An optimal scheduling controller for virtual power plant and microgrid integration using binary backtracking search algorithm

M. G.M. Abdolrasol, M. A. Hannan, A. Mohamed, Ungku Anisa Ungku Amirulddin Al Amin, Izham Zainal Abidin, M. N. Uddin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

We propose a novel binary backtracking search algorithm (BBSA) based optimal scheduling controller in an IEEE 14 bus system for controlling microgrids (MGs) in the form of virtual power plant (VPP) towards sustainable renewable energy sources integration. The VPP and MGs models are simulated and tested based on real parameters and loads data recorded in Perlis, Malaysia employed on each bus of the system for 24 hours. BBSA optimization algorithm provides the best binary fitness function i.e. global minimum fitness for finding the best cell to generate the optimal schedule. The obtained results show that the BBSA algorithm provides the best schedule for the energy management turning DGs ON and OFF in the MGs with the consideration of real weather conditions for solar irradiation and wind speed, battery charge/discharges, fuel states and demand of the specific hour. The developed BBSA optimization algorithm minimizes the power generation cost, reduces power losses, delivers the reliable high-quality power to the loads and integrates priority based sustainable MGs into the grid. Thus, VPP can enable efficient integration of DGs and MGs into the grid by balancing their variability.

Original languageEnglish
Title of host publication2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781509048946
DOIs
Publication statusPublished - 08 Nov 2017
Event2017 IEEE Industry Applications Society Annual Meeting, IAS 2017 - Cincinnati, United States
Duration: 01 Oct 201705 Oct 2017

Publication series

Name2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
Volume2017-January

Other

Other2017 IEEE Industry Applications Society Annual Meeting, IAS 2017
CountryUnited States
CityCincinnati
Period01/10/1705/10/17

Fingerprint

Microgrid
Optimal Scheduling
Backtracking
Power Plant
Search Algorithm
Power plants
Scheduling
Binary
Controller
Controllers
Optimization Algorithm
Schedule
Grid
Power Quality
Energy Management
Malaysia
Renewable Energy
Wind Speed
Global Minimum
Fitness Function

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Control and Optimization
  • Energy Engineering and Power Technology
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Abdolrasol, M. G. M., Hannan, M. A., Mohamed, A., Ungku Amirulddin Al Amin, U. A., Zainal Abidin, I., & Uddin, M. N. (2017). An optimal scheduling controller for virtual power plant and microgrid integration using binary backtracking search algorithm. In 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017 (pp. 1-8). (2017 IEEE Industry Applications Society Annual Meeting, IAS 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IAS.2017.8101737
Abdolrasol, M. G.M. ; Hannan, M. A. ; Mohamed, A. ; Ungku Amirulddin Al Amin, Ungku Anisa ; Zainal Abidin, Izham ; Uddin, M. N. / An optimal scheduling controller for virtual power plant and microgrid integration using binary backtracking search algorithm. 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1-8 (2017 IEEE Industry Applications Society Annual Meeting, IAS 2017).
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abstract = "We propose a novel binary backtracking search algorithm (BBSA) based optimal scheduling controller in an IEEE 14 bus system for controlling microgrids (MGs) in the form of virtual power plant (VPP) towards sustainable renewable energy sources integration. The VPP and MGs models are simulated and tested based on real parameters and loads data recorded in Perlis, Malaysia employed on each bus of the system for 24 hours. BBSA optimization algorithm provides the best binary fitness function i.e. global minimum fitness for finding the best cell to generate the optimal schedule. The obtained results show that the BBSA algorithm provides the best schedule for the energy management turning DGs ON and OFF in the MGs with the consideration of real weather conditions for solar irradiation and wind speed, battery charge/discharges, fuel states and demand of the specific hour. The developed BBSA optimization algorithm minimizes the power generation cost, reduces power losses, delivers the reliable high-quality power to the loads and integrates priority based sustainable MGs into the grid. Thus, VPP can enable efficient integration of DGs and MGs into the grid by balancing their variability.",
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Abdolrasol, MGM, Hannan, MA, Mohamed, A, Ungku Amirulddin Al Amin, UA, Zainal Abidin, I & Uddin, MN 2017, An optimal scheduling controller for virtual power plant and microgrid integration using binary backtracking search algorithm. in 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-8, 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017, Cincinnati, United States, 01/10/17. https://doi.org/10.1109/IAS.2017.8101737

An optimal scheduling controller for virtual power plant and microgrid integration using binary backtracking search algorithm. / Abdolrasol, M. G.M.; Hannan, M. A.; Mohamed, A.; Ungku Amirulddin Al Amin, Ungku Anisa; Zainal Abidin, Izham; Uddin, M. N.

2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1-8 (2017 IEEE Industry Applications Society Annual Meeting, IAS 2017; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abdolrasol MGM, Hannan MA, Mohamed A, Ungku Amirulddin Al Amin UA, Zainal Abidin I, Uddin MN. An optimal scheduling controller for virtual power plant and microgrid integration using binary backtracking search algorithm. In 2017 IEEE Industry Applications Society Annual Meeting, IAS 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 1-8. (2017 IEEE Industry Applications Society Annual Meeting, IAS 2017). https://doi.org/10.1109/IAS.2017.8101737