Enhanced Symbiotic Organisms Search and Hydrological Cycle Algorithms for Real Power Loss Diminution and Voltage Stability Enhancement

2022 ◽  
pp. 175-206
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Hydrological Cycle ◽  
Search Algorithm ◽  
Symbiotic Organisms Search ◽  
Roulette Wheel Selection ◽  
Voltage Stability Enhancement ◽  
Water Drops ◽  
Stability Enhancement ◽  
Symbiotic Organisms

In this chapter, enhanced symbiotic organisms search (ESOS) algorithm and hydrological cycle (HC) algorithm are projected to solve factual power loss lessening problem. Symbiotic search algorithm is based on the actions between two different organisms in the ecosystem: mutualism, commensalism, and parasitism. Exploration procedure has been initiated arbitrarily, and each organism indicates a solution with fitness value. Quasi-oppositional-based learning and chaotic local search have been applied to augment the performance of the algorithm. In this work, hydrological cycle (HC) algorithm has been utilized to solve the optimal reactive power problem. It imitates the circulation of water form land to sky and vice versa. Only definite number of water droplets is chosen for evaporation, and it is done through roulette-wheel selection method. In the condensation stage, water drops move closer, combine, and also collusion occurs as the temperature decreases.

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 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.

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