DOI: https://doi.org/10.20998/2074-272X.2019.5.11

REACTIVE POWER CONTROL IN MICRO-GRID NETWORKS USING ADAPTIVE CONTROL

A. Moghayadniya, E. Razavi

Анотація


Цель. Несмотря на их экономические и экологические преимущества, распределенные продукты в энергосистемах приводят к возникновению проблем в последних. Одним из наиболее важных вопросов в этой связи являются колебания напряжения и частоты в микросетях, которые зависят от нескольких факторов, таких как переменная нагрузка потребления и ошибки в энергосистемах. Одной из основных проблем, связанных с использованием микросетей, является энергоменеджмент источников распределенной генерации. Энергоменеджмент играет ключевую роль во многих микросетях и может обеспечить стабильную и улучшенную работу микросетей при постоянном состоянии системы. Настоящее исследование направлено на исследование энергоменеджмента в микросетях путем предложения адаптивного метода управления вместе с ПИД-контроллером для энергоменеджмента и координации в микросетях. Эта система координации функционирует между источниками производимой  энергии и контролирует уровни напряжения и частоты в отношении возможных помех, возникающих в любом месте контура системы. Результаты моделирования предложенного алгоритма в программной среде MATLAB показали высокую степень успеха (то есть правильную реакцию на колебания в микросети) и чрезвычайно низкую частоту ошибок (то есть надлежащую реактивную мощность в сети).

Ключові слова


микросеть; параметры управления; онлайн настройка параметров; пропорционально-интегрально-дифференцирующий (ПИД) контроллер; адаптивное управление

Повний текст:

PDF ENG (English)

Посилання


ElkhatibM.E., El-Shatshat R., Salama M.M.A. Novel Coordinated Voltage Control for Smart Distribution Networks with DG. IEEE Transactions on Smart Grid, 2011, vol.2, no.4, pp. 598-605. doi: 10.1109/TSG.2011.2162083.

Pepermans G., Driesen J., Haeseldonckx G., Belmans R., D’haeseleer W. Distributed generation: definition, benefits and issues. Energy Policy, 2005, vol.33, no.6, pp. 787-798. doi: 10.1016/j.enpol.2003.10.004.

Mandis A.C., Manoloiu A., StefanaNeagoe A.G., Leonida T., Neagoe A.C. Impact of distributed generation on steady state of electrical networks. Proceedings of ISFEE ’2014 – International Symposium on Fundamentals of Electrical Engineering. doi: 10.1109/ISFEE.2014.7050605.

Rezaei N., Haghifam M-R. Protection scheme for a distribution system with distributed generation using neural networks. International Journal of Electrical Power & Energy Systems, 2008, vol.30, no.4, pp. 235-241. doi: 10.1016/j.ijepes.2007.07.006.

Poornazaryan B., Karimyan P., Gharehpetian G.B., Abedi M. Optimal allocation and sizing of DG units considering voltage stability, losses and load variations. International Journal of Electrical Power & Energy Systems, 2016, vol.79, pp. 42-52. doi: 10.1016/j.ijepes.2015.12.034.

Sheng W., Meng X., Zhao S., Song X. Maximum penetration level of distributed generation in consideration of voltage fluctuations based on multi-resolution model. IET Generation, Transmission & Distribution, 2015, vol.9, no.3, pp. 241-248. doi: 10.1049/iet-gtd.2013.0883.

Pandi V.R., Zeineldin H.H., Xiao W. Determining Optimal Location and Size of Distributed Generation Resources Considering Harmonic and Protection Coordination Limits. IEEE Transactions on Power Systems, 2013, vol.28, no.2, pp. 1245-1254. doi: 10.1109/TPWRS.2012.2209687.

Bevrani H., Ghosh A., Ledwich G. Renewable energy sources and frequency regulation: survey and new perspectives. IET Renewable Power Generation, 2010, vol.4, no.5, pp. 438-457. doi: 10.1049/iet-rpg.2009.0049.

Shiva C.K., Mukherjee V. Automatic generation control of interconnected power system for robust decentralized random load disturbances using a novel quasioppositional harmony search algorithm. International Journal of Electrical Power & Energy Systems, 2015, vol.73, pp. 991-1001. doi: 10.1016/j.ijepes.2015.06.016.

Rerkpreedapong D., Hasanovic A., Feliachi A. Robust load frequency control using genetic algorithms and linear matrix inequalities. IEEE Transactions on Power Systems, 2003, vol.18, no.2, pp. 855-861. doi: 10.1109/TPWRS.2003.811005.

Esmaeli A. Stability analysis and control of microgrids by sliding mode control. International Journal of Electrical Power & Energy Systems, 2016. vol.78, pp. 22-28. doi: 10.1016/j.ijepes.2015.11.068.

Miveh M.R., Rahmat M.F., Ghadimi A.A., Mustafa M.W. Control techniques for three-phase four-leg voltage source inverters in autonomous Micro-grids: A review. Renewable and Sustainable Energy Reviews, 2016, vol.54, pp. 1592-1610. doi: 10.1016/j.rser.2015.10.079.

Khalghani M.R., Khooban M.H., Mahboubi-Moghaddam E., Vafamand V., Goodarzi M. A self-tuning load frequency control strategy for Micro-grids: Human brain emotional learning. International Journal of Electrical Power & Energy Systems, 2016, vol.75, pp. 311-319. doi: 10.1016/j.ijepes.2015.08.026.

Ghanbarian M.M., Nayeripour M., Rajaei A., Mansouri M.M. Design and implementation of a new modified sliding mode controller for grid connected inverter to controlling the voltage and frequency. ISA Transactions, 2016, vol.61, pp. 179-187. doi: 10.1016/j.isatra.2015.11.023.

Mahmoud M.S., Alyazidi N.M., Abouheaf M.I. Adaptive intelligent techniques for Micro-grid control systems: A survey. International Journal of Electrical Power & Energy Systems, 2017, vol.90, pp. 292-305. doi: 10.1016/j.ijepes.2017.02.008.

Shariatzadeh F., Kumar N., Srivastava A.K. Optimal Control Algorithms for Reconfiguration of Shipboard Micro-grid Distribution System Using Intelligent Techniques. IEEE Transactions on Industry Applications, 2017, vol.53, no.1, pp. 474-482. doi: 10.1109/TIA.2016.2601558.

Sedighizadeha M., Esmaili M., Eisapour-Moarref A. Voltage and frequency regulation in autonomous Micro-grids using Hybrid Big Bang-Big Crunch algorithm. Applied Soft Computing, 2017, vol.52, pp. 176-189. doi: 10.1016/j.asoc.2016.12.031.


Пристатейна бібліографія ГОСТ


  1. ElkhatibM.E., El-Shatshat R., Salama M.M.A. Novel Coordinated Voltage Control for Smart Distribution Networks with DG. IEEE Transactions on Smart Grid, 2011, vol.2, no.4, pp. 598-605. doi: 10.1109/TSG.2011.2162083.
  2. Pepermans G., Driesen J., Haeseldonckx G., Belmans R., D’haeseleer W. Distributed generation: definition, benefits and issues. Energy Policy, 2005, vol.33, no.6, pp. 787-798. doi: 10.1016/j.enpol.2003.10.004.
  3. Mandis A.C., Manoloiu A., StefanaNeagoe A.G., Leonida T., Neagoe A.C. Impact of distributed generation on steady state of electrical networks. Proceedings of ISFEE ’2014 – International Symposium on Fundamentals of Electrical Engineering. doi: 10.1109/ISFEE.2014.7050605.
  4. Rezaei N., Haghifam M-R. Protection scheme for a distribution system with distributed generation using neural networks. International Journal of Electrical Power & Energy Systems, 2008, vol.30, no.4, pp. 235-241. doi: 10.1016/j.ijepes.2007.07.006.
  5. Poornazaryan B., Karimyan P., Gharehpetian G.B., Abedi M. Optimal allocation and sizing of DG units considering voltage stability, losses and load variations. International Journal of Electrical Power & Energy Systems, 2016, vol.79, pp. 42-52. doi: 10.1016/j.ijepes.2015.12.034.
  6. Sheng W., Meng X., Zhao S., Song X. Maximum penetration level of distributed generation in consideration of voltage fluctuations based on multi-resolution model. IET Generation, Transmission & Distribution, 2015, vol.9, no.3, pp. 241-248. doi: 10.1049/iet-gtd.2013.0883.
  7. Pandi V.R., Zeineldin H.H., Xiao W. Determining Optimal Location and Size of Distributed Generation Resources Considering Harmonic and Protection Coordination Limits. IEEE Transactions on Power Systems, 2013, vol.28, no.2, pp. 1245-1254. doi: 10.1109/TPWRS.2012.2209687.
  8. Bevrani H., Ghosh A., Ledwich G. Renewable energy sources and frequency regulation: survey and new perspectives. IET Renewable Power Generation, 2010, vol.4, no.5, pp. 438-457. doi: 10.1049/iet-rpg.2009.0049.
  9. Shiva C.K., Mukherjee V. Automatic generation control of interconnected power system for robust decentralized random load disturbances using a novel quasioppositional harmony search algorithm. International Journal of Electrical Power & Energy Systems, 2015, vol.73, pp. 991-1001. doi: 10.1016/j.ijepes.2015.06.016.
  10. Rerkpreedapong D., Hasanovic A., Feliachi A. Robust load frequency control using genetic algorithms and linear matrix inequalities. IEEE Transactions on Power Systems, 2003, vol.18, no.2, pp. 855-861. doi: 10.1109/TPWRS.2003.811005.
  11. Esmaeli A. Stability analysis and control of microgrids by sliding mode control. International Journal of Electrical Power & Energy Systems, 2016. vol.78, pp. 22-28. doi: 10.1016/j.ijepes.2015.11.068.
  12. Miveh M.R., Rahmat M.F., Ghadimi A.A., Mustafa M.W. Control techniques for three-phase four-leg voltage source inverters in autonomous Micro-grids: A review. Renewable and Sustainable Energy Reviews, 2016, vol.54, pp. 1592-1610. doi: 10.1016/j.rser.2015.10.079.
  13. Khalghani M.R., Khooban M.H., Mahboubi-Moghaddam E., Vafamand V., Goodarzi M. A self-tuning load frequency control strategy for Micro-grids: Human brain emotional learning. International Journal of Electrical Power & Energy Systems, 2016, vol.75, pp. 311-319. doi: 10.1016/j.ijepes.2015.08.026.
  14. Ghanbarian M.M., Nayeripour M., Rajaei A., Mansouri M.M. Design and implementation of a new modified sliding mode controller for grid connected inverter to controlling the voltage and frequency. ISA Transactions, 2016, vol.61, pp. 179-187. doi: 10.1016/j.isatra.2015.11.023.
  15. Mahmoud M.S., Alyazidi N.M., Abouheaf M.I. Adaptive intelligent techniques for Micro-grid control systems: A survey. International Journal of Electrical Power & Energy Systems, 2017, vol.90, pp. 292-305. doi: 10.1016/j.ijepes.2017.02.008.
  16. Shariatzadeh F., Kumar N., Srivastava A.K. Optimal Control Algorithms for Reconfiguration of Shipboard Micro-grid Distribution System Using Intelligent Techniques. IEEE Transactions on Industry Applications, 2017, vol.53, no.1, pp. 474-482. doi: 10.1109/TIA.2016.2601558.
  17. Sedighizadeha M., Esmaili M., Eisapour-Moarref A. Voltage and frequency regulation in autonomous Micro-grids using Hybrid Big Bang-Big Crunch algorithm. Applied Soft Computing, 2017, vol.52, pp. 176-189. doi: 10.1016/j.asoc.2016.12.031.

 

 

 





Copyright (c) 2019 A. Moghayadniya, E. Razavi


This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

ISSN 2074–272X (Print)
ІSSN 2309–3404 (Online)