scholarly journals Real Power Loss Reduction and Voltage Stability Enhancement by Stock Exchange, Product Demand-Availability, Affluent and Penurious Algorithms

2020 ◽  
Vol 14 (2) ◽  
pp. 165
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Power Loss ◽  
Voltage Stability ◽  
Stock Exchange ◽  
Loss Reduction ◽  
Real Power ◽  
Product Demand ◽  
Exchange Product ◽  
Power Loss Reduction ◽  
Voltage Stability Enhancement ◽  
Stability Enhancement

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 Self-Adaptive Firefly-Algorithm-Based Unified Power Flow Controller Placement with Single Objectives

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Selvarasu Ranganathan ◽  
S. Rajkumar
Keyword(s):  
Power Loss ◽  
Power Flow ◽  
Unified Power Flow Controller ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Loss Reduction ◽  
Voltage Stability Enhancement ◽  
Stability Enhancement ◽  
Power Flow Controller ◽  
Voltage Profile Improvement

The selection of positions for unified power flow controller (UPFC) placement in transmission network is an essential factor, which aids in operating the system in a more reliable and secured manner. This paper focuses on strengthening the power system performance through UPFC placement employing self-adaptive firefly algorithm (SAFA), which selects the best positions along with parameters for UPFC placement. Three single objectives of real power loss reduction, voltage profile improvement, and voltage stability enhancement are considered in this work. IEEE 14, 30, and 57 test systems are selected to accomplish the simulations and to reveal the efficacy of the proposed SAFA approach; besides, solutions are compared with two other algorithms solutions of honey bee algorithm (HBA) and bacterial foraging algorithm (BFA). The proposed SAFA contributes real power loss reduction, voltage profile improvement, and voltage stability enhancement by optimally choosing the placement for UPFC.

Real Power Loss Reduction by Billfish and Red Mullet Optimization Algorithms

2021 ◽  
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Power Loss ◽  
Voltage Stability ◽  
Reactive Power ◽  
Smart Cities ◽  
Fitness Function ◽  
Loss Reduction ◽  
Real Power ◽  
Red Mullet ◽  
Power Loss Reduction ◽  
Continuous Power

In this paper Billfish Optimization Algorithm (BOA) and Red Mullet Optimization (RMO) Algorithm has been designed for voltage stability enhancement and power loss reduction. Electrical Power is one among vital need in the society and also it plays lead role in formation of smart cities. Continuous power supply is essential and mainly quality of the power should be maintained in good mode. In this work real power loss reduction is key objective. Natural hunting actions of Billfish over pilchards are utilized to model the algorithm. Candidate solutions in the projected algorithm are Billfish and population in the exploration space is arbitrarily engendered. Movement of Billfish is high, it will attack the pilchards vigorously and it can’t escape from the attack done by the group of Billfish. Then in this paper Red Mullet Optimization (RMO) Algorithm is proposed to solve optimal reactive power problem. Projected RMO algorithm modeled based on the behavior and characteristics of red mullet. As a group they hunt for the prey and in each group there will be chaser and blocker. When the prey approaches any one of the blocker red mullet then automatically it will turn as new chaser. So roles will interchangeable and very much flexible. At any time chaser will become blocker and any of the blocker will become a chaser with respect to prey position and conditions. Then in that particular area when all the preys are hunted completed then red mullet group will change the area. So there will be flexibility and changing the role quickly with respect to prey position. Alike to that with reference to the fitness function the particle will be chosen as chaser. By means of considering L (voltage stability) - index BOA, and RMO algorithms verified in IEEE 30- bus system. Then without L-index BOA and RMO algorithms is appraised in 30 bus test systems. Both BOA and RMO algorithms condensed the power loss proficiently with improvement in voltage stability and minimization of voltage deviation.

scholarly journals REDUCTION OF REAL POWER LOSS AND VOLTAGE STABILITY ENHANCEMENT BY SALMO SALAR ALGORITHM

2017 ◽  
Vol 5 (5) ◽  
pp. 349-360
Author(s):  
K. Lenin
Keyword(s):  
Salmo Salar ◽  
Power Loss ◽  
Voltage Stability ◽  
Reactive Power ◽  
Test System ◽  
Real Power ◽  
The North ◽  
Optimal Reactive Power Dispatch ◽  
Voltage Stability Enhancement ◽  
Stability Enhancement

This paper presents a new Salmo Salar (SS) algorithm for Solving Optimal Reactive Power Dispatch Problem. Salmo Salar Algorithm imitates the annual natural events happening in the North America. Millions of Salmo salar move about through mountain streams for spawning. Proposed SS algorithm utilizes the behaviour of Salmo Salar to solve the optimal reactive power problem. Proposed (SS) algorithm has been tested in standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm in reducing the real power loss and enhancing the voltage stability.

scholarly journals FCC Algorithm for Power Loss Diminution

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
L. Kanagasabai
Keyword(s):  
Power Loss ◽  
Voltage Stability ◽  
Fitness Function ◽  
Stability Index ◽  
Training Procedure ◽  
Power Loss Reduction ◽  
Lower Division ◽  
Voltage Stability Enhancement ◽  
Voltage Deviation ◽  
Stability Enhancement

In this work, the FCC algorithm has been applied to the power problem. Real power loss reduction, voltage deviation minimization, and voltage stability enhancement are the key objectives of the proposed work. The proposed FCC algorithm has been modeled based on the competition, communication among teams, and training procedure within the team. The solution has been created based on the team, players, coach, and substitution tactic. A preliminary solution of the problem is produced, and the initialization of the teams depends on the team’s formation with substitute tactics. Mainly fitness function for each solution is computed, and it plays an imperative role in the process of the algorithm. With the performance in the season, promotion and demotion of the teams will be there. Most excellently performed teams will be promoted to a senior division championship, and the most poorly performed team will be demoted to the top lower division league. Ideas and tactics sharing procedure, repositioning procedure, Substitution procedure, seasonal transmit procedure, Promotion and demotion procedure of a team which plays in the confederation cup has been imitated to solve the problem. Similar to an artificial neural network, a learning phase is also applied in the projected algorithm to improve the quality of the solution. Modernization procedure employed sequentially to identify the best solution. With and without voltage stability (L-index) FCC algorithm is evaluated in IEEE 30, bus system. Then the Proposed FCC algorithm has been evaluated in standard IEEE 14, 57,118,300 bus test systems without L-index. Power loss minimization and voltage stability index improvement have been achieved with voltage deviation minimization.

scholarly journals Real power loss reduction by hyena optimizer algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 186
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Mathematical Modelling ◽  
Convergent Evolution ◽  
Power Loss ◽  
Social Relationship ◽  
Reactive Power ◽  
Scent Marking ◽  
Loss Reduction ◽  
Real Power ◽  
Power Loss Reduction ◽  
Power Problem

<p><span>To solve optimal reactive power problem this paper projects Hyena Optimizer (HO) algorithm and it inspired from the behaviour of Hyena. Collaborative behaviour &amp; Social relationship between Hyenas is the key conception in this algorithm. Hyenas a form of carnivoran mammal &amp; deeds are analogous to canines in several elements of convergent evolution. Hyenas catch the prey with their teeth rather than claws – possess hardened skin feet with large, blunt, no retractable claws are adapted for running and make sharp turns. However, the hyenas' grooming, scent marking, defecating habits, mating and parental behaviour are constant with the deeds of other feliforms. Mathematical modelling is formulated for the basic attributes of Hyena. Standard IEEE 14,300 bus test systems used to analyze the performance of Hyena Optimizer (HO) algorithm. Loss has been reduced with control variables are within the limits.</span></p>

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