Power Management and Voltage Regulation in DC Microgrid with Solar Panels and Battery Storage System

Ashraf Abdualateef Mutlag, Mohammed Kdair Abd, Salam Waley Shneen

Abstract


Photovoltaics are one of the most important renewable energy sources to meet the increasing demand for energy. This led to the emergence of Microgrid s, which revealed a number of problems, the most important of which is managing and monitoring their operation, this research contributes mainly by using a maximum power tracking algorithm Which depends on artificial neurons and integrating it with a proposed algorithm for energy management in Standalone DC Microgrid, in order to control the distribution of power and maintain the DC bus voltage level.  Maximum Power Point Tracking (MPPT) algorithm based on ANN+PID is used. Where ANN tracks the maximum power point by estimating the reference voltage using real-time data such as temperature and solar radiation. The PI controller reduces the error between the measured voltage and the reference voltage and makes the necessary adjustments in order to control the boost converter connected to the photovoltaic panels. While the process of controlling the DC bus voltage level is done by controlling the battery charging and discharging process through the power management algorithm and controlling the Bidirectional converter switches according to the battery’s state of charge. The simulation results obtained by used MATLAB Simulink are shown that the used MPPT algorithm achieved the maximum power with the least amount of fluctuation, the method's efficiency was 99.92%, and its accuracy was 99.85%, as well as the success of the power management algorithm controlling the battery charging/discharging process and maintaining the DC voltage level at the specified value in different operating scenarios.

Keywords


DC Microgrid; Photovoltaic (PV) Systems; Maximum Power Point Tracking (MPPT); Voltage Regulation; Battery Energy Storage System (BESS); Energy Management (EM).

Full Text:

PDF

References


T. Debela and A. Bhattacharya, “Design and analysis of a DC/AC microgrid with centralized battery energy storage system,” in IECON 2017-43rd Annual Conference of the IEEE Industrial Electronics Society, pp. 8779–8784, 2017.

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.

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.

T. Thomas and M. K. Mishra, "Control Strategy for a PV-Wind based Standalone DC Microgrid with Hybrid Energy Storage System," 2019 IEEE 1st International Conference on Energy, Systems and Information Processing (ICESIP), pp. 1-6, 2019, doi: 10.1109/ICESIP46348.2019.8938310.

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.

D. Murugesan, K. Jagatheesan, P. Shah, and R. Sekhar, “Optimization of Load Frequency Control Gain Parameters for Stochastic Microgrid Power System,” J. Robot. Control, vol. 4, no. 5, pp. 726–742, 2023.

J. Kumar, A. Agarwal, and V. Agarwal, “A review on overall control of DC microgrids,” J. energy storage, vol. 21, pp. 113–138, 2019.

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.

M. Kumar, "Solar PV Based DC Microgrid under Partial Shading Condition with Battery-Part 2: Energy Management System," 2018 8th IEEE India International Conference on Power Electronics (IICPE), pp. 1-6, 2018, doi: 10.1109/IICPE.2018.8709437.

A. Bakundukize, M. Twizerimana, D. Bernadette, B. J. Pierre, and N. Theoneste, “Design and Modelling of PV Power Plant for Rural Electrification in Kayonza, Rwanda,” Journal of Energy Research and Reviews, pp. 31–55, 2021. doi: 10.9734/jenrr/2021/v7i430197.

S. Rüstemli, F. Dincer, and M. Almalı, “’Research On Effects Of Environmental Factors On Photovoltaic Panels and Modeling With Matlab/Simulink,” Prz. Elektrotechniczny, vol. 88, no. 2, pp. 63–66, 2012.

O. Eseosa and N. I. Wariboko, “Proposing Utilization of Photovoltaic (PV) Source into Power Distribution Network Using University of Port Harcourt as a Case Study,” J. Robot. Control, vol. 2, no. 4, pp. 274–282, 2021.

W. Bai, “DC Microgrid optimized energy management and real-time control of power systems for grid-connected and off-grid operating modes,” 2021.

A. El-Shahat and S. Sumaiya, “DC-microgrid system design, control, and analysis,” Electron., vol. 8, no. 2, 2019, doi: 10.3390/electronics8020124.

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.

C. Li, Y. Chen, D. Zhou, J. Liu, and J. Zeng, “A high-performance adaptive incremental conductance MPPT algorithm for photovoltaic systems,” Energies, vol. 9, no. 4, p. 288, 2016.

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.

K. Dahmane, B. Bouachrine, M. Ajaamoum, B. Imodane, S. Mouslim, and M. Benydir, “Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System,” J. Robot. Control, vol. 4, no. 1, pp. 1–11, 2023.

S. K. Kollimalla and M. K. Mishra, “A novel adaptive P&O MPPT algorithm considering sudden changes in the irradiance,” IEEE Trans. Energy Convers., vol. 29, no. 3, pp. 602–610, 2014.

M. E. Ahmad, A. H. Numan, and D. Y. Mahmood, “A comparative study of perturb and observe (P&O) and incremental conductance (INC) PV MPPT techniques at different radiation and temperature conditions,” Eng. Technol. J., vol. 40, no. 02, pp. 376–385, 2022.

F. Liu, S. Duan, F. Liu, B. Liu, and Y. Kang, “A variable step size INC MPPT method for PV systems,” IEEE Trans. Ind. Electron., vol. 55, no. 7, pp. 2622–2628, 2008.

M. I. Juma, C. J. Msigwa, and B. M. M. Mwinyiwiwa, “Solar Pv Based Maximum Power Point Tracking Embedded Voltage Regulation for Micro-Grid Application,” vol. 6, no. 06, pp. 552–558, 2019.

K. Gowtham, C. V Sivaramadurai, P. Hariprasath, and B. Indurani, “A Management of power flow for DC Microgrid with Solar and Wind Energy Sources,” in 2018 International Conference on Computer Communication and Informatics (ICCCI), pp. 1–5, 2018.

M. I. Juma, B. M. M. Mwinyiwiwa, C. J. Msigwa, and A. T. Mushi, “Design of a hybrid energy system with energy storage for standalone DC microgrid application,” Energies, vol. 14, no. 18, 2021, doi: 10.3390/en14185994.

P. Singh and J. S. Lather, “Accurate power-sharing, voltage regulation, and SOC regulation for LVDC microgrid with hybrid energy storage system using artificial neural network,” Int. J. Green Energy, vol. 17, no. 12, pp. 756–769, 2020.

M. Juma, C. Msigwa, and B. M. M. Mwinyiwiwa, “Solar PV based on maximum power point tracking embedded voltage regulation for micro-grid application,” Int. J. Innov. Res. Adv. Eng. IJIRAE, vol. 6, pp. 552–558, 2019.

S. Sahu, G. Panda, and S. P. Yadav, “Dynamic modelling and control of PMSG based stand-alone wind energy conversion system,” in 2018 Recent Advances on Engineering, Technology and Computational Sciences (RAETCS), pp. 1–6, 2018.

T. Satyanarayana and R. Dahiya, “Autonomous Battery Storage Energy System Control of PV-Wind Based DC Microgrid,” Int. J. Ambient Energy, vol. 42, no. 8, pp. 888–894, 2021.

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. 2, pp. 294–308, 2023.

S. Ali, Z. Zheng, M. Aillerie, J.-P. Sawicki, M.-C. Pera, and D. Hissel, “A review of DC Microgrid energy management systems dedicated to residential applications,” Energies, vol. 14, no. 14, p. 4308, 2021.

M. Ahmed, L. Meegahapola, A. Vahidnia, and M. Datta, “Stability and control aspects of microgrid Architectures–A comprehensive review,” IEEE access, vol. 8, pp. 144730–144766, 2020.

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.

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.

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.

S. D. Al-Majidi, M. F. Abbod, and H. S. Al-Raweshidy, “Design of an intelligent MPPT based on ANN using a real photovoltaic system data,” in 2019 54th International Universities Power Engineering Conference (UPEC), pp. 1–6, 2019.

R. B. Roy et al., “A comparative performance analysis of ANN algorithms for MPPT energy harvesting in solar PV system,” IEEE Access, vol. 9, pp. 102137–102152, 2021.

M. M. Iqbal and K. Islam, “Design and simulation of a PV System with battery storage using bidirectional DC-DC converter using Matlab Simulink,” Int. J. Sci. Technol. Res., vol. 6, no. 7, pp. 403–410, 2017.

S. Sumaiya, “Modeling, Designing and Analysis of a Standalone PV DC Microgrid System,” 2018.

S. Jadhav, N. Devdas, S. Nisar, and V. Bajpai, “Bidirectional DC-DC converter in solar PV system for battery charging application,” in 2018 international conference on smart city and emerging technology (ICSCET), pp. 1–4, 2018.

R. Teodorescu, M. Liserre, and P. Rodriguez. Grid converters for photovoltaic and wind power systems. John Wiley & Sons, 2011.

C. Phurailatpam, R. Sangral, B. S. Rajpurohit, S. N. Singh, and F. G. Longatt, “Design and analysis of a dc microgrid with centralized battery energy storage system,” in 2015 Annual IEEE India Conference (INDICON), pp. 1–6, 2015.

A. N. H. Hamoodi and F. S. Abdulla, “Design and sizing of solar plant for Qayarah general Hospital and simulation with the PV-SOL program,” NTU J. Eng. Technol., vol. 1, no. 1, pp. 67–71, 2021.

L. K. Amifia, “Direct Comparison Using Coulomb Counting and Open Circuit Voltage Method for the State of Health Li-Po Battery,” J. Robot. Control, vol. 3, no. 4, pp. 455–463, 2022.

M. Hailu Kebede, “Design of Standalone PV System for a Typical Modern Average Home in Shewa Robit Town-Ethiopia,” American Journal of Electrical and Electronic Engineering, vol. 6, no. 2. pp. 72–76, 2018, doi: 10.12691/ajeee-6-2-4.

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.

R. Çelikel and A. Gündoğdu, “ANN-based MPPT algorithm for photovoltaic systems,” Turkish J. Sci. Technol., vol. 15, no. 2, pp. 101–110, 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.

Z. Dzulfikri, N. Nuryanti, and Y. Erdani, “Design and implementation of artificial neural networks to predict wind directions on controlling yaw of wind turbine prototype,” J. Robot. Control, vol. 1, no. 1, pp. 20–26, 2020.

H. S. Dakheel, Z. B. Abdullah, N. S. Jasim, and S. W. Shneen, “Simulation model of ANN and PID controller for direct current servo motor by using Matlab/Simulink,” TELKOMNIKA Telecommunication Comput. Electron. Control., vol. 20, no. 4, pp. 922–932, 2022.

M. M. Gani, M. S. Islam, and M. A. Ullah, “Optimal PID tuning for controlling the temperature of electric furnace by genetic algorithm,” SN Appl. Sci., vol. 1, pp. 1–8, 2019.

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.

C. N. Bhende, S. Mishra, and S. G. Malla, “Permanent magnet synchronous generator-based standalone wind energy supply system,” IEEE Trans. Sustain. energy, vol. 2, no. 4, pp. 361–373, 2011.

I. Tank and S. Mali, “Renewable based DC microgrid with energy management system,” in 2015 IEEE international conference on signal processing, informatics, communication and energy systems (SPICES), pp. 1–5, 2015.

C. S. Rajan and M. Ebenezer, “Modeling operation and simulation of interconnected dc microgrids,” in 2020 International Conference on Power, Instrumentation, Control and Computing (PICC), pp. 1–6, 2020.

L. Assiya, D. Aziz, and H. Ahmed, “Comparative study of P&O and INC MPPT algorithms for DC-DC converter based PV system on MATLAB/SIMULINK,” in 2020 IEEE 2nd international conference on electronics, control, optimization and computer science (ICECOCS), pp. 1–5, 2020.

M. Sarvi and A. Azadian, “A comprehensive review and classified comparison of MPPT algorithms in PV systems,” Energy Syst., vol. 13, no. 2, pp. 281–320, 2022.

S. Motahhir, A. El Hammoumi, and A. El Ghzizal, “The most used MPPT algorithms: Review and the suitable low-cost embedded board for each algorithm,” J. Clean. Prod., vol. 246, p. 118983, 2020.

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.

D. Ounnas, D. Guiza, Y. Soufi, and M. Maamri, “Design and hardware implementation of modified incremental conductance algorithm for photovoltaic system,” Adv. Electr. Electron. Eng., vol. 19, no. 2, pp. 100–111, 2021, doi: 10.15598/aeee.v19i2.3881.

S. Adhikari, Z. Lei, W. Peng, and Y. Tang, “A battery/supercapacitor hybrid energy storage system for DC microgrids,” in 2016 IEEE 8th International Power Electronics and Motion Control Conference (IPEMC-ECCE Asia), pp. 1747–1753, 2016.




DOI: https://doi.org/10.18196/jrc.v5i2.20581

Refbacks

  • There are currently no refbacks.


Copyright (c) 2024 Ashraf Abdualateef Mutlag, Mohammed 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