scholarly journals Real power loss diminution by rain drop optimization algorithm

2021 ◽  
Vol 10 (2) ◽  
pp. 149
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Power Loss ◽  
Test System ◽  
Global Optimum ◽  
Loss Reduction ◽  
Natural Action ◽  
Small Streams ◽  
Power Loss Reduction ◽  
Rain Drop ◽  
Voltage Deviation ◽  
System Power

<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 stability improvementhas been achieved</p>

scholarly journals Recloser-Fuse settings in distribution systems with optimizing multiple distributed generation considering technical aspects

2020 ◽  
Vol 17 (3) ◽  
pp. 1135
Author(s):  
Ahmed Mohamed Abdelbaset ◽  
AboulFotouh A. Mohamed ◽  
Essam Abou El-Zahab ◽  
M. A. Moustafa Hassan
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Test System ◽  
Optimal Size ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
System Power

<p><span>With the widespread of using distributed generation, the connection of DGs in the distribution system causes miscoordination between protective devices. This paper introduces the problems associated with recloser fuse miscoordination (RFM) in the presence of single and multiple DG in a radial distribution system. Two Multi objective optimization problems are presented. The first is based on technical impacts to determine the optimal size and location of DG considering system power loss reduction and enhancement the voltage profile with a certain constraints and the second is used for minimizing the operating time of all fuses and recloser with obtaining the optimum settings of fuse recloser coordination characteristics. Whale Optimizer algorithm (WOA) emulated RFM as an optimization problem. The performance of the proposed methodology is applied to the standard IEEE 33 node test system. The results show the robustness of the proposed algorithm for solving the RFM problem with achieving system power loss reduction and voltage profile enhancement.</span></p>

Real Power Loss Reduction by Cinnamon ibon Search Optimization Algorithm

2021 ◽  
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Search Algorithm ◽  
Loss Reduction ◽  
Real Power ◽  
Search Optimization ◽  
Power Loss Reduction ◽  
Voltage Stability Enhancement ◽  
Voltage Deviation ◽  
Stability Enhancement

In this paper Cinnamon ibon Search Optimization Algorithm (CSOA) is used for solving the power loss lessening problem. Key objectives of the paper are Real power Loss reduction, Voltage stability enhancement and minimization of Voltage deviation. Searching and scavenging behavior of Cinnamon ibon has been imitated to model the algorithm. Cinnamon ibon birds which are in supremacy of the group are trustworthy to be hunted by predators and dependably attempt to achieve a improved position and the Cinnamon ibon ones that are positioned in the inner of the population, drive adjacent to the nearer populations to dodge the threat of being confronted. The systematic model of the Cinnamon ibon search Algorithm originates with an arbitrary individual of Cinnamon ibon. The Cinnamon ibon search algorithm entities show the position of the Cinnamon ibon. Besides, the Cinnamon ibon bird is supple in using the cooperating plans and it alternates between the fabricator and the cadger. Successively the Cinnamon ibon identifies the predator position; then they charm the others by tweeting signs. The cadgers would be focussed to the imperilled regions by fabricators once the fear cost is more than the defence threshold. Likewise, the subterfuge of both the cadger and the fabricator is commonly used by Cinnamon ibon. The dispersion of the Cinnamon ibon location in the solution area is capricious. An impulsive drive approach was applied when dispossession of any adjacent Cinnamon ibon in the purlieu of the present population. This style diminishes the convergence tendency and decreases the convergence inexorableness grounded on the controlled sum of iterations. Authenticity of the Cinnamon ibon Search Optimization Algorithm (CSOA) is corroborated in IEEE 30 bus system (with and devoid of L-index). Genuine power loss lessening is attained. Proportion of actual power loss lessening is amplified.

scholarly journals Enhanced sunflower optimization for placement distributed generation in distribution system

2021 ◽  
Vol 11 (1) ◽  
pp. 107
Author(s):  
Thuan Thanh Nguyen
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Optimization Problem ◽  
Test System ◽  
Loss Reduction ◽  
Power Loss Reduction ◽  
Distribution Generation

Installation of distribution generation (DG) in the distribution system gains many technical benefits. To obtain more benefits, the location and size of DG must be selected with the appropriate values. This paper presents a method for optimizing location and size of DG in the distribution system based on enhanced sunflower optimization (ESFO) to minimize power loss of the system. In which, based on the operational mechanisms of the original sunflower optimization (SFO), a mutation technique is added for updating the best plant. The calculated results on the 33 nodes test system have shown that ESFO has proficiency for determining the best location and size of DG with higher quality than SFO. The compared results with the previous methods have also shown that ESFO outperforms to other methods in term of power loss reduction. As a result, ESFO is a reliable approach for the DG optimization problem.

scholarly journals Real power loss reduction by dolphin swarm algorithm

2019 ◽  
Vol 8 (4) ◽  
pp. 285
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
Loss Reduction ◽  
Real Power ◽  
Power Loss Reduction ◽  
Spinner Dolphin ◽  
Simulation Results ◽  
Swarm Algorithm ◽  
Power Problem

<p>In this work Spinner Dolphin Swarm Algorithm (SDSA) has been applied to solve the optimal reactive power problem. Dolphins have numerous remarkable natural distinctiveness and living behavior such as echolocation, information interactions, collaboration, and partition of labor. Merging these natural distinctiveness and living behavior with swarm intelligence has been modeled to solve the reactive power problem. Proposed Spinner Dolphin Swarm Algorithm (SDSA) has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss extensively.</p>

scholarly journals Power loss reduction by chaotic based predator-prey brain storm optimization algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 218
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
Local Optimum ◽  
Loss Reduction ◽  
Optimal Parameters ◽  
Predator Prey ◽  
Brain Storm Optimization ◽  
Power Loss Reduction ◽  
Power Problem

<div data-canvas-width="34.43688268494255">In this paper chaotic predator-prey brain storm optimization (CPB) algorithm is proposed to solve optimal reactive power problem. In this work predator-prey brain storm optimization position cluster centers to perform as predators, consequently it will move towards better and better positions, while the remaining ideas perform as preys; hence get away from their adjacent predators. In the projected CPB algorithm chaotic theory has been applied in the modeling of the algorithm. In the proposed algorithm main properties of chaotic such as ergodicity and irregularity used to make the algorithm to jump out of the local optimum as well as to determine optimal parameters CPB algorithm has been tested in standard IEEE 57 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.</div>

scholarly journals A Hybrid Optimization Approach for Power Loss Reduction and DG Penetration Level Increment in Electrical Distribution Network

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6008
Author(s):  
Teketay Mulu Beza ◽  
Yen-Chih Huang ◽  
Cheng-Chien Kuo
Keyword(s):  
Power Loss ◽  
Distribution Network ◽  
Distribution Networks ◽  
Test System ◽  
Base Case ◽  
Optimization Approach ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Electrical Distribution ◽  
Power Loss Reduction

The electrical distribution system has experienced a number of important changes due to the integration of distributed and renewable energy resources. Optimal integration of distributed generators (DGs) and distribution network reconfiguration (DNR) of the radial network have significant impacts on the power system. The main aim of this study is to optimize the power loss reduction and DG penetration level increment while keeping the voltage profile improvements with in the permissible limit. To do so, a hybrid of analytical approach and particle swarm optimization (PSO) are proposed. The proposed approach was tested on 33-bus and 69-bus distribution networks, and significant improvements in power loss reduction, DG penetration increment, and voltage profile were achieved. Compared with the base case scenario, power loss was reduced by 89.76% and the DG penetration level was increased by 81.59% in the 69-bus test system. Similarly, a power loss reduction of 82.13% and DG penetration level increment of 80.55% was attained for the 33-bus test system. The simulation results obtained are compared with other methods published in the literature.

scholarly journals Power loss reduction by arctic wolf optimization algorithm

2019 ◽  
Vol 8 (3) ◽  
pp. 111
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
The Arctic ◽  
Gray Wolf ◽  
Loss Reduction ◽  
Power Loss Reduction ◽  
Average Size ◽  
Power Problem ◽  
North Western

This paper proposes Arctic Wolf optimization (AWO) algorithm to solve the optimal reactive power problem. Deeds of the Arctic wolf have been imitated to formulate the proposed algorithm. Arctic wolf also identified as the white wolf or polar wolf is a breed of gray wolf inhabitant from Melville Island to Ellesmere Island. It is average size, very smaller when compared to north western wolf, it possess whiter coloration, narrower braincase and big carnassials. Particle swarm optimization, Genetic algorithm has been used to improve the Exploration &amp; Exploitation ability of the algorithm by utilizes flag vector &amp; position, velocity update properties. Proposed Arctic Wolf optimization (AWO) algorithm has been tested in standard IEEE 30 bus test system and simulation results show the projected algorithms reduced the real power loss considerably.

scholarly journals TRUE POWER LOSS REDUCTION BY WOLF OPTIMIZATION ALGORITHM

2018 ◽  
Vol 6 (11) ◽  
pp. 323-329
Author(s):  
K. Lenin
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
Loss Reduction ◽  
Power Losses ◽  
Swarm Optimization ◽  
Power Loss Reduction ◽  
Solution Efficiency ◽  
Power Problem

In this paper wolf optimization algorithm (WOA) has been applied for solving reactive power problem. In order to enhance the search procedure the basic qualities of particle swarm optimization has been intermingled to improve the capability of the search to reach a global solution. Efficiency of the projected wolf optimization algorithm (WOA) is tested in standard IEEE 30 bus test system. Simulation study indicates wolf optimization algorithm (WOA) performs well in tumbling the actual power losses& particularly voltage stability has been enriched.

scholarly journals TECHNO-ECONOMIC ASSESMENT FOR DISTRIBUTED GENERATION PLACEMENT IN DISTRIBUTION SYSTEM

KURVATEK ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 1-6
Author(s):  
Sugiarto Kadiman
Keyword(s):  
Distributed Generation ◽  
Power Loss ◽  
Distribution Systems ◽  
Reactive Power ◽  
Test System ◽  
Optimal Placement ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
Reduction Index

This paper presents a proposed function which is known as techno-economic model for optimal placement of distributed generation (DG) resources in distribution systems in order to minimize the power losses and improve voltage profile. Combined sensitivity factors (CSF), such real power loss reduction index, reactive power loss reduction index, voltage profile improvement index, and life cycle cost, and particle swarm optimization (PSO) are applied to the proposed technique to obtain the best compromise between these costs. Simulation results on IEEE 14-bus test system are presented to demonstrate the usefulness of the proposed procedure.

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