Voltage Regulation and Power Management of DC Microgrid with Photovoltaic/Battery Storage System Using Flatness Control Method

Ashraf Abdualateef Mutlag, Mohommed Kdair Abd, Salam Waley Shneen

Abstract


This research aims to propose a power management strategy (PMS) based on the flatness control method for a stand-alone DC microgrid system. The goal of the proposed strategy is to create an efficient PMS using nonlinear flatness theory in order to provide a constant DC bus voltage and the best possible power-sharing mechanism between the battery and the PV array. A maximum power point tracking (MPPT) technique based on an artificial neural network (ANN) to optimize the PV's power. Moreover, the suggested PMS technique was tested in a simulation environment based on MATLAB®/Simulink. The obtained results demonstrate that the proposed PMS method can stabilize the bus voltage under variations in load or solar radiation. Additionally, the PMS method reduced bus voltage spikes and guaranteed good power quality, which extended the battery's lifespan and increased its efficiency. Also, the proposed approach outperforms the standard PI approach in terms of tracking efficiency and has a lower rate of overshoot in the bus voltage under different load scenarios. Therefore, the method is effective when compared with the classical PI approach. The overshoot in the PI method is 58 V, while the overshoot in the DC voltage is 5 V in the proposed method. The tracking speed of the proposed system is very low, and the slower speed was observed in the classical method, and the rise time of PI was 7.9ms, while the proposed method equals 2.2ms.


Keywords


Flatness Control; DC Mircrogrid; Nonlinear Control; Photovoltaic; Battery; Microgrid; MPPT; DC Voltage.

Full Text:

PDF

References


M. K. Abd, “Economic viability and profitability assessments of WECS.,” Int. J. Electr. Comput. Eng., vol. 10, no. 2, 2020.

A. L. Mahmood, A. M. Shakir, and B. A. Numan, “Design and performance analysis of stand-alone PV system at Al-Nahrain University, Baghdad, Iraq,” Int. J. Power Electron. Drive Syst., vol. 11, no. 2, p. 921, 2020.

S. J. Yaqoob, S. Motahhir, and E. B. Agyekum, “A new model for a photovoltaic panel using Proteus software tool under arbitrary environmental conditions,” J. Clean. Prod., vol. 333, p. 130074, 2022.

O. A. Towoju and O. A. Oladele, “Electricity Generation from Hydro, Wind, Solar and the Environment,” Eng. Technol. J., vol. 39, no. 9, pp. 1392–1398, 2021.

R. Alayi, H. Harasii, and H. Pourderogar, “Modeling and optimization of photovoltaic cells with GA algorithm,” J. Robot. Control, vol. 2, no. 1, pp. 35–41, 2021.

H. Wu, S. Wang, B. Zhao, and C. Zhu, “Energy management and control strategy of a grid‐connected PV/battery system,” Int. Trans. Electr. Energy Syst., vol. 25, no. 8, pp. 1590–1602, 2015.

S. Kamel, E. B. Agyekum, T. S. Adebayo, I. B. M. Taha, B. A. Gyamfi, and S. J. Yaqoob, “Comparative analysis of Rankine cycle linear Fresnel reflector and solar tower plant technologies: techno-economic analysis for Ethiopia,” Sustainability, vol. 14, no. 3, p. 1677, 2022.

F. A. Abbas, A. A. Obed, and S. J. Yaqoob, “A comparative study between the most used MPPT methods and particle swarm optimization method for a standalone PV system under fast change in irradiance level,” in AIP Conference Proceedings, 2023, vol. 2804, no. 1.

S. J. Yaqoob et al., “Efficient Flatness Based Energy Management Strategy for Hybrid Supercapacitor/Lithium-ion Battery Power System,” IEEE Access, vol. 10, pp. 132153–132163, 2022.

H. A. Hussein, A. J. Mahdi, and T. M. Abdul-Wahhab, “Design of a boost converter with mppt algorithm for a pv generator under extreme operating conditions,” Eng. Technol. J., vol. 39, no. 10, pp. 1473–1480, 2021.

O. Diouri, A. Gaga, S. Senhaji, and M. O. Jamil, “Design and PIL Test of High Performance MPPT Controller Based on P&O-Backstepping Applied to DC-DC Converter,” J. Robot. Control, vol. 3, no. 4, pp. 431–438, 2022.

Z. Bahij. DC Microgrid Modeling and Control in Islanded Mode. Rochester Institute of Technology, 2021.

D. E. Olivares et al., “Trends in microgrid control,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 1905–1919, 2014.

A. A. Abbooda, H. M. Habbib, and M. A. Zohdyc, “Investigation of Fault Analysis for Renewable Energy Microgrid,” Eng. Technol. J., vol. 41, no. 8, pp. 1118–1129, 2023.

A. K. Hado, B. S. Bashar, M. M. A. Zahra, R. Alayi, Y. Ebazadeh, and I. Suwarno, “Investigating and optimizing the operation of microgrids with intelligent algorithms,” J. Robot. Control, vol. 3, no. 3, pp. 279–288, 2022.

H. Mahmood, D. Michaelson, and J. Jiang, “Control strategy for a standalone PV/battery hybrid system,” in IECON 2012-38th Annual Conference on IEEE Industrial Electronics Society, pp. 3412–3418, 2012.

L. H. Pratomo, A. F. Wibisono, and S. Riyadi, “Design and Implementation of Double Loop Control Strategy in TPFW Voltage and Current Regulated Inverter for Photovoltaic Application,” J. Robot. Control, vol. 3, no. 2, pp. 196–204, 2022.

A. Tofighi and M. Kalantar, “Power management of PV/battery hybrid power source via passivity-based control,” Renew. Energy, vol. 36, no. 9, pp. 2440–2450, 2011.

M. Shen and Q. Gao, “A review on battery management system from the modeling efforts to its multiapplication and integration,” Int. J. Energy Res., vol. 43, no. 10, pp. 5042–5075, 2019.

M. Lelie et al., “Battery management system hardware concepts: An overview,” Appl. Sci., vol. 8, no. 4, p. 534, 2018.

A. A. Mutlag, M. K. Abd, and S. W. Shneen, “Power Management and Voltage Regulation in DC Microgrid with Solar Panels and Battery Storage System,” J. Robot. Control, vol. 5, no. 2, pp. 397–407, 2024.

Z. Liu, Z. Liu, J. Liu, and N. Wang, “Thermal management with fast temperature convergence based on optimized fuzzy PID algorithm for electric vehicle battery,” Appl. Energy, vol. 352, p. 121936, 2023.

Z. Yi, W. Dong, and A. H. Etemadi, “A unified control and power management scheme for PV-battery-based hybrid microgrids for both grid-connected and islanded modes,” IEEE Trans. Smart Grid, vol. 9, no. 6, pp. 5975–5985, 2017.

T. Alnejaili, S. Labdai, and L. Chrifi-Alaoui, “Predictive management algorithm for controlling pv-battery off-grid energy system,” Sensors, vol. 21, no. 19, p. 6427, 2021.

G. M. Alshabbani, M. K. Abd, M. Ilyas, and O. Bayat, “Management of Micro-grid with (SM) to Decrease Electricity Bills by Using (CAEST),” in 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), pp. 1–6, 2020.

S. Belaid, D. Rekioua, A. Oubelaid, D. Ziane, and T. Rekioua, “A power management control and optimization of a wind turbine with battery storage system,” J. Energy Storage, vol. 45, p. 103613, 2022.

K. Bedoud, H. Merabet, and T. Bahi, “Power control strategy of a photovoltaic system with battery storage system,” J. Eng. Appl. Sci., vol. 69, no. 1, pp. 1–20, 2022.

S. Batiyah, R. Sharma, S. Abdelwahed, W. Alhosaini, and O. Aldosari, “Predictive control of PV/battery system under load and environmental uncertainty,” Energies, vol. 15, no. 11, p. 4100, 2022.

Z. S. Whiteman, P. Bubna, A. K. Prasad, and B. A. Ogunnaike, “Design, operation, control, and economics of a photovoltaic/fuel cell/battery hybrid renewable energy system for automotive applications,” Processes, vol. 3, no. 2, pp. 452–470, 2015.

F. A. Mohammed, M. E. Bahgat, S. S. Elmasry, and S. M. Sharaf, “Design of a maximum power point tracking-based PID controller for DC converter of stand-alone PV system,” J. Electr. Syst. Inf. Technol., vol. 9, no. 1, p. 9, 2022.

M. M. Rahman and M. S. Islam, “PSO and ANN based hybrid MPPT algorithm for photovoltaic array under partial shading condition,” Eng. Int, vol. 8, no. 1, pp. 9–24, 2020.

B. Liang et al., “Simulation analysis of grid-connected AC/DC hybrid microgrid,” in 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp. 969–974, 2018.

M. Abdel-Salam, M.-T. El-Mohandes, and M. Goda, “An improved perturb-and-observe based MPPT method for PV systems under varying irradiation levels,” Sol. Energy, vol. 171, pp. 547–561, 2018.

A. Tiwari and A. Kumar, “Comparison of Fuzzy Logic Based MPPT of Grid-Connected Solar PV System with Different MPPT,” in International Conference on Intelligent Computing and Smart Communication 2019: Proceedings of ICSC 2019, pp. 47–60, 2020.

Y. E. A. Idrissi, K. Assalaou, L. Elmahni, and E. Aitiaz, “New improved MPPT based on artificial neural network and PI controller for photovoltaic applications,” Int. J. Power Electron. Drive Syst., vol. 13, no. 3, p. 1791, 2022.

Y. Han, P. M. Young, A. Jain, and D. Zimmerle, “Robust control for microgrid frequency deviation reduction with attached storage system,” IEEE Trans. Smart Grid, vol. 6, no. 2, pp. 557–565, 2014.

N. Allu and A. Toding, “Tuning with Ziegler Nichols method for design PID controller at rotate speed DC motor,” in IOP Conference Series: Materials Science and Engineering, vol. 846, no. 1, p. 12046, 2020.

G. A. Aziz, S. W. Shneen, F. N. Abdullah, and D. H. Shaker, “Advanced optimal GWO-PID controller for DC motor,” Int J Adv Appl Sci, vol. 11, no. 3, pp. 263–276, 2022.

H. S. Dakheel, Z. B. Abdullah, and S. W. Shneen, “Advanced optimal GA-PID controller for BLDC motor,” Bull. Electr. Eng. Informatics, vol. 12, no. 4, pp. 2077–2086, 2023.

C. G. Villegas-Mier, J. Rodriguez-Resendiz, J. M. Álvarez-Alvarado, H. Rodriguez-Resendiz, A. M. Herrera-Navarro, and O. Rodríguez-Abreo, “Artificial neural networks in MPPT algorithms for optimization of photovoltaic power systems: A review,” Micromachines, vol. 12, no. 10, p. 1260, 2021.

R. Divyasharon, R. N. Banu, and D. Devaraj, “Artificial neural network based MPPT with CUK converter topology for PV systems under varying climatic conditions,” in 2019 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS), pp. 1–6, 2019.

D. S. Obaida, A. J. Mahdib, and M. H. Alkafajia, “A Modified Global Management Controller for a Grid-connected PV System with Battery under Various Power Balance Modes,” Eng. Technol. J., vol. 41, no. 02, pp. 294–308, 2023.

S. A. Rizzo and G. Scelba, “ANN based MPPT method for rapidly variable shading conditions,” Appl. Energy, vol. 145, pp. 124–132, 2015.

F. A. Abbas, A. A. Obed, M. A. Qasim, S. J. Yaqoob, and S. Ferahtia, “An efficient energy-management strategy for a DC microgrid powered by a photovoltaic/fuel cell/battery/supercapacitor,” Clean Energy, vol. 6, no. 6, pp. 827–839, 2022.

S. J. Yaqoob, H. Arnoos, M. A. Qasim, E. B. Agyekum, A. Alzahrani, and S. Kamel, “An optimal energy management strategy for a photovoltaic/li-ion battery power system for DC microgrid application,” Front. Energy Res., vol. 10, p. 1066231, 2023.

S. Ferahtia, A. Djerioui, S. Zeghlache, and A. Houari, “A hybrid power system based on fuel cell, photovoltaic source and supercapacitor,” SN Appl. Sci., vol. 2, pp. 1–11, 2020.

A. A. Mutlag, M. K. Abd, and S. W. Shneen, "Power Management and Voltage Regulation in DC Microgrid with Solar Panels and Battery Storage System," Journal of Robotics and Control (JRC), vol. 5, no. 2, pp. 397-407, 2024.

M. Abdillah, T. Jayadiharja, R. H. Arjadi, H. Setiadi, R. Zamora, and Y. Afif, "Novel PID Controller on Battery Energy Storage Systems for Frequency Dynamics Enhancement," Journal of Robotics and Control (JRC), vol. 4, no. 3, pp. 278-288, 2023.

H. A. Hadi, A. Kassem, H. Amoud, S. Nadweh, and N. M. Ghazaly, "Using Grey Wolf Optimization Algorithm and Whale Optimization Algorithm for Optimal Sizing of Grid-Connected Bifacial PV Systems," Journal of Robotics and Control (JRC), vol. 5, no. 3, pp. 733-745, 2024.

W. Aribowo, H. Suryoatmojo, and F. A. Pamuji, "Improved Droop Control Based on Modified Osprey Optimization Algorithm in DC Microgrid," Journal of Robotics and Control (JRC), vol. 5, no. 3, pp. 804-820, 2024.

O. N. R. Al-Jaboury, Z. Hamodat, and R. W. Daoud, "Design of Power Control Circuit for Grid-Connected PV System-Based Neural Network," Journal of Robotics and Control (JRC), vol. 5, no. 3, pp. 821-828, 2024.

S. Abboud et al., "Optimizing Solar Energy Production in Partially Shaded PV Systems with PSO-INC Hybrid Control," Journal of Robotics and Control (JRC), vol. 5, no. 2, pp. 312-320, 2024.

Z. Zhu, X. Liu, X. Kong, L. Ma, K. Y. Lee, and Y. Xu, "PV/Hydrogen DC microgrid control using distributed economic model predictive control," Renewable Energy, vol. 222, p. 119871, 2024.

A. S. Dahane and R. B. Sharma, "Hybrid AC-DC microgrid coordinated control strategies: A systematic review and future prospect," Renewable Energy Focus, vol. 49, p. 100553, 2024.

M. A. Mesbah et al., " Adaptive control approach for accurate current sharing and voltage regulation in DC microgrid applications," Energies, vol. 17, no. 2, p. 284, 2024.




DOI: https://doi.org/10.18196/jrc.v5i6.22530

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Ashraf Abdualateef Mutlag, Mohommed Kdair Abd, Salam Waley Shneen

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

 


Journal of Robotics and Control (JRC)

P-ISSN: 2715-5056 || E-ISSN: 2715-5072
Organized by Peneliti Teknologi Teknik Indonesia
Published by Universitas Muhammadiyah Yogyakarta in collaboration with Peneliti Teknologi Teknik Indonesia, Indonesia and the Department of Electrical Engineering
Website: http://journal.umy.ac.id/index.php/jrc
Email: jrcofumy@gmail.com


Kuliah Teknik Elektro Terbaik