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All Journal International Journal of Informatics and Communication Technology (IJ-ICT) International Journal of Applied Power Engineering (IJAPE) International Journal of Advances in Applied Sciences Indonesian Journal of Electrical Engineering and Informatics (IJEEI)

Kanagasabai Lenin

Prasad V. Potluri Siddhartha Institute of Technology

Author-ID : 2403313

Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Polar wolf optimization algorithm for solving optimal reactive power problem Kanagasabai Lenin
International Journal of Applied Power Engineering (IJAPE) Vol 9, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

This paper proposes polar wolf optimization (PWO) algorithm to solve the optimal reactive power problem. Proposed algorithm enthused from actions of polar wolves. Leader’s wolves which denoted as xα are accountable for taking judgment on hunting, resting place, time to awaken etc. second level is xβ those acts when there is need of substitute in first case. Then xγ be as final level of the wolves. In the modeling social hierarchy is developed to discover the most excellent solutions acquired so far. Then the encircling method is used to describe circle-shaped vicinity around every candidate solutions. In order to agents work in a binary space, the position modernized accordingly. Proposed PWO algorithm has been tested in standard IEEE 14, 30, 57,118,300 bus test systems and simulation results show the projected algorithms reduced the real power loss considerably.

Solving optimal reactive power problem by hurricane search optimization algorithm Kanagasabai Lenin
International Journal of Applied Power Engineering (IJAPE) Vol 10, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

In this paper proposed hurricane search optimization (HSO) algorithm is proposed to solve optimal reactive power problem. An upward motion of air is caused due to release of heat which creates a low-pressure zone and by the rotation of the earth that is set into spin. In this spiraling airflow when energy is high then hurricane is created. Projected HSO algorithm design is based on the examination of the horizontal wind structure in a hurricane and how the wind parcels the progression in the neighboring atmosphere. A mixture of wind models has been developed for past few years to Backtesting and to compute hurricane exterior wind fields. Proposed HSO algorithm has been tested in standard IEEE 30, 57bus test systems and simulation results show the projected algorithm reduced the real power loss considerably.

Partition of spaces based algorithm for reduction of real power loss Kanagasabai Lenin
International Journal of Applied Power Engineering (IJAPE) Vol 9, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

In this work partition of spaces algorithm is proposed to solve optimal reactive power problem. In this algorithm, for finding the finest outcome based on the concentration of elevated quality and capable points in specific area is considered. State space area are identified and divided into subspaces iteratively and search has been made more comprehensively. Performance of the proposed partition of spaces algorithm is evaluated in standard IEEE 118,300 bus systems and simulated outcome gives better results. Real power loss has been considerably reduced.

Power loss reduction by chaotic based predator-prey brain storm optimization algorithm Kanagasabai Lenin
International Journal of Applied Power Engineering (IJAPE) Vol 9, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

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.

Diminution of factual power loss by enhanced bacterial foraging optimization algorithm Kanagasabai Lenin
International Journal of Applied Power Engineering (IJAPE) Vol 9, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

This paper presents an enhanced bacterial foraging optimization (EBFO)algorithm for solving the optimal reactive power problem. Bacterial foraging optimization is based on foraging behaviour of Escherichia coli bacteria which present in the human intestine. Bacteria have inclination to congregate the nutrient-rich areas by an action called as Chemo taxis. The bacterial foraging process consists of four chronological methods i.e. chemo taxis, swarming and reproduction and elimination-dispersal. In this work rotation angle adaptively and incessantly modernized, which augment the diversity of the population and progress the global search capability. The quantum rotation gate is utilized for chemo taxis to modernize the state of chromosome projected EBFO algorithm has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss extensively.

Factual power loss reduction by enriched black hole algorithm Kanagasabai Lenin
International Journal of Applied Power Engineering (IJAPE) Vol 10, No 2: June 2021
Publisher : Institute of Advanced Engineering and Science

This paper presents enriched black hole algorithm (EBHA) for solving optimal reactive power problem. In this work black hole algorithm based on membrane computing is projected. In black hole algorithm evolution of the population is through pushing the candidates in the course of the most excellent candidate in iterations and black hole which swap with those in the search space. Membrane computing is also branded as P system and it has multisets of objects with evolution rules in the membrane structure. Membrane structure is alike ingrained tree of section that demarcate the areas, and root is labelled as skin. Chemical substances (multisets of objects) are there inside the section (membranes) of a cell and the chemical reactions (evolution rules) that take place within the cell. Proposed enriched black hole algorithm (EBHA) has been evaluated in IEEE 14,300 bus test system. Loss reduction achieved.

Solving optimal reactive power problem by improved variable mesh optimization algorithm Kanagasabai Lenin
International Journal of Advances in Applied Sciences Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

In this work Improved Variable Mesh Optimization Algorithm (IVM) has been applied to solve the optimal reactive power problem. Projected Improved VMO algorithm has been modeled by hybridization of Variable mesh optimization algorithm with Clearing-Based Niche Formation Technique, Differential Evolution (DE) algorithm. Mesh formation and exploration has been enhanced by the hybridization. Amongst of niche development process, clearing is a renowned method in which general denominator is the formation of steady subpopulations (niches) at all local optima (peaks) in the exploration space. In Differential Evolution (DE) population is formed by common sampling within the stipulated smallest amount and maximum bounds. Subsequently DE travel into the iteration process where the progressions like, mutation, crossover, and selection, are followed. Proposed Improved Variable Mesh Optimization Algorithm (IVM) has been tested in standard IEEE 14,300 bus test system and simulationresults show the projected algorithm reduced the real power loss extensively.

Real power loss reduction by dolphin swarm algorithm Kanagasabai Lenin
International Journal of Advances in Applied Sciences Vol 8, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

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.

Active power loss reduction by opposition based kidney search algorithm Kanagasabai Lenin
International Journal of Advances in Applied Sciences Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

In this work Opposition based Kidney Search Algorithm (OKS) is used to solve the optimal reactive power problem. Kidney search algorithm imitates the various sequences of functions done by biological kidney. Opposition based learning (OBL) stratagem is engaged to commence the algorithm. This is to make certain high-quality of preliminary population and to expand the exploration steps in case of stagnation of the most excellent solutions. Opposition based learning (OBL) is one of the influential optimization tools to boost the convergence speed of different optimization techniques. The thriving implementation of the OBL engages evaluation of opposite population and existing population in the similar generation to discover the superior candidate solution of a given reactive power problem. Proposed Opposition based Kidney Search Algorithm (OKS) has been tested in standard IEEE 14, 30, 57,118,300 bus test systems and simulation results show that the proposed algorithm reduced the real power loss efficiently.

Embellished Particle Swarm Optimization Algorithm for Solving Reactive Power Problem Kanagasabai Lenin
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 5, No 3: September 2017
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v5i3.291

This paper proposes Embellished Particle Swarm Optimization (EPSO) algorithm for solving reactive power problem .The main concept of Embellished Particle Swarm Optimization is to extend the single population PSO to the interacting multi-swarm model. Through this multi-swarm cooperative approach, diversity in the whole swarm community can be upheld. Concurrently, the swarm-to-swarm mechanism drastically speeds up the swarm community to converge to the global near optimum. In order to evaluate the performance of the proposed algorithm, it has been tested in standard IEEE 57,118 bus systems and results show that Embellished Particle Swarm Optimization (EPSO) is more efficient in reducing the Real power losses when compared to other standard reported algorithms.

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