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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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Articles

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Real power loss diminution by predestination of particles wavering search algorithm Kanagasabai Lenin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

In this work Predestination of Particles Wavering Search (PPS) algorithm has been applied to solve optimal reactive power problem. PPS algorithm has been modeled based on the motion of the particles in the exploration space. Normally the movement of the particle is based on gradient and swarming motion. Particles are permitted to progress in steady velocity in gradient-based progress, but when the outcome is poor when compared to previous upshot, immediately particle rapidity will be upturned with semi of the magnitude and it will help to reach local optimal solution and it is expressed as wavering movement. In standard IEEE 14, 30, 57,118,300 bus systems Proposed Predestination of Particles Wavering Search (PPS) algorithm is evaluated and simulation results show the PPS reduced the power loss efficiently.

Real power loss reduction by tundra wolf algorithm Kanagasabai Lenin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

In this work Tundra wolf algorithm (TWA) is proposed to solve the optimal reactive power problem. In the projected Tundra wolf algorithm (TWA) in order to avoid the searching agents from trapping into the local optimal the converging towards global optimal is divided based on two different conditions. In the proposed Tundra wolf algorithm (TWA) omega tundra wolf has been taken as searching agent as an alternative of indebted to pursue the first three most excellent candidates. Escalating the searching agents numbers will perk up the exploration capability of the Tundra wolf wolves in an extensive range. Proposed Tundra wolf algorithm (TWA) has been tested in standard IEEE 14, 30 bus test systems and simulation results show the proposed algorithm reduced the real power loss effectively.

Diminution of real power loss by novel gentoo penguin algorithm Kanagasabai Lenin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

In this paper Gentoo Penguin Algorithm (GPA) is proposed to solve optimal reactive power problem. Gentoo Penguins preliminary population possesses heat radiation and magnetizes each other by absorption coefficient. Gentoo Penguins will move towards further penguins which possesses low cost (elevated heat concentration) of absorption. Cost is defined by the heat concentration, distance. Gentoo Penguins penguin attraction value is calculated by the amount of heat prevailed between two Gentoo penguins. Gentoo Penguins heat radiation is measured as linear. Less heat is received in longer distance, in little distance, huge heat is received. Gentoo Penguin Algorithm has been tested in standard IEEE 57 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.

Enhanced wormhole optimizer algorithm for solving optimal reactive power problem Kanagasabai Lenin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

In this paper Enhanced Wormhole Optimizer (EWO) algorithm is used to solve optimal reactive power problem. Proposed algorithm based on the Wormholes which exploits the exploration space. Between different universes objects are exchanged through white or black hole tunnels. Regardless of the inflation rate, through wormholes objects in all universes which possess high probability will shift to the most excellent universe. In the projected Enhanced Wormhole Optimizer (EWO) algorithm in order to avoid the solution to be get trapped into the local optimal solution Levy flight has been applied. Projected Enhanced Wormhole Optimizer (EWO) algorithm has been tested in standard IEEE 14, 30, 57,118,300 bus test systems and simulation results show that the EWO algorithm reduced the real power loss efficiently.

Power loss reduction by gryllidae optimization algorithm Kanagasabai Lenin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

This paper projects Gryllidae Optimization Algorithm (GOA) has been applied to solve optimal reactive power problem. Proposed GOA approach is based on the chirping characteristics of Gryllidae. In common, male Gryllidae chirp, on the other hand some female Gryllidae also do as well. Male Gryllidae draw the females by this sound which they produce. Moreover, they caution the other Gryllidae against dangers with this sound. The hearing organs of the Gryllidae are housed in an expansion of their forelegs. Through this, they bias to the produced fluttering sounds. Proposed Gryllidae Optimization Algorithm (GOA) has been tested in standard IEEE 14, 30 bus test systems and simulation results show that the projected algorithms reduced the real power loss considerably.

True power loss reduction by augmented mine blast algorithm Kanagasabai Lenin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 2: August 2020
Publisher : Institute of Advanced Engineering and Science

In this paper, Mine Blast Algorithm (MBA) has been intermingled with Harmony Search (HS) algorithm for solving optimal reactive power dispatch problem. MBA is based on explosion of landmines and HS is based on Creativeness progression of musicians – both are hybridized to solve the problem. In MBA Initial distance of shrapnel pieces are reduced gradually to allow the mine bombs search the probable global minimum location in order to amplify the global explore capability. Harmony search (HS) imitates the music creativity process where the musicians supervise their instruments’ pitch by searching for a best state of harmony. Hybridization of Mine Blast Algorithm with Harmony Search algorithm (MH) improves the search effectively in the solution space. Mine blast algorithm improves the exploration and harmony search algorithm augments the exploitation. At first the proposed algorithm starts with exploration & gradually it moves to the phase of exploitation. Proposed Hybridized Mine Blast Algorithm with Harmony Search algorithm (MH) has been tested on standard IEEE 14, 300 bus test systems. Real power loss has been reduced considerably by the proposed algorithm. Then Hybridized Mine Blast Algorithm with Harmony Search algorithm (MH) tested in IEEE 30, bus system (with considering voltage stability index)- real power loss minimization, voltage deviation minimization, and voltage stability index enhancement has been attained.

Enhanced whale optimization algorithm for active power loss diminution Kanagasabai Lenin
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 9, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

In this paper Enhanced whale Optimization Algorithm (EWO) proposed to solve the optimal reactive power problem. Whale optimization algorithm is modeled by Bubble-net hunting tactic. In the projected optimization algorithm an inertia weight ω ∈ [1, 0] has been introduced to perk up the search ability. Whales are commonly moving 10-16 meters down then through the bubbles which are created artificially then they encircle the prey and move upward towards the surface of sea. Proposed Enhanced whale optimization algorithm (EWO) is tested in standard IEEE 57 bus systems and power loss reduced considerably.

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.

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