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

Integration of the Demand Side Management with Active and Reactive Power Economic Dispatch of Microgrids

verfasst von : Mohammed K. Al-Saadi, Patrick C. K. Luk, John Economou

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

This paper presents a fully developed integration of the demand side management (DSM) into multi-period unified active and reactive power dynamic economic dispatch of the microgrids (MGs) combined with unit commitment (UC) to reduce the total operating cost or maximizes the profit with higher security. In the proposed optimization approach all consumers, such as residential, industrial, and commercial one can involve simultaneously in the DSM techniques. The shifting technique is applied to the residential load, while demand bidding programme (DBP) is applied to the industrial and commercial loads. The proposed optimal approach is tested on a low voltage (LV) hybrid connected MG including different types of loads and distributed generators (DGs). The results reveal that the proposed optimization approaches reduce the operating cost of the MG, while there are no impacts of the DSM on the profit.

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 An Improved Multi-objective Differential Evolution Algorithm for Active Power Dispatch in Power System with Wind Farms
Nächstes Kapitel Unit Commitment Dynamic Unified Active and Reactive Power Dispatch of Microgrids with Integration of Electric Vehicles
Literatur
1.
Parisio, A., Rikos, E., Tzamalis, G., Glielmo, L.: Use of model predictive control for experimental microgrid optimization. Appl. Energy 115, 37–46 (2014)CrossRef
2.
Parisio, A., Rikos, E., Glielmo, L.: A model predictive control approach to microgrid operation optimization. IEEE Trans. Control Syst. Technol. 22(5), 1813–1827 (2014)CrossRef
3.
Palma-Behnke, R., Benavides, C., Lanas, F., Severino, B., Reyes, L., Llanos, J., Saez, D.: A microgrid energy management system based on the rolling horizon strategy. IEEE Trans. Smart Grid 4(2), 996–1006 (2013)CrossRef
4.
Tsikalakis, A.G., Hatziargyriou, N.D.: Centralized Control for Optimizing Microgrids Operation. IEEE Trans. Energy Convers. 23(1), 241–248 (2008)CrossRef
5.
Zhang, D., Li, S., Zeng, P., Zang, C.: Optimal microgrid control and power-flow study with different bidding policies by using powerworld simulator. IEEE Trans. Sustain. Energy 5(1), 282–292 (2014)CrossRef
6.
Logenthiran, T., Srinivasan, D., Shun, T.Z.: Demand side management in smart grid using heuristic optimization. IEEE Trans. Smart Grid 3(3), 1244–1252 (2012)CrossRef
7.
Kinhekar, N., Padhy, N.P., Li, F., Gupta, H.O.: Utility oriented demand side management using smart AC and micro DC grid cooperative. IEEE Trans. Power Syst. 31(2), 1151–1160 (2016)CrossRef
8.
Logenthiran, T., Srinivasan, D., Khambadkone, A.M., Aung, H.N.: Multiagent system for real-time operation of a microgrid in real-time digital simulator. IEEE Trans. Smart Grid 3(2), 925–933 (2012)CrossRef
9.
Tsagarakis, G., Camilla Thomson, R., Collin, A.J., Harrison, G.P., Kiprakis, A.E., McLaughlin, S.: Assessment of the cost and environmental impact of residential demand-side management. IEEE Trans. Ind. Appl. 52(3), 2486–2495 (2016)CrossRef
10.
Fossati, J.P., Galarza, A., Martín-villate, A., Font, L.: A method for optimal sizing energy storage systems for microgrids. Renew. Energy 77, 539–549 (2015)CrossRef
11.
Xie, K., Song, Y.H., Zhang, D., Nakanishi, Y., Nakazawa, C.: Calculation and decomposition of spot price using interior point nonlinear optimisation methods. Int. J. Electr. Power Energy Syst. 26(5), 349–356 (2004)CrossRef
12.
Tomić, J., Kempton, W.: Using fleets of electric-drive vehicles for grid support. J. Power Sources 168(2), 459–468 (2007)CrossRef
13.
Cobelo, I.: Active control of distribution networks, Ph.D. thesis, Manchester University (2005)
14.
Mark Bilton, G.S., Aunedi, M., Woolf, M.: Smart appliances for residential demand response. In: Low Carbon London Learning Lab. Imperial College London (2014)
15.
Santos, J.R., Lora, A.T., Expósito, A.G., Ramos, J.L.M.: Finding improved local minima of power system optimization problems by interior-point methods. IEEE Trans. Power Syst. 18(1), 238–244 (2003)CrossRef
16.
MICROGRIDS large scale integration of micro-generation to low voltage grids. In: Eu contract ENK5-CT-2002-00610, Tech. Annex (2004)
17.
Box, P.O., -Hut, F.: Online management of MicroGrid with battery storage using multiobjective optimization. In: Power Engineering, Energy and Electrical Drives, pp. 231–236 (2007)
18.
di Valdalbero, D.R.: External costs and their integration in energy costs. In: Europen Sustain Energy Policy Seminar (2006)
19.
García-Gusano, D., Cabal, H., Lechón, Y.: Evolution of NOx and SO2 emissions in Spain: Ceilings versus taxes. Clean Technol. Environ. Policy 17(7), 1997–2011 (2015)CrossRef
20.
Zakariazadeh, A., Jadid, S., Siano, P.: Smart microgrid energy and reserve scheduling with demand response using stochastic optimization. Electr. Power Energy Syst. 63, 523–533 (2014)CrossRef
Metadaten
Titel
Integration of the Demand Side Management with Active and Reactive Power Economic Dispatch of Microgrids
verfasst von
Mohammed K. Al-Saadi
Patrick C. K. Luk
John Economou
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_66