scholarly journals TRUE POWER LOSS REDUCTION BY HARMONY SEARCH ALGORITHM

2018 ◽  
Vol 6 (9) ◽  
pp. 196-205
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Search Algorithm ◽  
Harmony Search ◽  
Population Based ◽  
Test System ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
Real Power ◽  
Power Loss Reduction

This paper presents Harmony Search algorithm (HS) for solving the reactive power problem.  Real power loss minimization is the major objective & also voltage profiles are should be kept within the limits.  This paper introduces a new search model the harmony search (HS) algorithm is a relatively new population-based metaheuristic optimization algorithm. It emulates the music improvisation progression where musicians improvise their instruments’ pitch by searching for a perfect state of harmony. In order to evaluate the efficiency of the proposed algorithm, it has been tested on practical 191 test system & real power loss has been considerably reduced.

scholarly journals True power loss reduction by augmented mine blast algorithm

2020 ◽  
Vol 9 (2) ◽  
pp. 83
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Power Loss ◽  
Voltage Stability ◽  
Search Algorithm ◽  
Harmony Search ◽  
Stability Index ◽  
Harmony Search Algorithm ◽  
Real Power ◽  
Voltage Stability Index ◽  
Mine Blast Algorithm ◽  
Power Loss Reduction

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.

scholarly journals Voltage and Frequency Based Optimal Load Shedding using Improved Self Adaptive Harmony Search Algorithm

2019 ◽  
Vol 8 (11) ◽  
pp. 475-480
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Search Algorithm ◽  
Harmony Search ◽  
Stability Index ◽  
Harmony Search Algorithm ◽  
Rate Of Change ◽  
Load Shedding ◽  
Voltage Dependent ◽  
Self Adaptive

This study presents, two load shedding scheme that are simulated on IEEE-14 bus systems are voltage dependent priority based approach and voltage and frequency based NVSI methods. The frequency-based method is designed to consider the rate of change of frequency to estimate the power loss and thereby trigger the load shedding when the frequency or rate of change of frequency exceeds the corresponding thresholds. A novel method voltage and frequency-based load shedding scheme is designed to estimate the real and reactive power losses using frequency. After estimating the power loss, the buses are indexed using the Novel Voltage Stability Index (NVSI) to select the load buses for load shedding. The loads to be shed at each of the buses are determined using the improved self adaptive harmony search(ISAHS) algorithm. Simulation results of voltage and frequency based NVSI method are presented in comparison with voltage dependent priority based approach.

scholarly journals Real power loss reduction by dolphin swarm algorithm

2019 ◽  
Vol 8 (4) ◽  
pp. 285
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
Loss Reduction ◽  
Real Power ◽  
Power Loss Reduction ◽  
Spinner Dolphin ◽  
Simulation Results ◽  
Swarm Algorithm ◽  
Power Problem

<p>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.</p>

scholarly journals Real power loss reduction by arctic char algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 261
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
Arctic Char ◽  
The Arctic ◽  
Real Power ◽  
Power Loss Reduction ◽  
Evolutionary Operators ◽  
Stochastic Mode ◽  
Power Problem

<span lang="IN">This </span><span>work presents Arctic Char </span><span lang="EN-GB">Algorithm (ACA) for solving optimal reactive power problem.</span><span> In North America movement of Arctic char phenomenon is one among the twelve-monthly innate actions. Deeds of Arctic char have been imitated to design the algorithm. In stochastic mode solutions are initialized with one segment on every side of to the route ascendancy; particularly in between lower bound and upper bounds. Previous to the movement, Arctic char come to a decision about the passageway based on their perception. This implies stochastic mix up of control parameters to push the Arctic char groups (preliminary solution) in mutual pathway (evolutionary operators). Projected Arctic Char </span><span lang="EN-GB">Algorithm (ACA) </span><span>has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss extensively.</span>

Harmony Search Algorithm and its Variants

2015 ◽  
Vol 29 (08) ◽  
pp. 1539001 ◽  
Author(s):  
Nazmul Siddique ◽  
Hojjat Adeli
Keyword(s):  
Heuristic Search ◽  
Optimization Problem ◽  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Population Based ◽  
Harmony Search Algorithm ◽  
Perfect State ◽  
The Past

In the past three decades nature-inspired and meta-heuristic algorithms have dominated the literature in the broad areas of search and optimization. Harmony search algorithm (HSA) is a music-inspired population-based meta-heuristic search and optimization algorithm. The concept behind the algorithm is to find a perfect state of harmony determined by aesthetic estimation. This paper starts with an overview of the harmonic phenomenon in music and music improvisation used by musicians and how it is applied to the optimization problem. The concept of harmony memory and its mathematical implementation are introduced. A review of HSA and its variants is presented. Guidelines from the literature on the choice of parameters used in HSA for effective solution of optimization problems are summarized.

scholarly journals REDUCTION OF ACTIVE POWER LOSS BY COYOTE SEARCH ALGORITHM

2018 ◽  
Vol 6 (10) ◽  
pp. 130-138
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Search Algorithm ◽  
Special Property ◽  
Test System ◽  
Active Power ◽  
Real Power ◽  
Simulation Results ◽  
Searching Ability ◽  
Power Problem

This paper presents Coyote Search Algorithm (CSA) for solving optimal reactive power problem. Coyote Search Algorithm is a new bio – inspired heuristic algorithm which based on coyote preying behaviour. The way coyote search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power problem. And the specialty of coyote is possessing both individual local searching ability & autonomous flocking movement and this special property has been utilized to formulate the search algorithm. The proposed Coyote Search Algorithm (CSA) has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the good performance of the proposed algorithm in reducing the real power loss.

scholarly journals Amplified and quantum based brain storm optimization algorithms for real power loss reduction

2021 ◽  
Vol 10 (1) ◽  
pp. 21
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Quantum State ◽  
Optimization Algorithm ◽  
Power Loss ◽  
Hamiltonian Cycle ◽  
Reactive Power ◽  
Test System ◽  
Real Power ◽  
Brain Storm Optimization ◽  
Power Loss Reduction ◽  
Abs Algorithm

In this work Amplified Brain Storm Optimization (ABS) algorithm and Quantum based Brain Storm (QBS) Optimization Algorithm is used for solving optimal reactive power problem. In the projected amplified Brain storm optimization algorithm Hamiltonian cycle has been applied to improve the search abilities and also to avoid of trap in local optimal solution. A node is arbitrarily chosen from the graph as the preliminary point to form a Hamiltonian cycle. At generation t and t+1, L<sub>t</sub> and L<sub>t</sub><sub>+1</sub> 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<em> </em>is used, to measure the position for each idea from the<em> </em>quantum state to the traditional one. Proposed Amplified Brain Storm Optimization (ABS) algorithm and Quantum based Brain Storm (QBS) Optimization Algorithm has been tested in standard IEEE 57 bus test system and simulation results show the projected algorithms reduced the real power loss effectively.

Factual Power Loss Diminution by Enhanced Frog Leaping Algorithm

2020 ◽  
Vol 3 (2) ◽  
pp. 114-118
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Local Search ◽  
Power Loss ◽  
Reactive Power ◽  
Test System ◽  
Premature Convergence ◽  
Speed Of Convergence ◽  
Real Power ◽  
The Real ◽  
Simulation Results ◽  
Power Problem

This paper proposes Enhanced Frog Leaping Algorithm (EFLA) to solve the optimal reactive power problem. Frog leaping algorithm (FLA) replicates the procedure of frogs passing though the wetland and foraging deeds. Set of virtual frogs alienated into numerous groups known as “memeplexes”. Frog’s position’s turn out to be closer in every memeplex after few optimization runs and certainly, this crisis direct to premature convergence. In the proposed Enhanced Frog Leaping Algorithm (EFLA) the most excellent frog information is used to augment the local search in each memeplex and initiate to the exploration bound acceleration. To advance the speed of convergence two acceleration factors are introduced in the exploration plan formulation. Proposed Enhanced Frog Leaping Algorithm (EFLA) has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.

scholarly journals ACTIVE POWER LOSS REDUCTION BY FLOWER POLLINATION ALGORITHM

2020 ◽  
Vol 5 (12) ◽  
pp. 223-231
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Biological Evolution ◽  
Point Of View ◽  
Flower Pollination Algorithm ◽  
Real Power ◽  
Flower Pollination ◽  
Power Loss Reduction ◽  
Nature Inspired Algorithm ◽  
Survival Of The Fittest

This paper presents Flower Pollination (FP) algorithm for solving the optimal reactive power problem. Minimization of real power loss is taken as key intent. Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. The biological evolution point of view, the objective of the flower pollination is the survival of the fittest and the optimal reproduction of plants in terms of numbers as well as the largely fittest. In order to evaluate the performance of the proposed Flower Pollination (FP) algorithm, it has been tested on IEEE 57 bus system and compared to other standard reported algorithms. Simulation results show that FP algorithm is better than other algorithms in reducing the real power loss and voltage profiles are within the limits.

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