Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment
This paper presents a distributed optimization strategy for reactive power–voltage control in distribution networks with high photovoltaic (PV) penetration under limited sensor deployment scenarios. To address voltage violations and minimize network power losses, a novel distributed optimization fra...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/14/3598 |
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| author | Xun Lu Junlei Liu Xinmiao Liu Jun Liu Lingxue Lin |
| author_facet | Xun Lu Junlei Liu Xinmiao Liu Jun Liu Lingxue Lin |
| author_sort | Xun Lu |
| collection | DOAJ |
| description | This paper presents a distributed optimization strategy for reactive power–voltage control in distribution networks with high photovoltaic (PV) penetration under limited sensor deployment scenarios. To address voltage violations and minimize network power losses, a novel distributed optimization framework is developed that utilizes selective nodal measurements from PV-integrated nodes and critical T-junction locations, coupled with inter-node communication for information exchange. The methodology integrates an adaptive step size algorithm within a dynamic projected primal–dual distributed optimization framework, eliminating manual parameter tuning requirements while ensuring theoretical convergence guarantees through Lyapunov stability analysis. Comprehensive validation on the IEEE 33-bus distribution test system demonstrates that the proposed strategy achieves significant performance improvements. The distributed control framework reduces measurement infrastructure requirements while maintaining near-optimal performance, demonstrating superior economic efficiency and operational reliability. These results establish the practical viability of the proposed approach for real-world distribution network applications with high renewable energy integration, providing a cost-effective solution for voltage regulation under incomplete observability conditions. |
| format | Article |
| id | doaj-art-e76c72274647413f9c659a6f8f540a59 |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-e76c72274647413f9c659a6f8f540a592025-08-20T02:45:45ZengMDPI AGEnergies1996-10732025-07-011814359810.3390/en18143598Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor DeploymentXun Lu0Junlei Liu1Xinmiao Liu2Jun Liu3Lingxue Lin4Department of Power Grid Planning, Guangdong Power Grid Co., Ltd., Guangzhou 510699, ChinaDepartment of Power Grid Planning, Guangdong Power Grid Co., Ltd., Guangzhou 510699, ChinaDepartment of Power Grid Planning, Guangdong Power Grid Co., Ltd., Guangzhou 510699, ChinaSchool of Electric Power Engineering, South China University of Technology, Guangzhou 510641, ChinaSchool of Electric Power Engineering, South China University of Technology, Guangzhou 510641, ChinaThis paper presents a distributed optimization strategy for reactive power–voltage control in distribution networks with high photovoltaic (PV) penetration under limited sensor deployment scenarios. To address voltage violations and minimize network power losses, a novel distributed optimization framework is developed that utilizes selective nodal measurements from PV-integrated nodes and critical T-junction locations, coupled with inter-node communication for information exchange. The methodology integrates an adaptive step size algorithm within a dynamic projected primal–dual distributed optimization framework, eliminating manual parameter tuning requirements while ensuring theoretical convergence guarantees through Lyapunov stability analysis. Comprehensive validation on the IEEE 33-bus distribution test system demonstrates that the proposed strategy achieves significant performance improvements. The distributed control framework reduces measurement infrastructure requirements while maintaining near-optimal performance, demonstrating superior economic efficiency and operational reliability. These results establish the practical viability of the proposed approach for real-world distribution network applications with high renewable energy integration, providing a cost-effective solution for voltage regulation under incomplete observability conditions.https://www.mdpi.com/1996-1073/18/14/3598distributed optimization strategyvoltage regulationPV-integrated power systemsadaptive step sizeimproved dynamic projected primal–dual distributed algorithm |
| spellingShingle | Xun Lu Junlei Liu Xinmiao Liu Jun Liu Lingxue Lin Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment Energies distributed optimization strategy voltage regulation PV-integrated power systems adaptive step size improved dynamic projected primal–dual distributed algorithm |
| title | Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment |
| title_full | Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment |
| title_fullStr | Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment |
| title_full_unstemmed | Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment |
| title_short | Distributed Optimization Strategy for Voltage Regulation in PV-Integrated Power Systems with Limited Sensor Deployment |
| title_sort | distributed optimization strategy for voltage regulation in pv integrated power systems with limited sensor deployment |
| topic | distributed optimization strategy voltage regulation PV-integrated power systems adaptive step size improved dynamic projected primal–dual distributed algorithm |
| url | https://www.mdpi.com/1996-1073/18/14/3598 |
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