificial bee colony algorithm (ABC). In GSA, solutions are fascinated towards each other by applying gravitational forces, which depending on the masses assigned to the solutions, to each other. The heaviest mass will move slower than other masses and pull others. Due to nature of gravitation, GSA may pass global minimum if some solutions stuck to local minimum. ABC updates the positions of the best solutions that hav

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19

Jebaraj, Luke, Charles Christober Asir Rajan, and Kumar Sriram. "Application of Firefly Algorithm in Voltage Stability Environment Incorporating Circuit Element Model of SSSC with Variable Susceptance Model of SVC." Advances in Electrical Engineering 2014 (April 24, 2014): 1–11. http://dx.doi.org/10.1155/2014/349787.

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This paper proposes an application of firefly algorithm (FA) based extended voltage stability margin and minimization of active (or) real power loss incorporating Series-Shunt flexible AC transmission system (FACTS) controller named as static synchronous series compensator (SSSC) combined with static var compensator (SVC). A circuit model of SSSC and variable susceptance model of SVC are utilized to control the line power flows and bus voltage magnitudes, respectively, for real power loss minimization and voltage stability limit improvement. The line quality proximity index (LQP) is used to as

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20

Yapıcı, Hamza, and Nurettin Çetinkaya. "An Improved Particle Swarm Optimization Algorithm Using Eagle Strategy for Power Loss Minimization." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/1063045.

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The power loss in electrical power systems is an important issue. Many techniques are used to reduce active power losses in a power system where the controlling of reactive power is one of the methods for decreasing the losses in any power system. In this paper, an improved particle swarm optimization algorithm using eagle strategy (ESPSO) is proposed for solving reactive power optimization problem to minimize the power losses. All simulations and numerical analysis have been performed on IEEE 30-bus power system, IEEE 118-bus power system, and a real power distribution subsystem. Moreover, th

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Lenin, K. "TRUE POWER LOSS REDUCTION BY HARMONY SEARCH ALGORITHM." International Journal of Research -GRANTHAALAYAH 6, no. 9 (2018): 196–205. http://dx.doi.org/10.29121/granthaalayah.v6.i9.2018.1220.

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This paper presents Harmony Search algorithm (HS) for solving the reactive power problem. Real power loss minimization is the major objective & also voltage profiles are should be kept within the limits. This paper introduces a new search model the harmony search (HS) algorithm is a relatively new population-based metaheuristic optimization algorithm. It emulates the music improvisation progression where musicians improvise their instruments’ pitch by searching for a perfect state of harmony. In order to evaluate the efficiency of the proposed algorithm, it has been tested on practical 191

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Dr., K. Lenin. "TRUE POWER LOSS REDUCTION BY HARMONY SEARCH ALGORITHM." International Journal of Research - Granthaalayah 6, no. 9 (2018): 196–205. https://doi.org/10.5281/zenodo.1436806.

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This paper presents Harmony Search algorithm (HS) for solving the reactive power problem. Real power loss minimization is the major objective & also voltage profiles are should be kept within the limits. This paper introduces a new search model the harmony search (HS) algorithm is a relatively new population-based metaheuristic optimization algorithm. It emulates the music improvisation progression where musicians improvise their instruments’ pitch by searching for a perfect state of harmony. In order to evaluate the efficiency of the proposed algorithm, it has been tested on practic

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Coronado de Koster, Othón Aram, and José Antonio Domínguez-Navarro. "Multi-Objective Tabu Search for the Location and Sizing of Multiple Types of FACTS and DG in Electrical Networks." Energies 13, no. 11 (2020): 2722. http://dx.doi.org/10.3390/en13112722.

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Flexible AC transmission systems and distributed generation units in power systems provide several benefits such as voltage stability, power loss minimization, thermal limits enhancement, or enables power system management close to the limit operation points; and by extension, economic benefits such as power fuel cost and power loss cost minimization. This work presents a multi-objective optimization algorithm to determine the location and size of hybrid solutions based on a combination of Flexible AC transmission systems devices and distributed generation. Further, the work expands the types

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Пугачев, Александр, Aleksandr Pugachev, Владимир Воробьев, Vladimir Vorobev, Андрей Космодамианский, and Andrey Kosmodamianskiy. "Control system of tractive induction motor with power loss minimization." Bulletin of Bryansk state technical university 2015, no. 2 (2015): 55–61. http://dx.doi.org/10.12737/22898.

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The mathematical model of induction motor taking power losses in stator and rotor iron and typical non-linearity is designed. The algorithm of optimal flux linkage reference providing power loss minimization is developed with regard to vector control. The induction motor stator current and voltage limits, the diesel generator unit power are chosen as a limiting factor. The tractive induction motor control system providing the direct regulation of wheel sliding for protection from slipping and having the internal system of power loss minimization is designed. The results of simulation are prese

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Lenin, K. "ENHANCED ALGORITHM FOR REDUCTION OF ACTIVE POWER LOSS." International Journal of Research -GRANTHAALAYAH 6, no. 7 (2018): 45–51. http://dx.doi.org/10.29121/granthaalayah.v6.i7.2018.1282.

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In this paper, Enhanced Aggressive Weed Optimization (EWO) algorithm is applied to solve the optimal reactive power Problem. Aggressive Weed Optimization is a stochastic search algorithm that imitate natural deeds of weeds in colonize and detection of appropriate place for growth and reproduction. Enhanced Aggressive Weed Optimization (EWO) algorithm is based on hybridization of genetic algorithm with weed optimization algorithm which refers combination of crossover and mutation of genetic algorithm, and by the use of the cross factor new species are arisen. Proposed Enhanced Aggressive Weed O

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Dr., K. Lenin. "ENHANCED ALGORITHM FOR REDUCTION OF ACTIVE POWER LOSS." International Journal of Research - Granthaalayah 6, no. 7 (2018): 45–51. https://doi.org/10.5281/zenodo.1322997.

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In this paper, Enhanced Aggressive Weed Optimization (EWO) algorithm is applied to solve the optimal reactive power Problem. Aggressive Weed Optimization is a stochastic search algorithm that imitate natural deeds of weeds in colonize and detection of appropriate place for growth and reproduction. Enhanced Aggressive Weed Optimization (EWO) algorithm is based on hybridization of genetic algorithm with weed optimization algorithm which refers combination of crossover and mutation of genetic algorithm, and by the use of the cross factor new species are arisen. Proposed Enhanced Aggressive Weed O

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Lamichhane, Bishal, and Mahesh Chandra Luintel. "Use of Genetic Algorithm on Optimal Power Flow: An Illustration of Transmission Line Loss Minimization." Kathford Journal of Engineering and Management 1, no. 1 (2018): 1–4. http://dx.doi.org/10.3126/kjem.v1i1.22012.

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This paper presents the usefulness and effectiveness of Genetic Algorithm on solving Optimal Power Flow (OPF) problem formulation of a real world power system. Optimization is a broad concept that is generally directly or indirectly related to cost factor. In this case, transmission lines loss minimization is presented as the objective of optimization problem formulation keeping all other technical factors and parameters under operating constraints. Results of this study, presented in the Integrated Nepal Power System (INPS) transmission line network show that the Genetic Algorithm is effectiv

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Duraisamy, Prasanth, and Arul Ponnusamy. "Power System Performance Improvement by Optimal Placement and Sizing of SVC using Genetic Algorithm." International Journal of Applied Power Engineering (IJAPE) 6, no. 2 (2017): 55. http://dx.doi.org/10.11591/ijape.v6.i2.pp55-62.

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The power system loss minimization becomes more important as the need of power generation is more recent days. The loss minimization improves the voltage profile which improves the loadability of the system. In many types of flexible AC transmission system (FACTS) devices static var compensators (SVC) are cost vise it is affordable and it improves the system performance with lesser size. Here SVC is optimally placed in a test system of 30 bus system. Genetic algorithm is used to find the optimal results.

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Duraisamy, Prasanth, and Arul Ponnusamy. "Power System Performance Improvement by Optimal Placement and Sizing of SVC using Genetic Algorithm." International Journal of Applied Power Engineering (IJAPE) 6, no. 2 (2017): 56. http://dx.doi.org/10.11591/ijape.v6.i2.pp56-63.

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The power system loss minimization becomes more important as the need of power generation is more recent days. The loss minimization improves the voltage profile which improves the loadability of the system. In many types of Flexible AC Transmission System (FACTS) devices Static Var Compensators (SVC) are cost vise it is affordable and it improves the system performance with lesser size. Here SVC is optimally placed in a test system of 30 bus system. Genetic algorithm is used to find the optimal results.

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Osazuwa, Obakpolo,, Onyegbadue Ikenna, and Guiawa Mathurine. "Power Loss Minimization and Voltage Profile Improvement on Nigeria Distribution Network Using Whale Optimization Algorithm." International Journal of Research and Review 11, no. 10 (2024): 225–46. http://dx.doi.org/10.52403/ijrr.20241021.

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The power grid has significant power losses, unstable voltage, and large voltage drops during high demand due to its high resistance. One way to reduce power loss is by strategically placing and sizing Distributed Generation (DG) within the distribution network. However, improper installation of DG can increase power loss. To address this issue, various optimization techniques have been used, but finding the best solution and dealing with complex issues has been challenging. It is important to make efforts to optimally place and size DG in the distribution network to minimize power loss. To th

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A., Immanuel, Challa Babu, Sudheer P., Pavan Kumar Naidu R., and Nageswara Rao Atyam. "Adaptive FPA Algorithm based OPF with Unified Power Flow Controller." EAI Endorsed Transactions on Energy Web 9, no. 40 (2022): e4. http://dx.doi.org/10.4108/ew.v9i40.150.

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In this work a novel modified flower pollination algorithm has been developed to solve the problem of single and multi-objective Optimal Power Flow operations for Unified power Flow Controller in Flexible Alternating Current Transmission Systems. In the proposed Adaptive Flower Pollination Algorithm the best initial solution can be chosen from the fittest and also the weights are adaptively adjusted to get better convergence characteristics. The nature of the objective functions is non-linear and difficult to get best possible solutions within the boundary conditions of total power demand. The

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Lenin, K. "ACTIVE POWER LOSS REDUCTION BY FLOWER POLLINATION ALGORITHM." International Journal of Research -GRANTHAALAYAH 5, no. 12 (2020): 223–31. http://dx.doi.org/10.29121/granthaalayah.v5.i12.2017.497.

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This paper presents Flower Pollination (FP) algorithm for solving the optimal reactive power problem. Minimization of real power loss is taken as key intent. Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. The biological evolution point of view, the objective of the flower pollination is the survival of the fittest and the optimal reproduction of plants in terms of numbers as well as the largely fittest. In order to evaluate the performance of the proposed Flower Pollination (FP) algorithm, it has been tested on IEEE 57 bus sys

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Dr.K.Lenin. "ACTIVE POWER LOSS REDUCTION BY FLOWER POLLINATION ALGORITHM." International Journal of Research - Granthaalayah 5, no. 12 (2017): 223–31. https://doi.org/10.5281/zenodo.1134563.

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This paper presents Flower Pollination (FP) algorithm for solving the optimal reactive power problem. Minimization of real power loss is taken as key intent. Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. The biological evolution point of view, the objective of the flower pollination is the survival of the fittest and the optimal reproduction of plants in terms of numbers as well as the largely fittest. In order to evaluate the performance of the proposed Flower Pollination (FP) algorithm, it has been tested on IEEE 57 bus sys

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Khasanov, Mansur, Salah Kamel, Jasur Abdubannaev, Furqat Nazarov, Abror Kurbanov, and Urinboy Jalilov. "Optimal distribution network reconfiguration to minimization power loss." E3S Web of Conferences 402 (2023): 05017. http://dx.doi.org/10.1051/e3sconf/202340205017.

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With the development of industry, population growth, and suburbanization, load demand is constantly increasing from year to year. Overload demand has greatly strained the distribution network (DN), resulting in increased power losses due to the high-power flow. Therefore, it becomes very important to minimize power losses at the DN to maximize the efficiency of the distribution companies. Network reconfiguration is one of the effective methods distribution companies use to minimize losses in the DN. This paper proposes Dingo Optimization Algorithm (DOA) to solve network reconfiguration problem

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Musa, Abdulhamid, and Tengku Juhana Tengku Hashim. "Optimal sizing and location of multiple distributed generation for power loss minimization using genetic algorithm." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 2 (2019): 956. http://dx.doi.org/10.11591/ijeecs.v16.i2.pp956-963.

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This paper presents a Genetic Algorithm (GA) for optimal location and sizing of multiple distributed generation (DG) for loss minimization. The study is implemented on a 33-bus radial distribution system to optimally allocate different numbers of DGs through the minimization of total active power losses and voltage deviation at power constraints of 0 – 2 MW and 0 – 3 MW respectively. The study proposed a PQ model of DG and Direct Load Flow (DLF) technique that uses Bus Incidence to Branch current (BIBC) and Branch Current to Bus Voltage (BCBV) matrices. The result obtained a minimum base case

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Shahbudin, Irham Syafiq, Ismail Musirin, Saiful Izwan Suliman, et al. "FACTS device installation in transmission system using whale optimization algorithm." Bulletin of Electrical Engineering and Informatics 8, no. 1 (2019): 30–38. http://dx.doi.org/10.11591/eei.v8i1.1442.

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As the world is progressing forward, the load demand in the power system has been continuously increasing day by day. This situation has forced the power system to operate under stress condition due to its limitation. Therefore, due to the stressed condition, the transmission losses faced higher increment with a lower minimum voltage. Theoretically, the installation of the Flexible AC Transmission System (FACTS) device can solve the problem experienced by the power system. This paper presents the Whale Optimization Algorithm for loss minimization using FACTS devices in the transmission system.

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Irham, Syafiq Shahbudin, Musirin Ismail, Izwan Suliman Saiful, et al. "FACTS device installation in transmission system using whale optimization algorithm." Bulletin of Electrical Engineering and Informatics 8, no. 1 (2019): 30–38. https://doi.org/10.11591/eei.v8i1.1442.

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As the world is progressing forward, the load demand in the power system has been continuously increasing day by day. This situation has forced the power system to operate under stress condition due to its limitation. Therefore, due to the stressed condition, the transmission losses faced higher increment with a lower minimum voltage. Theoretically, the installation of the Flexible AC Transmission System (FACTS) device can solve the problem experienced by the power system. This paper presents the Whale Optimization Algorithm for loss minimization using FACTS devices in the transmission system.

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Zhao, Buzheng, and Jianmei Xiao. "Reconfiguration of Distributed Power Distribution Networks Based on Gravitational Search Algorithms." Journal of Physics: Conference Series 2527, no. 1 (2023): 012071. http://dx.doi.org/10.1088/1742-6596/2527/1/012071.

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Abstract Distributed power supply access to the system affects the tidal distribution of the distribution network. The article establishes a mathematical optimization model with network loss minimization and load balance minimization as the objective function. In this paper, the idea of elite strategy is introduced into the gravitational search algorithm and combined with the Sigmoid function, an optimization method of distribution network reconfiguration based on the improved gravitational search algorithm is proposed by improving the particle iteration rule. The mathematical model is solved

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Lomi, Abraham, Awan Uji Krismanto, I. Made Wartana, and Dipu Sarkar. "A Numerically Robust Sequential Linear Programming Algorithm for Reactive Power Optimization." E3S Web of Conferences 188 (2020): 00002. http://dx.doi.org/10.1051/e3sconf/202018800002.

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A robust sequential primal-dual linear programming formulation for reactive power optimization is developed and discussed in this paper. The algorithm has the characteristic that no approximations or complicate control logic are required in the basic Sequential Linear Programming (SLP) formulation as used by other SLP algorithms reported in the literature. Transmission loss minimization is used as the primary objective. A secondary feasibility improvement objective is used which results in better feasible solution in comparison with the loss minimization objective especially when the initial b

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Lenin, Kanagasabai. "Real power loss diminution by rain drop optimization algorithm." International Journal of Advances in Applied Sciences (IJAAS) 10, no. 2 (2021): 149–55. https://doi.org/10.11591/ijaas.v10.i2.pp149-155.

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In this work Rain Drop Optimization (RDO) Algorithm is projected to reduce power loss. Proceedings of Rain drop have been imitated to model the RDO algorithm. Natural action of rain drop is flowing downwards form the peak and it may form small streams during the headway from the mountain or hill. As by gravitation principle raindrop flow as stream then as river form the peak of mountains or hill then it reach the sea as global optimum. Proposed Rain Drop Optimization (RDO) Algorithm evaluated in IEEE 30, bus test system. Power loss reduction, voltage deviation minimization, and voltage stabili

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Kumar, Naveen, and Ramesh Kumar. "Optimal Reactive Power Dispatch by Success History Based Adaptive Differential Evolution Salp Swarm Algorithm." Asian Journal of Water, Environment and Pollution 19, no. 6 (2022): 11–18. http://dx.doi.org/10.3233/ajw220083.

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In this study, a novel hybrid algorithm success history-based adaptive differential evolution salp swarm algorithm (SHADE-SSA) is proposed to solve two different cases of IEEE 30 bus reactive power dispatch problems integrated with thermal generators, wind farms and solar photovoltaic plants. Real power loss minimization and voltage deviation minimization are considered as main objectives in the present work. The performance and robustness of the proposed hybrid SHADE-SSA algorithm are compared with the results of five different metaheuristic algorithms for the same test system and consider th

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Lenin, K. "Minimization of real power loss by enhanced teaching learning based optimization algorithm." IAES International Journal of Robotics and Automation (IJRA) 9, no. 1 (2020): 1. http://dx.doi.org/10.11591/ijra.v9i1.pp1-5.

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<p class="Abstract">This paper presents an Enhanced Teaching-Learning-Based Optimization (ETLBO) algorithm for solving reactive power flow problem. Basic Teaching-Learning-Based Optimization (TLBO) is reliable, accurate and vigorous for solving the optimization problems. Also it has been found that TLBO algorithm slow in convergence due to its high concentration in the accuracy. This paper presents an, enhanced version of TLBO algorithm, called as enhanced Teaching-Learning-Based Optimization (ETLBO). A parameter called as “weight” has been included in the fundamental TLBO equations &amp

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Kanagasabai, Lenin. "Real power loss diminution by rain drop optimization algorithm." International Journal of Advances in Applied Sciences 10, no. 2 (2021): 149. http://dx.doi.org/10.11591/ijaas.v10.i2.pp149-155.

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<p>In this work Rain Drop Optimization (RDO) Algorithm is projected to reduce power loss. Proceedings of Rain drop have been imitated to model the RDO algorithm. Natural action of rain drop is flowing downwardsform the peak and it may form small streams during the headway from the mountain or hill. As by gravitation principle raindrop flow as stream then as river form the peak of mountains or hill then it reach the sea as global optimum. Proposed Rain Drop Optimization (RDO) Algorithm evaluated in IEEE 30, bus test system. Power loss reduction, voltage deviation minimization, and voltage

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Kumar, Pramod, Nagendra Kumar Swarnkar, Om Prakash Mahela, et al. "Optimal Sizing and Deployment of Renewable Energy Generators in Practical Transmission Network Using Grid-Oriented Multiobjective Harmony Search Algorithm for Loss Reduction and Voltage Profile Improvements." International Transactions on Electrical Energy Systems 2023 (March 22, 2023): 1–19. http://dx.doi.org/10.1155/2023/6315918.

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This paper presents grid-oriented multiobjective harmony search algorithm (GOMOHSA) to incorporate the multiple grid parameters for minimization of the active power loss, reactive power loss, and total voltage deviations (TVD) in a part of practical transmission network of Rajasthan Rajya Vidyut Prasaran Nigam Limited (RVPN) in southern parts of Rajasthan state of India. This is achieved by optimal deployment of optimally sized renewable energy (RE) generators using GOMOHSA. Performance indexes such as active power loss minimization index (APMLI), the reactive power loss minimization index (RP

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Le, Dung A., and Dieu N. Vo. "Cuckoo Search Algorithm for Minimization of Power Loss and Voltage Deviation." International Journal of Energy Optimization and Engineering 5, no. 1 (2016): 23–34. http://dx.doi.org/10.4018/ijeoe.2016010102.

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This paper proposes a cuckoo search algorithm (CSA) to solve the optimal reactive power dispatch (ORPD) problem in power system operation considering the power loss and voltage deviation. The proposed CSA is a nature inspired algorithm from the cuckoo species laying their eggs in the nest of other species. There is a probability of the host bird to discover the alien eggs in its nest and the host bird either destroys the strange egg or simply ignores the host and builds a new one. The advantages of the CSA method are few control parameters and high optimal solution quality. The proposed method

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Lenin, K. "Minimization of real power loss by enhanced teaching learning based optimization algorithm." IAES International Journal of Robotics and Automation (IJRA) 9, no. 1 (2020): 1–5. https://doi.org/10.11591/ijra.v9i1.pp1-5.

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This paper presents an Enhanced Teaching-Learning-Based Optimization (ETLBO) algorithm for solving reactive power flow problem. Teaching-learning process is an iterative process where in the continuous interaction takes place for the transfer of knowledge. Movements of trial solutions will investigate the internally final stages. Up gradation of the algorithm has been done through by adding weight in the learner values. Projected ETLBO algorithm has been tested in standard IEEE 57,118 bus systems and power loss has been reduced efficiently.

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Et. al., N. Karuppiah,. "Optimal siting and sizing of multiple type DGs for the performance enhancement of Distribution System using Differential Evolution Algorithm." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (2021): 1140–46. http://dx.doi.org/10.17762/turcomat.v12i2.1135.

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The necessity of Distributed Generation (DG) in the modern power system has increased greatly. Optimal placement and sizing of DGs have a significant impact on the objectives of voltage stability enhancement, real and reactive power loss minimization and power system security and reliability. Different types of DGs such as Type I, Type II, Type III and Type IVare placed. The optimal placement of these DGs is found using Voltage Stability Index (VSI). The optimal sizing of these DGs is done using Differential Evolution (DE) algorithm. MATLAB simulation is carried out in standard IEEE 33-bus tes

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Nur Azlin Ashiqin Mohd Amin, Siti Hafawati Jamaluddin, Nur Syuhada Muhammat Pazil, Norwaziah Mahmud, and Norhanisa Kimpol. "Minimizing Power Loss Using Modified Artificial Bee Colony Algorithm." Journal of Computing Research and Innovation 6, no. 2 (2021): 111–18. http://dx.doi.org/10.24191/jcrinn.v6i2.211.

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Electrical energy losses are found in any part of the power system. In the power system, it is essential to minimize the real power loss in transmission lines. The voltage deviation at the load buses through controlling the reactive power flow is very important. This ensures the secured operation of power systems regarding voltage stability and the economics of the process due to loss minimization. In this paper, the Modified Artificial Bee Colony (MABC) algorithm is implemented to solve the power system's optimal reactive power flow problem. Generator bus voltages, transformer tap positions,

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Lenin, Kanagasabai. "Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm for Solving Optimal Reactive Power Dispatch Problem." Journal of Applied Science, Engineering, Technology, and Education 3, no. 1 (2020): 12–21. http://dx.doi.org/10.35877/454ri.asci31106.

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In this work Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm (HGPSOS) has been done for solving the power dispatch problem. Genetic particle swarm optimization problem has been hybridized with Symbiotic organisms search (SOS) algorithm to solve the problem. Genetic particle swarm optimization algorithm is formed by combining the Particle swarm optimization algorithm (PSO) with genetic algorithm (GA). Symbiotic organisms search algorithm is based on the actions between two different organisms in the ecosystem- mutualism, commensalism and

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Reddy, A. V. Sudhakara, M. Damodar Reddy, and M. Satish Kumar Reddy. "Network Reconfiguration of Primary Distribution System Using GWO Algorithm." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 6 (2017): 3226. http://dx.doi.org/10.11591/ijece.v7i6.pp3226-3234.

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This manuscript presents a feeder reconfiguration in primary distribution networks with an objective of minimizing the real power loss or maximization of power loss reduction. An optimal switching for the network reconfiguration problem is introduced in this article based on step by step switching and simultaneous switching. This paper proposes a Grey Wolf Optimization (GWO) algorithm to solve the feeder reconfiguration problem through fitness function corresponding to optimum combination of switches in power distribution systems. The objective function is formulated to solve the reconfigurati

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