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Soft Computing

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19.05.2020 | Methodologies and Application

Real power loss reduction by Duponchelia fovealis optimization and enriched squirrel search optimization algorithms

verfasst von: Kanagasabai Lenin

Erschienen in: Soft Computing | Ausgabe 23/2020

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Abstract

In this work, Duponchelia fovealis optimization (DFO) algorithm and enriched squirrel search optimization (ESSO) algorithm are designed to solve optimal reactive power problem. DFO algorithm is based on the natural progression of the Duponchelia fovealis. In the exploration space, Duponchelia fovealis population will act as search agent and the light source is considered as optimal places of Duponchelia fovealis which attained so far. Around the light source, each Duponchelia fovealis will explore and its position has been updated. Gaussian mutation, chaotic local search and Kernel extreme learning machine which are based on extreme learning machine are applied successively in order to perk up the performance of the algorithm. Then, in this work enriched squirrel search optimization (ESSO) algorithm is projected to solve the problem. Proposed algorithm is based on the actions of squirrel foraging behavior. Naturally, squirrels are very less active and consume the stored nuts in the winter time to get ample of energy. Hickory tree (hickory nuts are found), oak tree (acorn nuts are found) and normal tree are the three types of food sources for squirrel. Naturally, the behavior (foraging) will be varied with reference to the seasonal variations. Proposed Duponchelia fovealis optimization (DFO) algorithm and enriched squirrel search optimization (ESSO) algorithm have been tested in standard IEEE 30, bus test system. The results show that the projected DFO and ESSO algorithms reduced the power loss comprehensively. Mainly, projected Duponchelia fovealis optimization (DFO) algorithm and enriched squirrel search optimization (ESSO) algorithm solved the multi-objective formulation of the problem and with reference to power loss, voltage deviation minimization and voltage stability enhancement results have been analyzed.

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Abdel-Akher M (2013) Voltage stability analysis of unbalanced distribution systems using backward/forward sweep load-flow analysis method with secant predictor. IET Gener Trans Distrib 7:309–317

Abualigah LMQ (2019) Feature selection and enhanced krill herd algorithm for text document clustering. Stud Comput Intell

Abualigah LMQ, Hanandeh ES (2015) Applying genetic algorithms to information retrieval using vector space model. Int J Comput Sci Eng Appl 5(1):19

Abualigah LM, Khader AT (2017) Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering. J Supercomput 73(11):4773–4795

Abualigah LM, Khader AT, Hanandeh ES (2017a) A new feature selection method to improve the document clustering using particle swarm optimization algorithm. J Comput Sci 25:456–466

Abualigah LM, Khader AT, Hanandeh ES, Gandomi AH (2017b) A novel hybridization strategy for krill herd algorithm applied to clustering techniques. Appl Soft Comput 60:423–435

Abualigah LM, Khader AT, Hanandeh ES (2018a) Hybrid clustering analysis using improved krillherd algorithm. Appl Intell 48(1):1–11

Abualigah LM, Khader AT, Hanandeh ES (2018b) A combination of objective functions and hybrid krill herd algorithm for text document clustering analysis. Eng Appl Artif Intell 73:111–125

Aljohani TM, Ebrahim AF, Mohammed Single O (2019a) Multiobjective optimal reactive power dispatch based on hybrid artificial physics–particle swarm optimization. Energies 12(12):2333. https://doi.org/10.3390/en12122333CrossRef

Aljohani TM, Ebrahim AF, Mohammed O (2019b) Single and multiobjective optimal reactive power dispatch based on hybrid artificial physics-particle swarm optimization. Energies MDPI Open Access J 12(12):1–24

Aljohani TM, Ebrahim AF, Mohammed O (2019c) Single and multiobjective optimal reactive power dispatch based on hybrid artificial physics-particle swarm optimization. Energies 12:2333

Arifoğlu U, Yalçin F (2018) System constrained active power loss minimization in practical multi-terminal HVDC systems through GA Sakarya University. J Sci. https://doi.org/10.16984/saufenbilder.421351CrossRef

Basu M (2016) Quasi-oppositional differential evolution for optimal reactive power dispatch. Electric Power Energy Syst 78:29–40

Beigvand SD, Abdi H, La Scala M (2016) Combined heat and power economic dispatch problem using gravitational search algorithm. Electric Power Syst Res 133:160–172

Bindu KN, Kumar KK (2016) Combined economic and emission dispatch using random drift particle swarm optimization. Int J Mod Trends Sci Technol 2(11):134–139

Bingane C, LeDigabel Miguel F AS (2019) Tight-and-cheap conic relaxation for the optimal reactive power dispatch problem. IEEE Trans Power Syst. https://doi.org/10.1109/tpwrs.2019.2912889CrossRef

Bjelogrlic MR, Calovic MS, Babic BS (1990) Application of Newton’s optimal power flow in voltage/reactive power control. IEEE Trans Power Syst 5(4):1447–1454

Caldera M, Ungaro P, Cammarata G, Puglisi G (2018) Survey-based analysis of the electrical energy demand in Italian households. Math Modell Eng Problems 5(3):217–224. https://doi.org/10.18280/mmep.050313CrossRef

Chavan SD, Adgokar NP (2015) An overview on particle swarm optimization: basic concepts and modified variants. Int J Sci Res 4(5):255–260

Dai C, Chen W, Zhu Y, Zhang X (2009) Seeker optimization algorithm for optimal reactive power dispatch. IEEE T Power Syst 24(3):1218–1231

Deeb NI (1998) An efficient technique for reactive power dispatch using a revised linear programming approach. Electric Power Syst Res 15(2):121–134

Du Z, Nie Y, Liao P (2014) PCPDIPM-based optimal reactive power flow model using augmented rectangular coordinates. Int Trans Electric Energy Syst 24:597–608

Duman S, Sönmez Y, Güvenç U, Yörükeren N (2012) Optimal reactive power dispatch using a gravitational search algorithm. IET Gener Trans Distrib 6:563–576

El Ela AA, Abido MA, Spea SR (2011) Differential evolution algorithm for optimal reactive power dispatch. Electric Power Syst Res 81:458–464

Fang S, Cheng H, Xu G, Zhou Q, He H, Zeng P (2017) Stochastic optimal reactive power reserve dispatch considering voltage control areas. Int Trans Electric Energy Syst 27:e2269

Gagliano A, Nocera F (2017) Analysis of the performances of electric energy storage in residential applications. Int J Heat Technol 1:S41–S48. https://doi.org/10.18280/ijht.35Sp0106CrossRef

Ghazavi Dozein M, Monsef H, Ansari J, Kazemi A (2016) An effective decentralized scheme to monitor and control the reactive power flow: a holonic-based strategy. Int Trans Electric Energy Syst 26:1184–1209

Granville S (1994) Optimal reactive dispatch through interior point methods. IEEE Trans Power Syst 9(1):136–146. https://doi.org/10.1109/59.317548CrossRef

Grudinin N (1998) Reactive power optimization using successive quadratic programming method. IEEE Trans Power Syst 13(4):1219–1225. https://doi.org/10.1109/59.736232CrossRef

Herbadji, O, Slimani L, Bouktir T (2017) Multiobjective optimal power flow considering the fuel cost, emission, voltage deviation and power losses using multi-objective dragonfly algorithm. In: International conference on recent advances in electrical systems, pp 191–197

Hussain AN, Abdullah AA, Neda OM (2018) Modified particle swarm optimization for solution of reactive power dispatch. Res J Appl Sci Eng Technol 15(8):316–327. https://doi.org/10.19026/rjaset.15.5917CrossRef

Illinois Center for a Smarter Electric Grid (ICSEG) Available online: https://icseg.iti.illinois.edu/ieee-30-bussystem/. Accessed on 25 Feb 2019)

Jain M, Singh V, Rani A (2019) A novel nature-inspired algorithm for optimization: squirrel search algorithm. Swarm Evolut Comput 44:148–175

Lee KY (1984) Fuel-cost minimisation for both real and reactive-power dispatches. Proceed Generat Trans Distribut Conf 131(3):85–93

Liu B, Liu F, Zhai B, Lan H (2019) Investigating continuous power flow solutions of IEEE 14-bus system. IEEJ Trans Electric Electron Eng 14:157–159

Mahate RK, Singh H (2019) Multi-objective optimal reactive power dispatch using differential evolution. Int J Eng Technol Manag Res 6(2):27–38. https://doi.org/10.5281/zenodo.2585477CrossRef

Morsal J, Zare K, Hagh MT (2015) Performance comparison of TCSC with TCPS and SSSC controllers in AGC of realistic interconnected multi—sources power system, vol 1. Elsevier, Amsterdam, pp 64–68

Mouassa S, Bouktir T (2019) Multi-objective ant lion optimization algorithm to solve large-scale multi-objective optimal reactive power dispatch problem. COMPEL Int J Comput Math Electric Electron Eng 38(1):304–324. https://doi.org/10.1108/COMPEL-05-2018-0208CrossRef

Nagendra P, Dey Halder Nee, Paul S (2014) Voltage stability assessment of a power system incorporating FACTS controllers using unique network equivalent. Ain Shams Eng J 5(1):103–111

Nagendra P, Dey Halder Nee, Paul S (2015) Location of static VAR compensator in a multi-bus power system using unique network equivalent. Adv Energy Res 3(4):235–249

Narang N, Sharma E, Dhillon JS (2017) Combined heat and power economic dispatch using integrated civilized swarm optimization and Powell’s pattern search method. Appl Soft Comput 52:190–202

Nguyen TP, Vo DN (2018) A novel stochastic fractal search algorithm for optimal allocation of distributed generators in radial distribution systems. Appl Sof Comput 70:773–796

Prasad D, Mukherjee V (2018) Solution of optimal reactive power dispatch by symbiotic organism search algorithm incorporating FACTS devices. IETE J Res 64(1):149–160. https://doi.org/10.1080/03772063.2017.1334600CrossRef

Prasad C, Prasad D, Kumar GP (2016) Effect of load parameters variations on AGC of single area thermal power system in presence of integral and PSO-PID controllers. Conf Power Control Common Compute Technol Sustain Growth 1:64–68

Ramírez M, Castellanos R, Calderón G, Malik Om (2018) Placement and sizing of battery energy storage for primary frequency control in an isolated section of the Mexican power system. Electric Power Syst Res 160:142–150

Rayudu K, Yesuratnam G, Jayalaxmi A (2017) Ant colony optimization algorithm based optimal reactive power dispatch to improve voltage stability. In: Proceedings of the 2017 IEEE international conference on circuit, power and computing technologies, ICCPCT 2017, pp 1–6

Reddy SS (2014) Faster evolutionary algorithm based optimal power flow using incremental variables. Electric Power Energy Syst 54:198–210

Rodríguez-Gallegos CD, Yang D, Gandhi O, Bieri M, Reindl T, Panda SK (2018) A multi-objective and robust optimization approach for sizing and placement of PV and batteries in off-grid systems fully operated by diesel generators. An Indonesian case study. Energy 160:410–429

Roy PK, Dutta S (2019) Economic load dispatch: optimal power flow and optimal reactive power dispatch concept. Optimal power flow using evolutionary algorithms. IGI Global Web. https://doi.org/10.4018/978-1-5225-6971-8.ch002CrossRef

Rupa JM, Ganesh S (2014) Power flow analysis for radial distribution system using backward/forward sweep method. Int J Electric Comput Electron Commun Eng 8:1540–1544

Soodi HA, Vural AM (2018) STATCOM estimation using back-propagation, pso, shuffled frog leap algorithm, and genetic algorithm based neural networks. Comput Intell Neurosci 2018:6381610

Subbaraj P, Rajnarayan PN (2009) Optimal reactive power dispatch using self-adaptive real coded Genetic algorithm. Electric Power Syst Res 79(2):374–384

Sun Y, Gao Y (2019) A multi-objective particle swarm optimization algorithm based on gaussian mutation and an improved learning strategy. Mathematics 7:148

SurenderReddy S (2017) Optimal reactive power scheduling using cuckoo search algorithm. Int J Electric Comput Eng 7(5):2349–2356

Teeparthi K, Kumar DV (2017a) Multi-objective hybrid PSO-APO algorithm-based security constrained optimal power flow with wind and thermal generators. Eng Sci Technol Int J 20:411–426

Teeparthi K, Kumar DV (2017b) Dynamic power system security analysis using a hybrid PSO-APO algorithm. Eng Technol Appl Sci Res 7:2124–2131

Vaisakh K, Member IEEE, Kanta Rao P (2008) Optimum reactive power dispatch using differential evolution for improvement of voltage stability. 978- 1-4244-1762-9/08/C 2008 IEEE

Warid W, Hizam H, Mariun N, Wahab NIA (2018) A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution. Appl Soft Comput J 65:360–373

Wei H, Lin C, Wang Y (2018) The optimal reactive power flow model in mixed polar form based on transformer dummy nodes. IEEJ Trans Elec Electron Eng 13:411–416

Yalçın E, Taplamacıoğlu M, Çam E (2019) The adaptive chaotic symbiotic organisms search algorithm proposal for optimal reactive power dispatch problem in power systems. Electrica 19:37–47

Zhang H, Lei X, Wang C, Yue D, Xie X (2017) Adaptive grid based multi-objective Cauchy differential evolution for stochastic dynamic economic emission dispatch with wind power uncertainty. PLoS ONE, pp 1–25

Zhang Q, Chen H, Heidari AA, Zhao X, Xu Y, Wang P (2019) Chaos- induced and mutation-driven schemes boosting salp chains-inspired optimizers. IEEE Access. https://doi.org/10.1109/ACCESS.2019.2902306CrossRef

Zhao D, Huang C, Wei Y, Fanhua Y, Wang M, Chen H (2017) An effective computational model for bankruptcy prediction using kernel extreme learning machine approach. Comput Econ 49(2):325–341

Zhao X, Zhang X, Cai Z, Tian X, Wang X, Huang Y et al (2019) Chaos en- hanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients. Comput Biol Chem 78:481–490

Titel: Real power loss reduction by Duponchelia fovealis optimization and enriched squirrel search optimization algorithms
verfasst von: Kanagasabai Lenin
Publikationsdatum: 19.05.2020
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 23/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-020-05036-x

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