nach oben

Soft Computing

Erschienen in:

01.07.2017 | Methodologies and Application

Solution of short-term hydrothermal scheduling using sine cosine algorithm

verfasst von: Sujoy Das, Aniruddha Bhattacharya, Ajoy Kumar Chakraborty

Erschienen in: Soft Computing | Ausgabe 19/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Hydrothermal scheduling is an important issue in the field of power system economics. The aim of the short-term hydrothermal scheduling is to optimize the hourly output of power generation for different hydrothermal units for certain intervals of time to minimize the total cost of generations. The purpose of this article is to propose a new population-based algorithm named sine cosine algorithm to solve short-term hydrothermal scheduling problem. Hydrothermal scheduling problem is considered as an optimization problem by formulating objective function taking different equality and inequality constraints. Along with valve point loading effect, transmission loss is also considered. Here six different test systems are considered with different cost functions to verify the performance of sine cosine algorithm. The results obtained by sine cosine algorithm are compared with the results obtained by other recently developed techniques, and it was observed that it provides superior results than others in terms of generation cost as well as simulation time. Sine cosine algorithm is still new and has not yet been applied by the researchers in the field of power system. Therefore, the researchers may apply this algorithm in a different power system-related problems.

Vorheriger Artikel Multi-focus image fusion method using S-PCNN optimized by particle swarm optimization

Nächster Artikel Vehicle license plate detection using region-based convolutional neural networks

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Ahmadi A, Kaymanesh A, Siano P, Janghorbani M, Nezhad AE, Sarno D (2015) Evaluating the effectiveness of normal boundary intersection method for short-term environmental/economic hydrothermal self-scheduling. Electr Power Syst Res 123:192–204. doi:10.1016/j.epsr.2015.02.007 CrossRef

Amjady N, Soleymanpour HR (2010) Daily hydrothermal generation scheduling by a new modified adaptive particle swarm optimization technique. Electr Power Syst Res 80(6):723–732. doi:10.1016/j.epsr.2009.11.004 CrossRef

Banerjee S, Dasgupta K, Chanda CK (2016) Short-term hydro-wind-thermal scheduling based on particle swarm optimization technique. Int J Electr Power 81:275–288. doi:10.1016/j.ijepes.2016.01.031 CrossRef

Basu M (2003) Hopfield neural networks for optimal scheduling of fixed head hydrothermal power systems. Electr Power Syst Res 64(1):11–15. doi:10.1016/S0378-7796(02)00118-9 CrossRef

Basu M (2011) Artificial immune system for fixed head hydrothermal power system. Energy 36(1):606–612. doi:10.1016/j.energy.2010.09.057 CrossRef

Bhattacharjee K, Bhattacharya A, nee Dey SH (2014) Real coded chemical reaction based optimization for short-term hydrothermal scheduling. Appl Soft Comput 24:962–976. doi:10.1016/j.asoc.2014.08.048 CrossRef

Bhattacharjee K, Bhattacharya A, nee Dey SH (2014) Oppositional real coded chemical reaction based optimization to solve short-term hydrothermal scheduling problems. Int J Electr Power 63:145–157. doi:10.1016/j.ijepes.2014.05.065 CrossRef

Chan PH, Chang HC (1996) Genetic aided scheduling of hydraulically coupled plants in hydrothermal coordination. IEEE Trans Power Syst 11(2):975–981. doi:10.1109/59.496183 CrossRef

Das S, Bhattacharya A, Chakraborty AK (2016) Quasi reflected ion motion optimization algorithm for short-term hydro thermal scheduling. Neural Comput Appl. doi:10.1007/s00521-016-2529-8 CrossRef

Derrac J, Garcia S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1:3–18. doi:10.1016/j.swevo.2011.02.002 CrossRef

Dubey HM, Pandit M, Panjigrahi BK (2016) Ant lion optimization for short-term wind integrated hydrothermal power generation scheduling. Int J Electr Power 83:158–174. doi:10.1016/j.ijepes.2016.03.057 CrossRef

Engles L, Larson RE, Peschon J, Stanton KN (1976) Dynamic programming applied to hydro and thermal generation scheduling. In: IEEE tutorial course text, 76CH1107-2-PWR, IEEE, New York

Fakhar MS, Kahif SAR, Saqib MA, Hassan TU (2015) Non cascaded short-term hydro-thermal scheduling using fully-informed particle swarm optimization. Int J Electr Power Energy Syst 73:983–990. doi:10.1016/j.ijepes.2015.06.030 CrossRef

Fang N, Zhou J, Zhang R, Liu Y, Zhang Y (2014) A hybrid of real coded genetic algorithm and artificial fish swarm algorithm for short-term optimal hydrothermal scheduling. Int J Electr Power Energy Syst 62:617–629. doi:10.1016/j.ijepes.2014.05.017 CrossRef

Franco P, Carvalho M, Soares S (1994) A network flow model for short-term hydro dominated hydrothermal scheduling problems. IEEE Trans Power Syst 9(2):1016–1022. doi:10.1109/59.317642 CrossRef

Gil E, Araya J (2016) Short-term hydrothermal generation scheduling using a parallelized stochastic mixed-integer linear programming algorithm. Energy Proc 87:77–84. doi:10.1016/j.egypro.2015.12.360 CrossRef

Gouthamkumar N, Sharma V, Naresh R (2015) Disruption based gravitational search algorithm for short term hydrothermal scheduling. Expert Syst Appl 42:7000–7011. doi:10.1016/j.eswa.2015.05.017 CrossRef

Habibollahzadeh H, Bubenko J (1986) Application of decomposition techniques to short-term operation planning of hydrothermal power system. IEEE Trans Power Syst 1(1):41–47. doi:10.1109/TPWRS.1986.4334842 CrossRef

Hota PK, Barisal AK, Chakrabarti R (2009) An improved PSO technique for short-term optimal hydrothermal scheduling. Electr Power Syst Res 79(7):1047–1053. doi:10.1016/j.epsr.2009.01.001 CrossRef

Jingrui Z, Jian W, Chaoyuan Y (2012) Small population-based particle swarm optimization for short-term hydrothermal scheduling. IEEE Trans Power Syst 27(1):142–152. doi:10.1109/TPWRS.2011.2165089 CrossRef

Mandal KK, Chakraborty N (2008) Differential evolution technique-based short-term economic generation scheduling of hydrothermal systems. Electr Power Syst Res 78(11):1972–1979. doi:10.1016/j.epsr.2008.04.006 CrossRef

Mandal KK, Basu M, Chakraborty N (2008b) Particle swarm optimization technique based short-term hydrothermal scheduling. Appl Soft Comput 8(4):1392–1399. doi:10.1016/j.asoc.2007.10.006 CrossRef

Mirjalili S (2015a) The ant lion optimizer. Adv Eng Softw 83:80–98. doi:10.1016/j.advengsoft.2015.01.010

Mirjalili S (2015b) Moth-flame optimization algorithm: a novel nature-inspired heuristic paradigm. Knowl Based Syst 89:228–249. doi:10.1016/j.knosys.2015.07.006

Mirjalili S (2016a) Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Comput Apppl 27:1053–1073. doi:10.1007/s00521-015-1920-1 CrossRef

Mirjalili S (2016b) SCA: a sine cosine algorithm for solving optimization problems. Knowl Based Syst 96:120–133. doi:10.1016/j.knosys.2015.12.022 CrossRef

Mirjalili S, Lewis A (2016) The Whale optimization algorithm. Adv Eng Softw 95:51–67. doi:10.1016/j.advengsoft.2016.01.008

Nguyen TT, VO DN (2015) Modified cuckoo search algorithm for short-term hydrothermal scheduling. Electr Power Energy Syst 65:271–281. doi:10.1016/j.ijepes.2014.10.004 CrossRef

Nguyen TT, Vo DN (2016) An efficient cuckoo bird inspired meta-heuristic algorithm for short-term combined economic emission hydrothermal scheduling. Ain Shams Eng J. doi:10.1016/j.asej.2016.04.003 CrossRef

Nguyen TT, VO DN, Ruong AV (2014) Cuckoo search algorithm for short-term hydrothermal scheduling. Appl Energy 132:276–287. doi:10.1016/j.apenergy.2014.07.017 CrossRef

Nilsson O, Sjelvgren D (1996) Mixed-integer programming applied to short-term planning of a hydrothermal system. IEEE Trans Power Syst 11(1):281–286. doi:10.1109/59.486107 CrossRef

Orero SO, Irving MR (1998) A genetic algorithm modeling framework and solution technique for short term optimal hydrothermal scheduling. IEEE Trans PWRS 13(2):501–518. doi:10.1109/TPWRS.2002.807053 CrossRef

Rasoulzadeh-akhijahani A, Mohammadi-ivatloo B (2015) Short-term hydrothermal generation scheduling by modified dynamic neighborhood learning based particle swarm optimization. Int J Electr Power 67:350–367CrossRef

Roy PK (2013) Teaching learning based optimization for short-term hydrothermal scheduling problem considering valve point effect and prohibited discharge constraint. Int J Electr Power 53:10–19. doi:10.1016/j.ijepes.2013.03.024 CrossRef

Roy PK, Sur A, Pradhan DK (2014) Optimal short-term hydrothermal scheduling using quasi-oppositional teaching learning based optimization. Eng Appl Artif Intell 26:2516–2524

Roy PK, Pradhan M, Paul T (2015) Krill herd algorithm applied to short-term hydrothermal scheduling problem. Ain Shams Eng J. doi:10.1016/j.asej.2015.09.003 CrossRef

Saha TN, Khaparde SA (1978) An application of a direct method for the optimal scheduling of hydrothermal power systems. IEEE Trans PAS 97(3):977–985. doi:10.1109/TPAS.1978.354571 CrossRef

Salam Nor KM, Hamdan AR (1998) Hydrothermal scheduling based Lagrangian relaxation approach to hydrothermal coordination. IEEE Trans Power Syst 13(1):226–235. doi:10.1109/59.651640 CrossRef

Sheskin DJ (2006) Handbook of parametric and nonparametric statistical procedures, 4th edn. Chapman & Hall/CRC, LondonMATH

Sinha N, Chakrabarti R, Chattopadhaya PK (2003) Fast evolutionary programming techniques for short-term hydrothermal scheduling. Electr Power Syst Res 66:97–103. doi:10.1109/TPWRS.2002.807053 CrossRef

Turgeon A (1981) Optimal short-term hydro scheduling from the principle of progressive optimality. Water Resour Res 17(3):481–486. doi:10.1029/WR017i003p00481 CrossRef

Türkay B, Mecitoğlu F, Baran S (2011) Application of a fast evolutionary algorithm to short-term hydrothermal generation scheduling. Energy Sour B Econ Plan Policy. doi:10.1080/15567249.2010.489098 CrossRef

Wang Y, Zhou J, Mo L, Zhang R, Zhang Y (2012) Short-term hydrothermal generation scheduling using differential real-coded quantum-inspired evolutionary algorithm. Energy 44(1):657–671. doi:10.1016/j.energy.2012.05.026 CrossRef

Wang Y, Zhou J, Mo L, Ouyang S, Zhang Y (2012) A clonal real-coded quantum-inspired evolutionary algorithm with cauchy mutation for short-term hydrothermal generation scheduling. Int J Electr Power Energy Syst 43(1):1228–1240. doi:10.1016/j.ijepes.2012.06.036 CrossRef

Wong KP, Wong YW (1994a) Short-term hydrothermal scheduling part I: simulated annealing approach. Proc Inst Electr Eng Gen Transm Distrib 141(5):497–501. doi:10.1049/ip-gtd:19941350 CrossRef

Wong KP, Wong YW (1994b) Short-term hydrothermal scheduling part II: parallel simulated annealing approach. Proc Inst Electr Eng Gen Transm Distrib 141(5):502–506. doi:10.1049/ip-gtd:19941351 CrossRef

Wood AJ, Wollenberg BF (1984) Power generation, operation and control. Wiley, New York

Yang H, Yang P, Huang C (1996) Evolutionary programming based economic dispatch for units with non-smooth fuel cost functions. IEEE Trans PWRS 11(1):112–118. doi:10.1109/59.485992 CrossRef

Yu B, Yuan X, Wang J (2007) Short-term hydrothermal scheduling using particle swarm optimization method. Energy Convers Manag 48(7):1902–1908. doi:10.1016/j.enconman.2007.01.034 CrossRef

Yuan X, Tian H, Yuan Y, Huang Y, Ikram RM (2015) An extended NSGA-III for solution multi-objective hydrothermal-wind scheduling considering wind power cost. Energy Convers Manag 96:568–578. doi:10.1016/j.enconman.2015.03.009 CrossRef

Zaghlool MF, Trutt FC (1988) Efficient methods for optimal scheduling of fixed head hydrothermal power systems. IEEE Trans Power Syst. doi:10.1109/59.43176 CrossRef

Zhang J, Lin S, Qiu W (2015) A modified chaotic differential evolution algorithm for short-term optimal hydrothermal scheduling. Int J Electr Power Energy Syst 65:159–168. doi:10.1016/j.ijepes.2014.09.041 CrossRef

Titel: Solution of short-term hydrothermal scheduling using sine cosine algorithm
verfasst von: Sujoy Das
Aniruddha Bhattacharya
Ajoy Kumar Chakraborty
Publikationsdatum: 01.07.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 19/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-017-2695-3

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 19/2018

Multi-view 3D reconstruction and modeling of the unknown 3D scenes using genetic algorithms

Multi-focus image fusion method using S-PCNN optimized by particle swarm optimization

Vehicle license plate detection using region-based convolutional neural networks

A hidden semi-Markov model for chart pattern matching in financial time series

Automatic detection and recognition of optic disk with maker-controlled watershed segmentation and mathematical morphology in color retinal images

Many-objective artificial bee colony algorithm for large-scale software module clustering problem