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All Journal IAES International Journal of Robotics and Automation (IJRA) 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

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

Published : 21 Documents Claim Missing Document

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Articles

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Solving optimal reactive power problem by enhanced fruit fly optimization algorithm and status of material algorithm 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 enhanced fruit fly optimization algorithm (EFF) and status of material algorithm (SMA) to solve the optimal reactive power problem. Fruit fly optimization algorithm is based on the food finding behavior of the fruit fly. There are two steps in food finding procedure of fruit fly: At first it smells the food source by means of osphresis organ and it flies in that direction; afterwards, when it gets closer to the food site, through its sensitive vision it will find the food. At the beginning of the run by diminishing the inertia weight from a large value to a small value, will lead to enhance the global search capability and more local search ability will be in process the end of the run of the EFF algorithm. Then SMA is projected to solve the problem. Three state of material are solid, liquid, and gas. For evolution procedure direction vector operator assign a direction to every molecule consecutively to guide the particle progression. Collision operator imitates the collisions factor in which molecules are interacting to each other. Proposed enhanced EFF, SMA has been tested in standard IEEE 30 bus test system and simulation results show the projected algorithms reduced the real power loss considerably.

Amplified and quantum based brain storm optimization algorithms for real power loss reduction Kanagasabai Lenin
International Journal of Applied Power Engineering (IJAPE) Vol 10, No 1: March 2021
Publisher : Institute of Advanced Engineering and Science

In this work amplified brain storm optimization (ABS) algorithm and quantum based brain storm (QBS) optimization algorithm is applied to solve the problem. A node is arbitrarily chosen from the graph as the preliminary point to form a Hamiltonian cycle. At generation t and t+1, Lt and Lt+1 are the length of Hamiltonian cycle correspondingly. In the QBS algorithm a Quantum state of an idea is illustrated by a wave function ( ⃗ ) as an alternative of the position modernized only in brain storm optimization algorithm. Monte Carlo simulation method is used, to measure the position for each idea from the quantum state to the traditional one. Proposed ABS algorithm and QBS optimization algorithm has been tested in standard IEEE 57 bus test system and real power loss reduced effectively.

Factual power loss lessening by synthetic supportive exploration algorithm Kanagasabai Lenin
International Journal of Applied Power Engineering (IJAPE) Vol 10, No 2: June 2021
Publisher : Institute of Advanced Engineering and Science

In this work an innovative synthetic supportive exploration (SSE) algorithm is utilized for solving optimal reactive power problem. Projected algorithm is based on communication between two simulated fabulous creatures as both of them intermingle and voyage to altered zones to find comprehensive minimum. In a definite zone according to the climate altering conditions amount of food can be found will be varied. Due to this reason, fabulous creatures develop seasonal exodus deeds to find out improved food sources. Earlier to exodus fabulous creatures will divide into subgroups in order to find an improved food source. Coordination of sub-groups will determine the performance of the search. Communication and exploration are the two key deeds of the fabulous creatures. Also, the two fabulous creatures make a decision on the marauder and prey by the sub fabulous creature. Proposed synthetic supportive exploration (SSE) algorithm has been tested in IEEE 14 and 300 bus systems. Real power loss power loss reduction achieved.

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.

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