Determining the Optimal Location and Number of Voltage Dip Monitoring Devices Using the Binary Bat Algorithm
Abstract
:1. Introduction
- Introduction of a new objective function including constraints (optimization problem) for determining the optimal number and location of voltage dip measuring devices.
- Application of the binary bat algorithm for solving the proposed optimization problem.
- Verification of the proposed optimization methodology by the traditional mixed-integer linear programming algorithm.
2. Method for the Optimal Number and Location of Power Quality Monitors
2.1. The Existing Method Based on the Monitor Reach Area
2.2. Exposed Area
2.3. Proposed Objective Function
2.4. Bat Algorithm
3. Methodology for Solving the Proposed Optimization Model
4. Verification and Testing of the Proposed Method by Using the IEEE 39 Buses Test System
4.1. Optimal Location of Measuring Devices for Three-Phase Short Circuits
4.2. Optimal Location of Measuring Devices for Single-Phase Short Circuits
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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Busbars | Coefficient | Busbars | Coefficient | Busbars | Coefficient | Busbars | Coefficient |
---|---|---|---|---|---|---|---|
1 | 0.18 | 11 | 0.46 | 21 | 0.49 | 31 | 0.23 |
2 | 0.53 | 12 | 0.46 | 22 | 0.35 | 32 | 0.24 |
3 | 0.67 | 13 | 0.48 | 23 | 0.35 | 33 | 0.13 |
4 | 0.56 | 14 | 0.58 | 24 | 0.57 | 34 | 0.08 |
5 | 0.48 | 15 | 0.58 | 25 | 0.49 | 35 | 0.21 |
6 | 0.47 | 16 | 0.61 | 26 | 0.66 | 36 | 0.16 |
7 | 0.46 | 17 | 0.70 | 27 | 0.76 | 37 | 0.17 |
8 | 0.46 | 18 | 0.67 | 28 | 0.45 | 38 | 0.25 |
9 | 0.27 | 19 | 0.31 | 29 | 0.41 | 39 | 0.03 |
10 | 0.44 | 20 | 0.20 | 30 | 0.15 | - | - |
Binary Bat Algorithm | GLPK | |
---|---|---|
Bus | Weighted Coefficient | Bus |
2 | 0.53 | 2 |
6 | 0.47 | 8 |
27 | 0.76 | 20 |
34 | 0.08 | 27 |
36 | 0.16 | 36 |
Total weighted coefficient | 2 | - |
Binary Bat Algorithm | GLPK | |
---|---|---|
Bus | Weighted Coefficient | Bus |
12 | 0 | 12 |
20 | 0 | 20 |
25 | 0.83 | 30 |
30 | 0 | 31 |
31 | 0 | 32 |
32 | 0 | 33 |
33 | 0 | 34 |
34 | 0 | 35 |
35 | 0 | 36 |
36 | 0 | 37 |
37 | 0 | 38 |
38 | 0 | 39 |
Total weighted coefficient | 0.83 | - |
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Šipoš, M.; Klaić, Z.; Nyarko, E.K.; Fekete, K. Determining the Optimal Location and Number of Voltage Dip Monitoring Devices Using the Binary Bat Algorithm. Energies 2021, 14, 255. https://doi.org/10.3390/en14010255
Šipoš M, Klaić Z, Nyarko EK, Fekete K. Determining the Optimal Location and Number of Voltage Dip Monitoring Devices Using the Binary Bat Algorithm. Energies. 2021; 14(1):255. https://doi.org/10.3390/en14010255
Chicago/Turabian StyleŠipoš, Mario, Zvonimir Klaić, Emmanuel Karlo Nyarko, and Krešimir Fekete. 2021. "Determining the Optimal Location and Number of Voltage Dip Monitoring Devices Using the Binary Bat Algorithm" Energies 14, no. 1: 255. https://doi.org/10.3390/en14010255
APA StyleŠipoš, M., Klaić, Z., Nyarko, E. K., & Fekete, K. (2021). Determining the Optimal Location and Number of Voltage Dip Monitoring Devices Using the Binary Bat Algorithm. Energies, 14(1), 255. https://doi.org/10.3390/en14010255