A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency Scenarios
This research presents a novel methodology based on data analysis for improving voltage stability in transmission systems. The proposal aims to determine a single distributed generator’s optimal location and sizing using the Fast Voltage Stability Index (FVSI) as the primary metric under <inline-...
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2025-05-01
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| author | Manuel Jaramillo Diego Carrión Filippos Perdikos Luis Tipan |
| author_facet | Manuel Jaramillo Diego Carrión Filippos Perdikos Luis Tipan |
| author_sort | Manuel Jaramillo |
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| description | This research presents a novel methodology based on data analysis for improving voltage stability in transmission systems. The proposal aims to determine a single distributed generator’s optimal location and sizing using the Fast Voltage Stability Index (FVSI) as the primary metric under <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>N</mi><mo>−</mo><mn>1</mn></mrow></semantics></math></inline-formula> contingency conditions. The developed strategy systematically identifies the most critical transmission lines close to instability through a frequency analysis of the FVSI in the base case and across multiple contingency scenarios. Subsequently, the weak buses associated with the most critical line are determined, on which critical load increases are simulated. The Distributed Generator (DG) sizing and location parameters are then optimized through a statistical analysis of the inflection point and the rate of change of the FVSI statistical parameters. The methodology is validated in three case studies: IEEE systems with 14, 30, and 118 buses, demonstrating its scalability and effectiveness. The results show significant reductions in FVSI values and notable improvements in voltage profiles under stress and contingency conditions. For example, in the 30-bus IEEE system, the average FVSI for all contingency scenarios was reduced by 26% after applying the optimal solution. At the same time, the voltage profiles even exceeded those of the base case. This strategy represents a significant contribution, as it is capable of improving the stability of the electrical power system in all <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>N</mi><mo>−</mo><mn>1</mn></mrow></semantics></math></inline-formula> contingency scenarios with overload at critical nodes. Using a single DG as a low-cost and highly effective corrective measure, the proposed approach outperforms conventional solutions through statistical analysis and a data-centric approach. |
| format | Article |
| id | doaj-art-7ca2a6ae75064df4a8d0a5f9fc3f2828 |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Energies |
| spelling | doaj-art-7ca2a6ae75064df4a8d0a5f9fc3f28282025-08-20T02:33:59ZengMDPI AGEnergies1996-10732025-05-011810246610.3390/en18102466A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency ScenariosManuel Jaramillo0Diego Carrión1Filippos Perdikos2Luis Tipan3Smart Grid Research Group—GIREI (Spanish Acronym), Electrical Engineering Department, Salesian Polytechnic University, Quito EC170702, EcuadorSmart Grid Research Group—GIREI (Spanish Acronym), Electrical Engineering Department, Salesian Polytechnic University, Quito EC170702, EcuadorOpenchip & Software Technologies SL, 08034 Barcelona, SpainSmart Grid Research Group—GIREI (Spanish Acronym), Electrical Engineering Department, Salesian Polytechnic University, Quito EC170702, EcuadorThis research presents a novel methodology based on data analysis for improving voltage stability in transmission systems. The proposal aims to determine a single distributed generator’s optimal location and sizing using the Fast Voltage Stability Index (FVSI) as the primary metric under <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>N</mi><mo>−</mo><mn>1</mn></mrow></semantics></math></inline-formula> contingency conditions. The developed strategy systematically identifies the most critical transmission lines close to instability through a frequency analysis of the FVSI in the base case and across multiple contingency scenarios. Subsequently, the weak buses associated with the most critical line are determined, on which critical load increases are simulated. The Distributed Generator (DG) sizing and location parameters are then optimized through a statistical analysis of the inflection point and the rate of change of the FVSI statistical parameters. The methodology is validated in three case studies: IEEE systems with 14, 30, and 118 buses, demonstrating its scalability and effectiveness. The results show significant reductions in FVSI values and notable improvements in voltage profiles under stress and contingency conditions. For example, in the 30-bus IEEE system, the average FVSI for all contingency scenarios was reduced by 26% after applying the optimal solution. At the same time, the voltage profiles even exceeded those of the base case. This strategy represents a significant contribution, as it is capable of improving the stability of the electrical power system in all <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>N</mi><mo>−</mo><mn>1</mn></mrow></semantics></math></inline-formula> contingency scenarios with overload at critical nodes. Using a single DG as a low-cost and highly effective corrective measure, the proposed approach outperforms conventional solutions through statistical analysis and a data-centric approach.https://www.mdpi.com/1996-1073/18/10/2466voltage stability enhancementcontingency analysis (<i>N</i> − 1)fast voltage stability indexdata-driven DG placementpower system resilience |
| spellingShingle | Manuel Jaramillo Diego Carrión Filippos Perdikos Luis Tipan A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency Scenarios Energies voltage stability enhancement contingency analysis (<i>N</i> − 1) fast voltage stability index data-driven DG placement power system resilience |
| title | A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency Scenarios |
| title_full | A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency Scenarios |
| title_fullStr | A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency Scenarios |
| title_full_unstemmed | A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency Scenarios |
| title_short | A Data-Driven Approach to Voltage Stability Support via FVSI-Based Distributed Generator Placement in Contingency Scenarios |
| title_sort | data driven approach to voltage stability support via fvsi based distributed generator placement in contingency scenarios |
| topic | voltage stability enhancement contingency analysis (<i>N</i> − 1) fast voltage stability index data-driven DG placement power system resilience |
| url | https://www.mdpi.com/1996-1073/18/10/2466 |
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