An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm

Bins; Controllers; Fueling; Gas generators; Global optimization; Health; Integration; Learning algorithms; Optimization; Particle swarm optimization (PSO); Power generation; Reliability; Renewable energy resources; Scheduling; Wind; Backtracking search algorithms; Micro grid; Optimal scheduling; Sch...

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Main Authors: Abdolrasol M.G.M., Hannan M.A., Mohamed A., Amiruldin U.A.U., Abidin I.B.Z., Uddin M.N.
Other Authors: 35796848700
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-238322023-05-29T14:52:14Z An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm Abdolrasol M.G.M. Hannan M.A. Mohamed A. Amiruldin U.A.U. Abidin I.B.Z. Uddin M.N. 35796848700 7103014445 57195440511 26422804600 35606640500 55663372800 Bins; Controllers; Fueling; Gas generators; Global optimization; Health; Integration; Learning algorithms; Optimization; Particle swarm optimization (PSO); Power generation; Reliability; Renewable energy resources; Scheduling; Wind; Backtracking search algorithms; Micro grid; Optimal scheduling; Scheduling controllers; Virtual power plants; Wind speed; Power control This paper presents a novel binary backtracking search algorithm (BBSA) for an optimal scheduling controller applied to the IEEE 14-bus test system for controlling distributed generators (DGs) in microgrids (MGs) in the form of virtual power plant (VPP) toward 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 h. 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 fitness function is generated based on real conditions such as solar irradiation and wind speed and preparation of battery charge/discharges, fuel states and demand of the specific hour. The obtained results show that the BBSA algorithm provides the best schedule to control DGs ON and OFF based on controller decision. Results obtained from the BBSA are compared with binary particle swarm optimization in terms of objective function and power saving to validate the developed controller. The developed BBSA optimization algorithm minimizes the power generation cost, reduces power losses, delivers reliable and 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. � 1972-2012 IEEE. Final 2023-05-29T06:52:14Z 2023-05-29T06:52:14Z 2018 Conference Paper 10.1109/TIA.2018.2797121 2-s2.0-85040985677 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040985677&doi=10.1109%2fTIA.2018.2797121&partnerID=40&md5=245e53026e24d9788bcb25a6a872142a https://irepository.uniten.edu.my/handle/123456789/23832 54 3 2834 2844 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Bins; Controllers; Fueling; Gas generators; Global optimization; Health; Integration; Learning algorithms; Optimization; Particle swarm optimization (PSO); Power generation; Reliability; Renewable energy resources; Scheduling; Wind; Backtracking search algorithms; Micro grid; Optimal scheduling; Scheduling controllers; Virtual power plants; Wind speed; Power control
author2 35796848700
author_facet 35796848700
Abdolrasol M.G.M.
Hannan M.A.
Mohamed A.
Amiruldin U.A.U.
Abidin I.B.Z.
Uddin M.N.
format Conference Paper
author Abdolrasol M.G.M.
Hannan M.A.
Mohamed A.
Amiruldin U.A.U.
Abidin I.B.Z.
Uddin M.N.
spellingShingle Abdolrasol M.G.M.
Hannan M.A.
Mohamed A.
Amiruldin U.A.U.
Abidin I.B.Z.
Uddin M.N.
An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm
author_sort Abdolrasol M.G.M.
title An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm
title_short An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm
title_full An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm
title_fullStr An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm
title_full_unstemmed An Optimal Scheduling Controller for Virtual Power Plant and Microgrid Integration Using the Binary Backtracking Search Algorithm
title_sort optimal scheduling controller for virtual power plant and microgrid integration using the binary backtracking search algorithm
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806426209907638272
score 13.188404