Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems
This paper presents a voltage sensitivity analysis with respect to the real power injected with renewable energies to determine the optimal integration of distributed generation (DG) in distribution systems (DS). The best nodes where the power injections improve voltages magnitudes complying with th...
- Autores:
-
Cabana, Katherine
Candelo, John
Castillo, Rafael
De-La-Hoz-Franco, Emiro
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/6092
- Acceso en línea:
- https://hdl.handle.net/11323/6092
https://repositorio.cuc.edu.co/
- Palabra clave:
- Voltage magnitudes
Sensitivity analysis
Distribution networks
Distributed generation
Metaheuristic algorithms
- Rights
- openAccess
- License
- CC0 1.0 Universal
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Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems |
| title |
Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems |
| spellingShingle |
Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems Voltage magnitudes Sensitivity analysis Distribution networks Distributed generation Metaheuristic algorithms |
| title_short |
Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems |
| title_full |
Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems |
| title_fullStr |
Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems |
| title_full_unstemmed |
Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems |
| title_sort |
Voltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systems |
| dc.creator.fl_str_mv |
Cabana, Katherine Candelo, John Castillo, Rafael De-La-Hoz-Franco, Emiro |
| dc.contributor.author.spa.fl_str_mv |
Cabana, Katherine Candelo, John Castillo, Rafael De-La-Hoz-Franco, Emiro |
| dc.subject.spa.fl_str_mv |
Voltage magnitudes Sensitivity analysis Distribution networks Distributed generation Metaheuristic algorithms |
| topic |
Voltage magnitudes Sensitivity analysis Distribution networks Distributed generation Metaheuristic algorithms |
| description |
This paper presents a voltage sensitivity analysis with respect to the real power injected with renewable energies to determine the optimal integration of distributed generation (DG) in distribution systems (DS). The best nodes where the power injections improve voltages magnitudes complying with the constraints are determined. As it is a combinatorial problem, particle swarm optimization (PSO) and simulated annealing (SA) were used to change injections from 10% to 60% of the total power load using solar and wind generators and find the candidate nodes for installing power sources. The method was tested using the 33-node, 69-node and 118-node radial distribution networks. The results showed that the best nodes for injecting real power with renewable energies were selected for the distribution network by using the voltage sensitivity analysis. Algorithms found the best nodes for the three radial distribution networks with similar values in the maximum injection of real power, suggesting that this value maintains for all the power system cases. The injections applied to the different nodes showed that voltage magnitudes increase significantly, especially when exceeding the maximum penetration of DG. The test showed that some nodes support injections up to the limits, but the voltages increase considerably on all nodes. |
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2019 |
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2019-02 |
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2020-03-10T13:07:20Z |
| dc.date.available.none.fl_str_mv |
2020-03-10T13:07:20Z |
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Artículo de revista |
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Text |
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2088-8708 |
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https://hdl.handle.net/11323/6092 |
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DOI: 10.11591/ijece.v9i1.pp55-65 |
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Corporación Universidad de la Costa |
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REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
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2088-8708 DOI: 10.11591/ijece.v9i1.pp55-65 Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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https://hdl.handle.net/11323/6092 https://repositorio.cuc.edu.co/ |
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eng |
| language |
eng |
| dc.relation.references.spa.fl_str_mv |
[1] P. Suresh Babu and R. Madhan Mohan, “Optimal Performance Enhancement of DG for Loss Reduction using Fuzzy and Harmony Search Algorithm,” in 2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO), 2015, pp. 1–5. [2] Y. O. Gummadi Srinivasa Rao, “Voltage Profile Improvement of Distribution System using Distributed Generating Units,” Int. J. Electr. Comput. Eng., vol. 3, no. 2088–8708, pp. 337–343, 2013. [3] A. Yadav and L. Srivastava, “Optimal Placement of Distributed Generation: An Overview and Key Issues,” in 2014 International Conference on Power Signals Control and Computations (EPSCICON), 2014, pp. 1–6. [4] M. P.S. and S. Hemamalini, “Optimal Siting of Distributed Generators in a Distribution Network using Artificial Immune System,” Int. J. Electr. Comput. Eng., 2017. [5] A. A. Abou El-Ela, A. M. Azmay, and A. A. Shammah, “Optimal Sitting and Sizing of Distributed Generations In Distribution Networks Using Heuristic Algorithm,” in 2015 50th International Universities Power Engineering Conference (UPEC), 2015, pp. 1–7. [6] and A. G. Hocine Ait-Saadi1, Jean-Yves Chouinard2, “A PAPR Reduction for OFDM Signals Based on Self-Adaptive Multipopulation DE algorithm Hocine,” Int. J. Electr. Comput. Eng., 2017. [7] R. S. Al Abri, E. F. El-Saadany, and Y. M. Atwa, “Optimal Placement and Sizing Method to Improve the Voltage Stability Margin in a Distribution System Using Distributed Generation,” IEEE Trans. Power Syst., vol. 28, no. 1, pp. 326–334, Feb. 2013. [8] H. W. K. M. Amarasekara, L. Meegahapola, A. P. Agalgaonkar, and S. Perera, “Impact of Renewable Power Integration On VQ Stability Margin,” in 2013 Australasian Universities Power Engineering Conference (AUPEC), 2013, pp. 1–6. [9] R. S. Al Abri, “Voltage Stability Analysis With High Distributed Generation Penetration,” Waterloo, 2012. [10] L. Wei and Zhang Haiyan, “Allocation of Distributed Generations Based on Improved Particle Swarm Optimization Algorithm,” Int. Conf. Meas. Inf. Control, 2013. [11] W. S. Ke-yan Liu, Kaiyuan He, “Multiple-Objetive DG Optimal Sizing In Distribution System Using An Improverd PSO Algorith,” IEEE Trans. Automat. Contr., pp. 1–4, 2013. [12] S. S. Musa, H. ; Adamu, “Enhanced PSO Based Multi-Objective Distributed Generation Placement And Sizing For Power Loss Reduction And Voltage Stability Index Improvement,” IEEE Trans. Automat. Contr., pp. 1–6, 2013. [13] M. Shekeew, M. Elshahed, and M. Elmarsafawy, “Impact of Optimal Location, Size And Number Of Distributed Generation Units On The Performance Of Radial Distribution Systems,” in 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), 2016, pp. 1–6. [14] D. Jia, L. Hu, K. Liu, Y. Liu, X. Meng, and W. Sheng, “Simplified Probabilistic Voltage Stability Evaluation Considering Variable Renewable Distributed Generation In Distribution Systems,” IET Gener. Transm. Distrib., vol. 9, no. 12, pp. 1464–1473, Sep. 2015. [15] J. Silva et al., “A 75 Bus Bars Model To Evaluate The Steady State Operation Of A Sub-Transmission Electrical Power Grid,” Espacios, 2016. [16] K. Cabana, “Statistical Analysis of Voltage Sensitivity in Distribution Systems Integrating DG,” IEEE Latin America Transactions. 2016. [17] Z. Garcia Sánchez, J. A. González Cueto, G. Quintana de Basterra, and J. G. Boza Valerino, “Implementación de Un Estudio De Estabilidad De La Tensión Al Paquete De Programas Psx. 2.87,” Ing. Energética, vol. 34, no. 1, pp. 33–42. [18] K. Morison, X. Wang, A. Moshref, and A. Edris, “Identification of Voltage Control Areas And Reactive Power Reserve; An Advancement In On-Line Voltage Security Assessment,” in 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008, pp. 1–7. [19] R. A. Walling, R. Saint, R. C. Dugan, J. Burke, and L. A. Kojovic, “Summary of Distributed Resources Impact on Power Delivery Systems,” IEEE Trans. Power Deliv., vol. 23, no. 3, pp. 1636–1644, Jul. 2008. [20] H. Zeineldin, E. El-saadany, and M. A. Salama, “Distributed Generation Micro-Grid Operation: Control and Protection,” in 2006 Power Systems Conference: Advanced Metering, Protection, Control, Communication, and Distributed Resources, 2006, pp. 105–111. [21] P. C. Lu Zhang, Wei Tang, Muke Bai, “Analysis of Distributed Generation Influences On The Voltage Limit Violation Probability Of Distribution Line,” Energy Power Eng., vol. 5, pp. 756–762, 2013. [22] Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama, and R. Seethapathy, “Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization,” IEEE Trans. Power Syst., vol. 25, no. 1, pp. 360–370, Feb. 2010. [23] Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama, and R. Seethapathy, “Distribution System Loss Minimization Using Optimal DG Mix,” in 2009 IEEE Power & Energy Society General Meeting, 2009, pp. 1–6. [24] M. H. Albadi and E. F. El-Saadany, “Novel Method For Estimating the CF of Variable Speed Wind Turbines,” in 2009 IEEE Power & Energy Society General Meeting, 2009, pp. 1–6. [25] M. H. Albadi and E. F. El-Saadany, “Wind Turbines Capacity Factor Modeling—A Novel Approach,” IEEE Trans. Power Syst., vol. 24, no. 3, pp. 1637–1638, Aug. 2009. [26] P. Monzón, Artenstein Michel, and J. Alonso, “Evaluación De La Estabilidad De Tensión En Una Red De Potencia Con Base A Criterios Derivados De La Teoría De La Bifurcación Más Cercana,” Aerosp. Eng. Control Syst. Eng. Electr. Eng., 2014. [27] A. N. B. Alsammak, “Bifurcation and Voltage Collapse In The Electrical Power Systems,” Al_Rafidain Eng., vol. vol.13, pp. 25–41, 2005. [28] S. A. Taher and S. A. Afsari, “Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm,” Math. Probl. Eng., vol. 2012, 2012. [29] M. E. Baran and F. F. Wu, “Network Reconfiguration In Distribution Systems For Loss Reduction And Load Balancing,” IEEE Trans. Power Deliv., vol. 4, no. 2, pp. 1401–1407, Apr. 1989. [30] P. Phonrattanasak and N. Leeprechanon, “Optimal Location of Fast Charging Station on Residential Distribution Grid - Volume 3 Number 6 (Dec. 2012) - IJIMT,” Int. J. Innov. Manag. Technol., vol. 3, no. 6, pp. 675–681, 2012. [31] S. Sultana and P. K. Roy, “Multi-Objective Quasi-Oppositional Teaching Learning Based Optimization For Optimal Location Of Distributed Generator In Radial Distribution Systems,” Int. J. Electr. Power Energy Syst., vol. 63, pp. 534–545, 2014. |
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Cabana, KatherineCandelo, JohnCastillo, RafaelDe-La-Hoz-Franco, Emiro2020-03-10T13:07:20Z2020-03-10T13:07:20Z2019-022088-8708https://hdl.handle.net/11323/6092DOI: 10.11591/ijece.v9i1.pp55-65Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/This paper presents a voltage sensitivity analysis with respect to the real power injected with renewable energies to determine the optimal integration of distributed generation (DG) in distribution systems (DS). The best nodes where the power injections improve voltages magnitudes complying with the constraints are determined. As it is a combinatorial problem, particle swarm optimization (PSO) and simulated annealing (SA) were used to change injections from 10% to 60% of the total power load using solar and wind generators and find the candidate nodes for installing power sources. The method was tested using the 33-node, 69-node and 118-node radial distribution networks. The results showed that the best nodes for injecting real power with renewable energies were selected for the distribution network by using the voltage sensitivity analysis. Algorithms found the best nodes for the three radial distribution networks with similar values in the maximum injection of real power, suggesting that this value maintains for all the power system cases. The injections applied to the different nodes showed that voltage magnitudes increase significantly, especially when exceeding the maximum penetration of DG. The test showed that some nodes support injections up to the limits, but the voltages increase considerably on all nodes.Cabana, KatherineCandelo, JohnCastillo, RafaelDe-La-Hoz-Franco, Emiro-will be generated-orcid-0000-0002-4926-7414-600engInternational Journal of Electrical and Computer EngineeringCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Voltage magnitudesSensitivity analysisDistribution networksDistributed generationMetaheuristic algorithmsVoltage sensitivity analysis to determine the optimal integration of distributed generation in distribution systemsArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion[1] P. Suresh Babu and R. Madhan Mohan, “Optimal Performance Enhancement of DG for Loss Reduction using Fuzzy and Harmony Search Algorithm,” in 2015 International Conference on Electrical, Electronics, Signals, Communication and Optimization (EESCO), 2015, pp. 1–5.[2] Y. O. Gummadi Srinivasa Rao, “Voltage Profile Improvement of Distribution System using Distributed Generating Units,” Int. J. Electr. Comput. Eng., vol. 3, no. 2088–8708, pp. 337–343, 2013.[3] A. Yadav and L. Srivastava, “Optimal Placement of Distributed Generation: An Overview and Key Issues,” in 2014 International Conference on Power Signals Control and Computations (EPSCICON), 2014, pp. 1–6.[4] M. P.S. and S. Hemamalini, “Optimal Siting of Distributed Generators in a Distribution Network using Artificial Immune System,” Int. J. Electr. Comput. Eng., 2017.[5] A. A. Abou El-Ela, A. M. Azmay, and A. A. Shammah, “Optimal Sitting and Sizing of Distributed Generations In Distribution Networks Using Heuristic Algorithm,” in 2015 50th International Universities Power Engineering Conference (UPEC), 2015, pp. 1–7.[6] and A. G. Hocine Ait-Saadi1, Jean-Yves Chouinard2, “A PAPR Reduction for OFDM Signals Based on Self-Adaptive Multipopulation DE algorithm Hocine,” Int. J. Electr. Comput. Eng., 2017.[7] R. S. Al Abri, E. F. El-Saadany, and Y. M. Atwa, “Optimal Placement and Sizing Method to Improve the Voltage Stability Margin in a Distribution System Using Distributed Generation,” IEEE Trans. Power Syst., vol. 28, no. 1, pp. 326–334, Feb. 2013.[8] H. W. K. M. Amarasekara, L. Meegahapola, A. P. Agalgaonkar, and S. Perera, “Impact of Renewable Power Integration On VQ Stability Margin,” in 2013 Australasian Universities Power Engineering Conference (AUPEC), 2013, pp. 1–6.[9] R. S. Al Abri, “Voltage Stability Analysis With High Distributed Generation Penetration,” Waterloo, 2012.[10] L. Wei and Zhang Haiyan, “Allocation of Distributed Generations Based on Improved Particle Swarm Optimization Algorithm,” Int. Conf. Meas. Inf. Control, 2013.[11] W. S. Ke-yan Liu, Kaiyuan He, “Multiple-Objetive DG Optimal Sizing In Distribution System Using An Improverd PSO Algorith,” IEEE Trans. Automat. Contr., pp. 1–4, 2013.[12] S. S. Musa, H. ; Adamu, “Enhanced PSO Based Multi-Objective Distributed Generation Placement And Sizing For Power Loss Reduction And Voltage Stability Index Improvement,” IEEE Trans. Automat. Contr., pp. 1–6, 2013.[13] M. Shekeew, M. Elshahed, and M. Elmarsafawy, “Impact of Optimal Location, Size And Number Of Distributed Generation Units On The Performance Of Radial Distribution Systems,” in 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), 2016, pp. 1–6.[14] D. Jia, L. Hu, K. Liu, Y. Liu, X. Meng, and W. Sheng, “Simplified Probabilistic Voltage Stability Evaluation Considering Variable Renewable Distributed Generation In Distribution Systems,” IET Gener. Transm. Distrib., vol. 9, no. 12, pp. 1464–1473, Sep. 2015.[15] J. Silva et al., “A 75 Bus Bars Model To Evaluate The Steady State Operation Of A Sub-Transmission Electrical Power Grid,” Espacios, 2016.[16] K. Cabana, “Statistical Analysis of Voltage Sensitivity in Distribution Systems Integrating DG,” IEEE Latin America Transactions. 2016.[17] Z. Garcia Sánchez, J. A. González Cueto, G. Quintana de Basterra, and J. G. Boza Valerino, “Implementación de Un Estudio De Estabilidad De La Tensión Al Paquete De Programas Psx. 2.87,” Ing. Energética, vol. 34, no. 1, pp. 33–42.[18] K. Morison, X. Wang, A. Moshref, and A. Edris, “Identification of Voltage Control Areas And Reactive Power Reserve; An Advancement In On-Line Voltage Security Assessment,” in 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008, pp. 1–7.[19] R. A. Walling, R. Saint, R. C. Dugan, J. Burke, and L. A. Kojovic, “Summary of Distributed Resources Impact on Power Delivery Systems,” IEEE Trans. Power Deliv., vol. 23, no. 3, pp. 1636–1644, Jul. 2008.[20] H. Zeineldin, E. El-saadany, and M. A. Salama, “Distributed Generation Micro-Grid Operation: Control and Protection,” in 2006 Power Systems Conference: Advanced Metering, Protection, Control, Communication, and Distributed Resources, 2006, pp. 105–111.[21] P. C. Lu Zhang, Wei Tang, Muke Bai, “Analysis of Distributed Generation Influences On The Voltage Limit Violation Probability Of Distribution Line,” Energy Power Eng., vol. 5, pp. 756–762, 2013.[22] Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama, and R. Seethapathy, “Optimal Renewable Resources Mix for Distribution System Energy Loss Minimization,” IEEE Trans. Power Syst., vol. 25, no. 1, pp. 360–370, Feb. 2010.[23] Y. M. Atwa, E. F. El-Saadany, M. M. A. Salama, and R. Seethapathy, “Distribution System Loss Minimization Using Optimal DG Mix,” in 2009 IEEE Power & Energy Society General Meeting, 2009, pp. 1–6.[24] M. H. Albadi and E. F. El-Saadany, “Novel Method For Estimating the CF of Variable Speed Wind Turbines,” in 2009 IEEE Power & Energy Society General Meeting, 2009, pp. 1–6.[25] M. H. Albadi and E. F. El-Saadany, “Wind Turbines Capacity Factor Modeling—A Novel Approach,” IEEE Trans. Power Syst., vol. 24, no. 3, pp. 1637–1638, Aug. 2009.[26] P. Monzón, Artenstein Michel, and J. Alonso, “Evaluación De La Estabilidad De Tensión En Una Red De Potencia Con Base A Criterios Derivados De La Teoría De La Bifurcación Más Cercana,” Aerosp. Eng. Control Syst. Eng. Electr. Eng., 2014.[27] A. N. B. Alsammak, “Bifurcation and Voltage Collapse In The Electrical Power Systems,” Al_Rafidain Eng., vol. vol.13, pp. 25–41, 2005.[28] S. A. Taher and S. A. Afsari, “Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm,” Math. Probl. Eng., vol. 2012, 2012.[29] M. E. Baran and F. F. Wu, “Network Reconfiguration In Distribution Systems For Loss Reduction And Load Balancing,” IEEE Trans. Power Deliv., vol. 4, no. 2, pp. 1401–1407, Apr. 1989.[30] P. Phonrattanasak and N. Leeprechanon, “Optimal Location of Fast Charging Station on Residential Distribution Grid - Volume 3 Number 6 (Dec. 2012) - IJIMT,” Int. J. Innov. Manag. Technol., vol. 3, no. 6, pp. 675–681, 2012.[31] S. Sultana and P. K. Roy, “Multi-Objective Quasi-Oppositional Teaching Learning Based Optimization For Optimal Location Of Distributed Generator In Radial Distribution Systems,” Int. J. Electr. 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