ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation
Cost effectiveness; Cost reduction; Electric power transmission networks; Learning algorithms; Neural networks; Renewable energy resources; Scheduling; Wind; Backtracking search algorithms; Charging/discharging; Correlation coefficient; Mean absolute error; Optimal scheduling; Optimization algorithm...
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-265112023-05-29T17:11:21Z ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation Hannan M.A. Abdolrasol M.G. Mohamed R. Al-Shetwi A. Ker P. Begum R. Muttaqi K. 7103014445 35796848700 7005169066 57004922700 37461740800 14007780000 55582332500 Cost effectiveness; Cost reduction; Electric power transmission networks; Learning algorithms; Neural networks; Renewable energy resources; Scheduling; Wind; Backtracking search algorithms; Charging/discharging; Correlation coefficient; Mean absolute error; Optimal scheduling; Optimization algorithms; Renewable energy source; Virtual power plants (VPP); Electric power system control This article reports an artificial neural network (ANN)-based binary backtracking search algorithm (BBSA) for optimal scheduling controller applied on IEEE 14-bus system for controlling microgrids (MGs) formed virtual power plant (VPP) toward sustainable renewable energy sources (RESs) integration. The model of VPP was simulated and validated based on actual parameters and load data reported in Perlis, Malaysia. BBSA optimization algorithm offers the best binary fitness function to find the best cell. It creates the optimum scheduling using the actual data for wind speed, solar radiation, fuel conditions, battery charging/discharging, and specific hour demand. The developed ANN-based BBSA search for the optimal ANN parameters architecture, e.g., (the number of neurons and learning rate) that enhanced the ANN controller to predict the optimal schedules to regulate power-sharing via prioritizing the utilization of RES in place of the national grid purchases. The results of the optimal on/off status prediction of the 25 DGs showed that the ANN-BBSA gives a mean absolute error (MAE) of 6.2 � 10-3 with a unity correlation coefficient. The results showed a significant reduction in the cost and emission by 41.88% and 40.7%, respectively. Thus, the developed algorithms reduced the energy cost while delivered reliable power toward grid decarbonization. � 1972-2012 IEEE. Final 2023-05-29T09:11:20Z 2023-05-29T09:11:20Z 2021 Article 10.1109/TIA.2021.3100321 2-s2.0-85111564673 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111564673&doi=10.1109%2fTIA.2021.3100321&partnerID=40&md5=6b183b7e5bf72b836ccce67f2918de25 https://irepository.uniten.edu.my/handle/123456789/26511 57 6 5603 5613 Institute of Electrical and Electronics Engineers Inc. Scopus |
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| description |
Cost effectiveness; Cost reduction; Electric power transmission networks; Learning algorithms; Neural networks; Renewable energy resources; Scheduling; Wind; Backtracking search algorithms; Charging/discharging; Correlation coefficient; Mean absolute error; Optimal scheduling; Optimization algorithms; Renewable energy source; Virtual power plants (VPP); Electric power system control |
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7103014445 Hannan M.A. Abdolrasol M.G. Mohamed R. Al-Shetwi A. Ker P. Begum R. Muttaqi K. |
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Article |
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Hannan M.A. Abdolrasol M.G. Mohamed R. Al-Shetwi A. Ker P. Begum R. Muttaqi K. |
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Hannan M.A. Abdolrasol M.G. Mohamed R. Al-Shetwi A. Ker P. Begum R. Muttaqi K. ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation |
| author_sort |
Hannan M.A. |
| title |
ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation |
| title_short |
ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation |
| title_full |
ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation |
| title_fullStr |
ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation |
| title_full_unstemmed |
ANN-Based Binary Backtracking Search Algorithm for VPP Optimal Scheduling and Cost-Effective Evaluation |
| title_sort |
ann-based binary backtracking search algorithm for vpp optimal scheduling and cost-effective evaluation |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806423461716819968 |