Currently, this work lays the ground work for sophisticated control methods and decision support systems in hybrid microgrid operations by providing insightful information about integrating artificial intelligence for improved microgrid control. In this work, a neural network (NN) method is proposed for power flow analysis in an IEEE 12-bus-based Hybrid AC/DC Microgrid. The study optimizes power dispatch, minimizes expenses, and minimizes losses in both AC and DC components. Simulation is carried using MATLAB software and the results are presented and analysed. The accuracy of the NN’s predictions of active power flows is demonstrated by training it on historical data and validating it on real-time observations. Regression plots comparing anticipated and real values demonstrate the effectiveness of NN-based analysis in reaching the ideal power distribution.
Keywords
Optimal power flow, Cost Analysis, hybrid AC/DC microgrid, IEEE 12 bus system, Neural Network Controller.
“On certain integrals of Lipschitz-Hankel type involving products of bessel functions,” Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences, vol. 247, no. 935, pp. 529–551, Apr. 1955, doi: 10.1098/rsta.1955.0005.
Venkataramana Ajjarapu,”Computational Techniques for Voltage Stability Assessment and Control E- Book—Library of Congress” Iowa State University, Department of Electrical and Computer Engineering. 1122 Coover Hall, Ames Iowa 50011, U.S.A. Control Number: 2006926216.
Togiti, Varun, "Pattern Recognition of Power System Voltage Stability using Statistical and Algorithmic Methods" ,University of New Orleans Theses and Dissertations. (2012), 1488.
B. Gao, G. K. Morison, and P. Kundur, “Voltage stability evaluation using modal analysis,” IEEE Transactions on Power Systems, vol. 7, no. 4, pp. 1529–1542, 1992, doi: 10.1109/59.207377.
P.-A. Lof, T. Smed, G. Andersson, and D. J. Hill, “Fast calculation of a voltage stability index,” IEEE Transactions on Power Systems, vol. 7, no. 1, pp. 54–64, 1992, doi: 10.1109/59.141687.
Lixin Bao, Zhenyu Huang, and Wilsun Xu, “Online voltage stability monitoring using var reserves,” IEEE Transactions on Power Systems, vol. 18, no. 4, pp. 1461–1469, Nov. 2003, doi: 10.1109/tpwrs.2003.818706.
Satish Joshi , “A Thesis on Voltage stability and contingency selection studies in electrical power system”, Department of electrical engineering. Indian institute of technology Kanpur . December 1995.
P. Kundur, T. Van Cutsem, V. Vittal 8.J. Paserba, V. Ajjarapu, G. Andersson, A. Bose, C. Canizares, N. Hatziargyriou, D. Hill, A. Stankovic, C. Taylor, “Power System Stability and Control McGraw”,Hilll, 1994.
“Definition and Classification of Power System Stability IEEE/CIGRE Joint Task Force on Stability Terms and Definitions,” IEEE Transactions on Power Systems, vol. 19, no. 3, pp. 1387–1401, Aug. 2004, doi: 10.1109/tpwrs.2004.825981.
L. A. Kraft and G. T. Heydt, “Adaptive Acceleration Factors for the Newton-Raphson Power Flow Study,” Electric Machines & Power Systems, vol. 11, no. 4, pp. 337–346, Jan. 1986, doi: 10.1080/07313568608909188.
S. Mehfuz and S. Kumar, “Two dimensional particle swarm optimization algorithm for load flow analysis,” International Journal of Computational Intelligence Systems, vol. 7, no. 6, p. 1074, 2014, doi: 10.1080/18756891.2014.963973.
K. Nohac, V. Sitar, and J. Veleba, “Load flow analysis in alternative tools using equations, physical and block diagrams,” 2016 17th International Scientific Conference on Electric Power Engineering (EPE), May 2016, doi: 10.1109/epe.2016.7521747.
D.K. Tanti Dharamjit, "Load Flow Analysis on IEEE 30 bus System", International Journal of Scientific and Research Publications, vol. 2, no. 11, November 2012.
Deepinder Kaur Mander and Supreet Kaur Saini, "Load Flow Analysis: A Review", International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering, vol. 5, no. 3, March 2016.
Deepinder Kaur Mander and GS Virdi, "Result Analysis on Load Flow by Using Newton Raphson Method", International Journal of Advanced Research in Electrical Electronics and Instrumentation Engineering, vol. 6, no. 7, July 2017.
Vadimgadu Roja and M.S Sujatha, "A Review of Optimal DG Allocation in Distribution System for Loss Minimization", IOSR Journal of Electrical and Electronics Engineering, pp. 15-22.
D. Shirmohammadi, H. W. Hong, A. Semlyen, and G. X. Luo, “A compensation-based power flow method for weakly meshed distribution and transmission networks,” IEEE Transactions on Power Systems, vol. 3, no. 2, pp. 753–762, May 1988, doi: 10.1109/59.192932.
G. X. Luo and A. Semlyen, “Efficient load flow for large weakly meshed networks,” IEEE Transactions on Power Systems, vol. 5, no. 4, pp. 1309–1316, 1990, doi: 10.1109/59.99382.
D. Rajicic and A. Dimitrovski, “A new method for handling PV nodes in backward/forward power flow for radial and weakly meshed networks,” 2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502), doi: 10.1109/ptc.2001.964896.
S. M. Moghaddas-Tafreshi and E. Mashhour, “Distributed generation modeling for power flow studies and a three-phase unbalanced power flow solution for radial distribution systems considering distributed generation,” Electric Power Systems Research, vol. 79, no. 4, pp. 680–686, Apr. 2009, doi: 10.1016/j.epsr.2008.10.003.
A. Augugliaro, L. Dusonchet, S. Favuzza, M. G. Ippolito, and E. R. Sanseverino, “A backward sweep method for power flow solution in distribution networks,” International Journal of Electrical Power & Energy Systems, vol. 32, no. 4, pp. 271–280, May 2010, doi: 10.1016/j.ijepes.2009.09.007.
A. Hamouda and K. Zehar, “Improved algorithm for radial distribution networks load flow solution,” International Journal of Electrical Power & Energy Systems, vol. 33, no. 3, pp. 508–514, Mar. 2011, doi: 10.1016/j.ijepes.2010.11.004.
M. M. Hamada, Mohamed. A. A. Wahab, and Nasser. G. A. Hemdan, “Simple and efficient method for steady-state voltage stability assessment of radial distribution systems,” Electric Power Systems Research, vol. 80, no. 2, pp. 152–160, Feb. 2010, doi: 10.1016/j.epsr.2009.08.017.
P. Mandal, T. Senjyu, N. Urasaki, A. Yona, T. Funabashi, and A. K. Srivastava, “Price Forecasting for Day-Ahead Electricity Market Using Recursive Neural Network,” 2007 IEEE Power Engineering Society General Meeting, Jun. 2007, doi: 10.1109/pes.2007.385970.
M. Tuo and X. Li, “Long-Term Recurrent Convolutional Network-based Inertia Estimation using Ambient Measurements,” 2022 IEEE Industry Applications Society Annual Meeting (IAS), Oct. 2022, doi: 10.1109/ias54023.2022.9940112.
L. Wu, J. Park, J. Choi, J. Cha, and K. Y. Lee, “A study on wind speed prediction using artificial neural network at Jeju Island in Korea,” 2009 Transmission & Distribution Conference & Exposition: Asia and Pacific, Oct. 2009, doi: 10.1109/td-asia.2009.5356873.
M. K. Thukral, “Solar Power Output Prediction Using Multilayered Feedforward Neural Network: A Case Study of Jaipur,” 2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC), Dec. 2020, doi: 10.1109/isssc50941.2020.9358821.
S. Huang, M. Yang, C. Zhang, J. Yun, Y. Gao, and P. Li, “A Control Strategy Based on Deep Reinforcement Learning Under the Combined Wind-Solar Storage System,” 2020 IEEE 3rd Student Conference on Electrical Machines and Systems (SCEMS), Dec. 2020, doi: 10.1109/scems48876.2020.9352436.
S. M. Miraftabzadeh, F. Foiadelli, M. Longo, and M. Pasetti, “A Survey of Machine Learning Applications for Power System Analytics,” 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Jun. 2019, doi: 10.1109/eeeic.2019.8783340.
J. E. King, S. C. E. Jupe, and P. C. Taylor, “Network State-Based Algorithm Selection for Power Flow Management Using Machine Learning,” IEEE Transactions on Power Systems, vol. 30, no. 5, pp. 2657–2664, Sep. 2015, doi: 10.1109/tpwrs.2014.2361792.
W. A. Alsulami and R. S. Kumar, “Artificial neural network based load flow solution of Saudi national grid,” 2017 Saudi Arabia Smart Grid (SASG), Dec. 2017, doi: 10.1109/sasg.2017.8356516.
M. S. S. T. O. A. B. J. Duncan Glover, "Power System Analysis and Design", Cengage Learning, 2022.
X. Li, A. S Korad, and P. Balasubramanian, “Sensitivity factors based transmission network topology control for violation relief,” IET Generation, Transmission & Distribution, vol. 14, no. 17, pp. 3539–3547, Jul. 2020, doi: 10.1049/iet-gtd.2019.1196.
R. Lukomski and K. Wilkosz, “Power system topology verification using artificial neural networks: maximum utilization of measurement data,” 2003 IEEE Bologna Power Tech Conference Proceedings,, doi: 10.1109/ptc.2003.1304451.
A. V. Ramesh and X. Li, “Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment,” IEEE Transactions on Power Systems, vol. 39, no. 2, pp. 4735–4746, Mar. 2024, doi: 10.1109/tpwrs.2023.3313430.
A. Keyhani, A. Abur, and S. Hao, “Evaluation of power flow techniques for personal computers,” IEEE Transactions on Power Systems, vol. 4, no. 2, pp. 817–826, May 1989, doi: 10.1109/59.193857.
M. K. Thukral, “Solar Power Output Prediction Using Multilayered Feedforward Neural Network: A Case Study of Jaipur,” 2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC), Dec. 2020, doi: 10.1109/isssc50941.2020.9358821.
Acknowledgements
The authors would like to thank to the reviewers for nice comments on the manuscript.
Funding
No funding was received to assist with the preparation of this manuscript.
Ethics declarations
Conflict of interest
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Availability of data and materials
Data sharing is not applicable to this article as no new data were created or analysed in this study.
Author information
Contributions
All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.
Corresponding author
Pagidela Yamuna
Pagidela Yamuna
Department of Electrical and Electronics Engineering, JNTUA College of Engineering, Ananthapuramu, India.
Open Access This article is licensed under a Creative Commons Attribution NoDerivs is a more restrictive license. It allows you to redistribute the material commercially or non-commercially but the user cannot make any changes whatsoever to the original, i.e. no derivatives of the original work. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-nd/4.0/
Cite this article
Pagidela Yamuna and Visali N, “Optimal Power Flow in Hybrid AC/DC Microgrid using ANN for Cost Minimization", pp. 408-418, April 2024. doi: 10.53759/7669/jmc202404039.
