Optimal Sizing and Siting of Distributed Generation for Losses Minimization in Distribution System Using Fractional Lévy Flight Bat Algorithm

2021 ◽  
pp. 1-10
Author(s):  
Aditya N. Koundinya ◽  
Galiveeti Hemakumar Reddy ◽  
Z. Mohammed Khalander ◽  
Revanasidda
Keyword(s):  
Distributed Generation ◽  
Distribution System ◽  
Bat Algorithm ◽  
Lévy Flight ◽  
Levy Flight ◽  
Optimal Sizing

Simultaneous placement of DG and FACTS device in the Distribution system using Fractional Lévy Flight Bat Algorithm to minimize the Power losses

2021 ◽  
Author(s):  
Aditya N Koundinya ◽  
Galiveeti Hemakumar Reddy ◽  
Z Mohammed Khalander ◽  
Revanasidda Belure ◽  
More Raju
Keyword(s):  
Distribution System ◽  
Bat Algorithm ◽  
Lévy Flight ◽  
Power Losses ◽  
Levy Flight

Optimal placement of distributed generation based on DISCO’s additional benefit using self adaptive levy flight based black widow optimization

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Naga Lakshmi Gubbala Venkata ◽  
Jaya Laxmi Askani ◽  
Venkataramana Veeramsetty
Keyword(s):  
Distributed Generation ◽  
Distribution Network ◽  
Additional Benefit ◽  
Operating Conditions ◽  
Optimal Placement ◽  
Lévy Flight ◽  
Black Widow ◽  
Levy Flight ◽  
Simulation Performance ◽  
Self Adaptive

Abstract Optimal placement of Distributed Generation (DG) is a crucial challenge for Distribution Companies (DISCO’s) to run the distribution network in good operating conditions. Optimal positioning of DG units is an optimization issue where maximization of DISCO’s additional benefit due to the installation of DG units in the network is considered to be an objective function. In this article, the self adaptive levy flight based black widow optimization algorithm is used as an optimization strategy to find the optimum position and size of the DG units. The proposed algorithm is implemented in the IEEE 15 and PG & E 69 bus management systems in the MATLAB environment. Based on the simulation performance, it has been found that with the correct location and size of the DG modules, the distribution network can be run with maximum DISCO’s additional benefit.

Insulin DNA Sequence Classification Using Levy Flight Bat With Back Propagation Algorithm

2020 ◽  
pp. 232-252
Author(s):  
Siyab Khan ◽  
Abdullah Khan ◽  
Rehan Ullah ◽  
Maria Ali ◽  
Rahat Ullah
Keyword(s):  
Dna Sequence ◽  
Dna Sequences ◽  
Optimization Problems ◽  
Back Propagation ◽  
Bat Algorithm ◽  
Hybrid Models ◽  
Lévy Flight ◽  
Healthy Human ◽  
Levy Flight ◽  
Nature Inspired Algorithms

Various nature-inspired algorithms are used for optimization problems. Recently, one of the nature-inspired algorithms became famous because of its optimality. In order to solve the problem of low accuracy, famous computational methods like machine learning used levy flight Bat algorithm for the problematic classification of an insulin DNA sequence of a healthy human, one variant of the insulin DNA sequence is used. The DNA sequence is collected from NCBI. Preprocessing alignment is performed in order to obtain the finest optimal DNA sequence with a greater number of matches between base pairs of DNA sequences. Further, binaries of the DNA sequence are made for the aim of machine readability. Six hybrid algorithms are used for the classification to check the performance of these proposed hybrid models. The performance of the proposed models is compared with the other algorithms like BatANN, BatBP, BatGDANN, and BatGDBP in term of MSE and accuracy. From the simulations results it is shown that the proposed LFBatANN and LFBatBP algorithms perform better compared to other hybrid models.

A novel path planning method of mobile robots based on an improved bat algorithm

2020 ◽  
pp. 095440622096314
Author(s):  
Zhongbin Wang ◽  
Ziqing Wu ◽  
Lei Si ◽  
Kuangwei Tong ◽  
Chao Tan
Keyword(s):  
Path Planning ◽  
Mobile Robots ◽  
Fitness Function ◽  
Bat Algorithm ◽  
Cauchy Distribution ◽  
Planning Problem ◽  
Lévy Flight ◽  
Levy Flight ◽  
Global Path Planning ◽  
Search Stage

In order to solve the global path planning problem of mobile robots, an improved bat algorithm based on inertial weight and Levy flight is proposed in this paper. The linear inertial weights are used to prevent the algorithm from converging prematurely and the Levy flight is introduced in the global search stage to change the flight direction of the bat individuals. Furthermore, in the local search stage, the random exploration mechanism in Cauchy Distribution is utilized to enhance the local mining ability of the algorithm and search for the local optimal values. Then, some simulations are provided to verify the superiority of the improved bat algorithm to other optimization algorithms. Finally, the improved bat algorithm is applied in the global path planning, and the environment model and fitness function construction are reasonably established. The results indicate the feasibility and effectiveness of proposed algorithm in solving path planning problems.

scholarly journals Modified Bat Algorithm Based on Lévy Flight and Opposition Based Learning

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Xian Shan ◽  
Kang Liu ◽  
Pei-Liang Sun
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Real Life ◽  
Bat Algorithm ◽  
Global Optimum ◽  
Lévy Flight ◽  
Levy Flight ◽  
Local Optima ◽  
Opposition Based Learning ◽  
Modified Bat Algorithm

Bat Algorithm (BA) is a swarm intelligence algorithm which has been intensively applied to solve academic and real life optimization problems. However, due to the lack of good balance between exploration and exploitation, BA sometimes fails at finding global optimum and is easily trapped into local optima. In order to overcome the premature problem and improve the local searching ability of Bat Algorithm for optimization problems, we propose an improved BA called OBMLBA. In the proposed algorithm, a modified search equation with more useful information from the search experiences is introduced to generate a candidate solution, and Lévy Flight random walk is incorporated with BA in order to avoid being trapped into local optima. Furthermore, the concept of opposition based learning (OBL) is embedded to BA to enhance the diversity and convergence capability. To evaluate the performance of the proposed approach, 16 benchmark functions have been employed. The results obtained by the experiments demonstrate the effectiveness and efficiency of OBMLBA for global optimization problems. Comparisons with some other BA variants and other state-of-the-art algorithms have shown the proposed approach significantly improves the performance of BA. Performances of the proposed algorithm on large scale optimization problems and real world optimization problems are not discussed in the paper, and it will be studied in the future work.

Locational marginal price computation in radial distribution system using Self Adaptive Levy Flight based JAYA Algorithm and game theory

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Venkataramana Veeramsetty ◽  
Venkaiah Chintham ◽  
Vinod Kumar D.M.
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Emission Reduction ◽  
Jaya Algorithm ◽  
Lévy Flight ◽  
Levy Flight ◽  
Reliability Improvement ◽  
Locational Marginal Price ◽  
Marginal Price ◽  
Self Adaptive

Abstract This study presents a computational approach to compute locational marginal price (LMP) at distributed generation (DG) buses in an electric power distribution system using self-adaptive levy flight based JAYA algorithm and proportional nucleolus theory (PNT). This method provides financial incentive to DG owners based on their contribution in reliability improvement, loss and emission reduction. In this study expected energy not supplied (EENS) is used for measuring the reliability of a given radial distribution network. This method is implemented on 38 bus distribution system under MATLAB environment to compute LMP values at each DG as per its contribution towards reliability improvement, loss reduction and emission reduction. It is found from the study that reliability has been improved, losses and emissions of system were reduced by providing proper financial incentives to DG owners. The proposed method can be utilized by a distribution company (DISCO) to operate network optimally and to estimate state of network.

scholarly journals Power Quality Enhancement by Integrating Distributed Generation in Distribution System

2018 ◽  
Vol 7 (4.24) ◽  
pp. 167
Author(s):  
Mr. Rajesh Kumar Samala ◽  
Dr. K Mercy Rosalina
Keyword(s):  
Power Quality ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Bat Algorithm ◽  
Optimal Placement ◽  
Optimal Size ◽  
Voltage Profile ◽  
Real Power ◽  
Optimal Capacity

This research is to enhance the quality of power by reduce real power loss in distribution system and enables voltage profile enhancement at each bus. This will achieve by integrating Distributed Generation (DG) in optimal place with suitable size. In order to overcome the disadvantage of sluggish convergence of conventional algorithms the BAT Algorithm (BA) is used. In this paper the week buses are finding by using Backward/Forward (BW/FW) sweep approach based on real power loss. Later by using BA approach determination of optimal capacity and location will be done. This optimal size and location will leads to great minimization in real power loss and improvement of voltage at each bus. In this research the wind energy and Photo Voltaic (PV) energies are consider as DGs. This research is to determine the advantage of the proposed analysis on IEEE-69 radial bus using MATLAB software. The results were evaluated with the GSA approach existing in literature. Finally simulation outcomes prove that the proposed approach performance is superior in enhancing the power quality by optimal placement of DG and capacity of the DG.

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