Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
Research on Wind Speed Vertical Extrapolation Based on Extreme Learning Machine Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

A Green Dispatch Model of Power System with Wind Energy Considering Energy-Environmental Efficiency

verfasst von : Daojun Chen, Liqing Liang, Lei Zhang, Jian Zuo, Keren Zhang, Chenkun Li, Hu Guo

Erschienen in: Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration

Verlag: Springer Singapore

Einloggen

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

search-config
loading …

Abstract

With rising pressure caused by decreasing natural resources, there emerges stronger call for environmental protection and sustainable development. As a kind of environmental-friendly energy, wind power has been increasing in capacity around the world in recent years. As more and more wind power gets connected with the grid, its impact on power dispatch should also be considered. Based on traditional power system optimized dispatch, this paper introduces the energy-environmental efficiency concept into construction of a green dispatch model for wind incorporated power systems. The strategy takes both minimum resource consumption and best energy-environmental efficiency as indexes to assess the optimization of wind power incorporated systems from an environmental-friendly point of view. Fuzzy technology is adopted along with the tabu search-based PSO algorithm to solve the problem. It is proven that the proposed model is reasonable and of good practicality.

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 "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

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
Vorheriges Kapitel Building a Virtual Reality System for Intelligent Agriculture Greenhouse Based on Web3D
Literatur
1.
Damousis, I.G., Alexiadis, M.C., Theocharis, J.B., Dokopoulos, P.S.: A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation. IEEE Trans. Energy Convers. 19(2), 352–361 (2004)CrossRef
2.
Miranda, V., Hang, P.S.: Economic dispatch model with fuzzy wind constraints and attitudes of dispatchers. IEEE Trans. Power Syst. 20(4), 2143–2145 (2005)CrossRef
3.
Chen, C.L., Lee, T.Y., Jan, R.M.: Optimal wind-thermal coordination dispatch in isolated power systems with large integration of wind capacity. Energy Convers. Manage. 47(18–19), 3456–3472 (2006)CrossRef
4.
Eriksen, P.B., Ackermann, T., Abildgaard, H., Smith, P., Winter, W., Rodriquez Garcia, J.M.: System operation with high wind penetration. IEEE Power Energy Mag. 3(6), 65–74 (2005)CrossRef
5.
Marwali, M.K., Shahidehpour, S.M.: Coordination between long-term and short-term generation scheduling with net-work constraints. IEEE Trans. Power Syst. 15(3), 1161–1167 (2000)CrossRef
6.
Carrion, M., Arroyo, J.M.: A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem. IEEE Trans. Power Syst. 21(3), 1371–1378 (2006)CrossRef
7.
Li, C.A., Jap, P.J., Streiffert, D.L.: Implementation of network flow programming to the hydrothermal coordination in an energy management system. IEEE Trans. Power Syst. 8(3), 1045–1093 (1993)CrossRef
8.
Kumar, S., Naresh, R.: Efficient real coded genetic algorithm to solve the non-convex hydrothermal scheduling problem. Electr. Power Energy Syst. 29(10), 738–747 (2007)CrossRef
9.
Yu, B.H., Yuan, X.H., Wang, J.W.: Short-term hydro-thermal scheduling using particle swarm optimization method. Energy Convers. Manag. 48(7), 1902–1908 (2007)CrossRef
10.
Damousis, I.G., Bakirtzis, A.G., Dokopoulos, P.S.: Network-constrained economic dispatch using real-coded genetic algorithm. IEEE Trans. Power Syst. 18(1), 198–205 (2003)CrossRef
11.
Yang, H.T., Yang, P.C., Huang, C.L.: Evolutionary programming based economic dispatch for units with nonsmooth fuel cost functions. IEEE Trans. Power Syst. 11, 112–118 (1996)CrossRef
12.
Walters, D., Sheble, C., Gerald, B.: Genetic algorithm solution of economic dispatch with valve point loading. IEEE Trans. Power Syst. 8, 1325–1332 (1993)CrossRef
13.
Cardu, M., Baica, M.: Regarding a global methodology to estimate the energy-ecologic efficiency of thermopower plants. Energy Convers. Manag. 40(1), 71–87 (1999)CrossRef
14.
Chen, H.Y., Chen, J.F., Duan, X.Z.: Study on power flow calculation of distribution system with DGs. Autom. Electr. Power Syst. 30(1), 35–40 (2006)
15.
Huang, C.M., Yang, H.T., Huang, C.L.: Bi-objective power dispatch using fuzzy satisfaction-maximizing decision approach. IEEE Trans. Power Syst. 12(4), 1715–1721 (1997)CrossRef
16.
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE Proceedings of the International Conference on Neural Networks, Perth, Australia, pp. 1942–1948 (1995)
17.
Chen, D., Gong, Q., Zou, B., et al.: A low-carbon dispatch model in a wind power integrated system considering wind speed forecasting and energy-environmental efficiency. Energies 5(4), 1245–1270 (2012)CrossRef
18.
Hirotaka, Y., Kenichi, K., Yoshikazu, F.: A particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE Trans. Power Syst. 15(4), 1232–1239 (2000)
19.
Park, J.B., Jeong, Y.W., Shin, J.R., Lee, K.Y.: An improved particle swarm optimization for nonconvex economic dispatch problems. IEEE Trans. Power Syst. 25(1), 156–166 (2010)CrossRef
20.
Saravuth, P., Issarachai, N., Waree, K.: Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints. Energy Convers. Manage. 49(4), 506–516 (2008)CrossRef
21.
Chen, D., Wang, X., Zuo, J.: A joint optimal dispatching method for pumped storage power station and wind power considering wind power uncertainties. Power Syst. Clean Energy 32(8), 110–116 (2016)
22.
Chen, D., Li, L., Yang, N.: Combination forecasting method of wind power based on optimal weight coefficient. Power Syst. Clean Energy 32(4), 99–105 (2016)
23.
Metadaten
Titel
A Green Dispatch Model of Power System with Wind Energy Considering Energy-Environmental Efficiency
verfasst von
Daojun Chen
Liqing Liang
Lei Zhang
Jian Zuo
Keren Zhang
Chenkun Li
Hu Guo
Copyright-Jahr
2017
Verlag
Springer Singapore
Buch
Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration

Print ISBN: 978-981-10-6363-3

Electronic ISBN: 978-981-10-6364-0

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-981-10-6364-0_79