How to search?
advanced search

Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 9
items per page: 25 50 75
Sort by:

A control topology for frequency regulation capability in a grid integrated PV system

Ritesh Kumar Balakrushna Sahu Chandan Kumar Shiva B. Rajender
Archives of Electrical Engineering | 2020 | vol. 69 | No 2 | 389-401 | DOI: 10.24425/aee.2020.133033
Keywords frequency controller maximum power point tracking (MPPT) photovoltaic (PV) power system pseudo maximum power point tracking (PMPPT)
Download PDF Download RIS Download Bibtex

Abstract

Photovoltaic (PV) cells are very costly because of the silicon element which is not cheaply available. Usually, PV cells are preferred to be used at maximum efficiency. Therefore, PV plants are emphasized to extract maximum power from PVcells. When inertia free PV plants are integrated into the grid in large numbers, the problem of maintaining system stability subjected to load perturbation is quite difficult. In response to this, a control topology is being an approach to make available the PV cells in maintaining system stability by utilizing the system frequency deviation as feedback to the controller. To implement this, the PVs are operated at Maximum Power Point Tracking (MPPT). This allows the PV to operate at Pseudo Maximum Power Point tracking (PMPPT) which makes it possible to run the PV with reserve power capacity without employing a battery for storage. The control strategy has been implemented over a two-stage power conversion model of the PV system. The simulation results showed that the proposed control PMPPT topology is effective in frequency regulation capability as compared to the MPPT technique.

Go to article

Authors and Affiliations

Ritesh Kumar
Balakrushna Sahu
Chandan Kumar Shiva
B. Rajender

A Hybrid Maximum Power Point Search Method Using Temperature Measurements in Partial Shading Conditions

Janusz Mroczka Mariusz Ostrowski
Metrology and Measurement Systems | 2014 | No 4 | 733-740 | DOI: 10.2478/mms-2014-0056
Keywords maximum power point partial shading perturb and observe temperature measurement
Download PDF Download RIS Download Bibtex

Abstract

Photovoltaic panels have a non-linear current-voltage characteristics to produce the maximum power at only one point called the maximum power point. In the case of the uniform illumination a single solar panel shows only one maximum power, which is also the global maximum power point. In the case an irregularly illuminated photovoltaic panel many local maxima on the power-voltage curve can be observed and only one of them is the global maximum. The proposed algorithm detects whether a solar panel is in the uniform insolation conditions. Then an appropriate strategy of tracking the maximum power point is taken using a decision algorithm. The proposed method is simulated in the environment created by the authors, which allows to stimulate photovoltaic panels in real conditions of lighting, temperature and shading.

Go to article

Authors and Affiliations

Janusz Mroczka
Mariusz Ostrowski

Development of rapid and reliable cuckoo search algorithm for global maximum power point tracking of solar PV systems in partial shading condition

Khadidja Bentata Ahmed Mohammedi Tarak Benslimane
Archives of Control Sciences | 2021 | vol. 31 | No 3 | 495-526 | DOI: 10.24425/acs.2021.138690
Keywords photovoltaic system maximum power point tracking partial shading cuckoosearch algorithm
Download PDF Download RIS Download Bibtex

Abstract

The solar photovoltaic output power fluctuates according to solar irradiation, temperature, and load impedance variations. Due to the operating point fluctuations, extracting maximum power from the PV generator, already having a low power conversion ratio, becomes very complicated. To reach a maximum power operating point, a maximum power point tracking technique (MPPT) should be used. Under partial shading condition, the nonlinear PV output power curve contains multiple maximum power points with only one global maximum power point (GMPP). Consequently, identifying this global maximum power point is a difficult task and one of the biggest challenges of partially shaded PV systems. The conventional MPPT techniques can easily be trapped in a local maximum instead of detecting the global one. The artificial neural network techniques used to track the GMPP have a major drawback of using huge amount of data covering all operating points of PV system, including different uniform and non-uniform irradiance cases, different temperatures and load impedances. The biological intelligence techniques used to track GMPP, such as grey wolf algorithm and cuckoo search algorithm (CSA), have two main drawbacks; to be trapped in a local MPP if they have not been well tuned and the precision-transient tracking time complex paradox. To deal with these drawbacks, a Distributive Cuckoo Search Algorithm (DCSA) is developed, in this paper, as GMPP tracking technique. Simulation results of the system for different partial shading patterns demonstrated the high precision and rapidity, besides the good reliability of the proposed DCSAGMPPT technique, compared to the conventional CSA-GMPPT.
Go to article

Bibliography

[1] Zhao Zhuoli, Runting Cheng, Baiping Yan, Jiexiong Zhang, Ze- han Zhang, Mingyu Zhang, and Loi Lei Lai: A dynamic particles MPPT method for photovoltaic systems under partial shading conditions. Energy Conversion and Management, 220 (2020), 113070, DOI: 10.1016/j.enconman.2020.113070.
[2] Nabil A. Ahmed and Masafumi Miyatake: A novel maximum power point tracking for photovoltaic applications under partially shaded insolation conditions. Electric Power Systems Research, 78(5), (2008), 777–784, DOI: 10.1016/j.epsr.2007.05.026.
[3] Liqun Liu, Xiaoli Meng, and Chunxia Liu: A review of maximum power point tracking methods of PV power system at uniform and partial shading. Renewable and Sustainable Energy Reviews, 53 (2016), 1500–1507, DOI: 10.1016/j.rser.2015.09.065.
[4] Yanzhi Wang, Xue Lin, Younghyun Kim, Naehyuck Chang, and Mas- soud Pedram: Enhancing efficiency and robustness of a photovoltaic power system under partial shading. Thirteenth International Symposium on Quality Electronic Design (ISQED), Santa Clara USA, (2012), 592–600, DOI: 10.1109/ISQED.2012.6187554.
[5] Ricardo Orduz, Jorge Solorzano, Miguel Ángel Egido, and Ed- uardo Roman: Analytical study and evaluation results of power optimizers for distributed power conditioning in photovoltaic arrays. Progress in Photovoltaics: Research and Applications, 21(3), (2013), 359–373, DOI: 10.1002/pip.1188.
[6] Kashif Ishaque and Zainal Salam: A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition. Renewable and Sustainable Energy Reviews, 19 (2013), 475–488, DOI: 10.1016/j.rser.2012.11.032.
[7] Jubaer Ahmed and Zainal Salam: A critical evaluation on maximum power point tracking methods for partial shading in PV systems. Renewable and Sustainable Energy Reviews, 47 (2015), 933–953, DOI: 10.1016/j.rser.2015.03.080.
[8] Ali M. Eltamaly: Performance of MPPT techniques of photovoltaic systems under normal and partial shading conditions. Advances in Renewable Energies and Power Technologies, vol. 1, Solar and Wind Energies, I. Yahyaoui, 2018, Elsevier, Chapter 4, 115–161.
[9] Ali M. Eltamaly: Performance of smart maximum power point tracker under partial shading conditions of photovoltaic systems. Journal ofRenewable and Sustainable Energy, 7(4), (2015), 043141, DOI: 10.1063/1.4929665.
[10] A. Talha, H. Boumaaraf, and O. Bouhali: Evaluation of maximum power point tracking methods for photovoltaic systems. Archives of Control Sciences, 21(2), (2011), 151–165.
[11] Hegazy Rezk and Ali M. Eltamaly: A comprehensive comparison of different MPPT techniques for photovoltaic systems. Solar Energy, 112 (2015), 1–11, DOI: 10.1016/j.solener.2014.11.010.
[12] S. Lyden and M.E. Haque: Maximum power point tracking techniques for photovoltaic systems: A comprehensive review and comparative analysis. Renewable and Sustainable Energy Reviews, 52 (2015): 1504–1518, DOI: 10.1016/j.rser.2015.07.172.
[13] Zainal Salam, Jubaer Ahmed, and Benny S. Merugu: The application of soft computing methods for MPPT of PV system: A technological and status review. Applied Energy, 107 (2013), 135–148, DOI: 10.1016/j.apenergy.2013.02.008.
[14] Hassan M.H. Farh, Mohamed F. Othman, and Ali M. Eltamaly: Maximum power extraction from grid-connected PV system. Saudi Arabia Smart Grid (SASG), (2017), 1–6, DOI: 10.1109/SASG.2017.8356498.
[15] Seyedali Mirjalili, Seyed Mohammad Mirjalili, and Andrew Lewis: GreyWolf optimizer. Advances in Engineering Software, 69 (2014), 46–61, DOI: 10.1016/j.advengsoft.2013.12.007.
[16] Sabrina Titri, Cherif Larbes, Kamal Youcef Toumi, and Karima Be- natchba: A new MPPT controller based on the ant colony optimization algorithm for photovoltaic systems under partial shading conditions. Applied Soft Computing, 58 (2017), 465–479, DOI: 10.1016/j.asoc.2017.05.017.
[17] Lian Lian Jiang, Douglas L. Maskell, and Jagdish C. Patra:Anovel ant colony optimization-based maximum power point tracking for photovoltaic systems under partially shaded conditions. Energy and Buildings, 58 (2013), 227–236, DOI: 10.1016/j.enbuild.2012.12.001.
[18] Lian Lian Jiang, R. Srivatsan, and Douglas L. Maskell: Computational intelligence techniques for maximum power point tracking in PV systems: A review. Renewable and Sustainable Energy Reviews, 85 (2018), 14–45, DOI: 10.1016/j.rser.2018.01.006.
[19] Ali M. Eltamaly and Hassan M.H. Farh: Dynamic global maximum power point tracking of the PV systems under variant partial shading using hybrid GWO-FLC. Solar Energy, 177 (2019), 306–316, DOI: 10.1016/j.solener.2018.11.028.
[20] Jubaer Ahmed and Zainal Salam: A maximum power point tracking (MPPT) for PV system using cuckoo search with partial shading capability. Applied Energy, 119 (2014), 118–130, DOI: 10.1016/j.apenergy.2013.12.062.
[21] Xin-She Yang and Suash Deb: Cuckoo search via Lévy flights. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), Coimbatore, India (2009), 210–214, DOI: 10.1109/NABIC.2009.5393690.
[22] Jubaer Ahmed and Zainal Salam: A soft computing MPPT for PV system based on cuckoo search algorithm. 4th International Conference on Power Engineering, Energy and Electrical Drives, Istanbul, Turkey, (2013), 558– 562, DOI: 10.1109/PowerEng.2013.6635669.
[23] Ahmed A. El Baset, A. El Halim, Naggar H. , and Ahmed A. El Sattar: A comparative study between perturb and observe and cuckoo search algorithm for maximum power point tracking. 21st International Middle East Power Systems Conference (MEPCON), Cairo, Egypt, (2019), 716–723, DOI: 10.1109/MEPCON47431.2019.9008210.
[24] Filippo Spertino and Jean Sumaili Akilimali: Are manufacturing I–V mismatch and reverse currents key factors in large photovoltaic arrays? IEEE Transactions on Industrial Electronics, 56(11), (2009), 4520–4531, DOI: 10.1109/TIE.2009.2025712.
[25] M. Drif, P.J. Perez, J. Aguilera, and J.D. Aguilar: A new estimation method of irradiance on a partially shaded PV generator in grid-connected photovoltaic systems. Renewable Energy, 33(9), (2008), 2048–2056, DOI: 10.1016/j.renene.2007.12.010.
[26] Bidyadhar Subudhi and Raseswari Pradhan: A comparative study on maximum power point tracking techniques for photovoltaic power systems. IEEE Transactions on Sustainable Energy, 4(1), (2012), 89–98, DOI: 10.1109/TSTE.2012.2202294.
[27] Kashif Ishaque and Zainal Salam:AcomprehensiveMATLAB Simulink PV system simulator with partial shading capability based on two-diode model. Solar Energy, 85(9), (2011), 2217–2227, DOI: 10.1016/j.solener.2011.06.008.
[28] Mohamed I.Mosaad, M. Osama Abed el-Raouf, Mahmoud A. Al- Ahmar, and Fahd A. Banakher: Maximum power point tracking of PV system based cuckoo search algorithm; review and comparison. Energy Procedia, 162 (2019), 117–126, DOI: 10.1016/j.egypro.2019.04.013.
[29] Bo Yang, JingboWang, Xiaoshun Zhang, Tao Yu, Wei Yao, Hongchun Shu, Fang Zeng, and Liming Sun: Comprehensive overview of metaheuristic algorithm applications on PV cell parameter identification. Energy Conversion and Management, 208 (2020), 112595, DOI: 10.1016/j.enconman.2020.112595.
[30] Tong Kang, Jiangang Yao, Min Jin, Shengjie Yang, and Thanh Long Duong: A novel improved cuckoo search algorithm for parameter estimation of photovoltaic (PV) models. Energies, 11(5), (2018), 1060, DOI: 10.3390/en11051060.
[31] S. Walton, O. Hassan, K. Morgan, and M.R. Brown: Modified cuckoo search: a new gradient free optimisation algorithm. Chaos, Solitons & Fractals, 44(9), (2011), 710718, DOI: 10.1016/j.chaos.2011.06.004.
[32] Amir Hossein Gandomi, Xin-She Yang, and Amir Hossein Alavi: Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with Computers, 29(1), (2013), 17–35, DOI: 10.1007/s00366-011-0241-y.
[33] Abdesslem Layeb: A novel quantum inspired cuckoo search for knapsack problems. International Journal of Bio-Inspired Computation, 3(5), (2011), 297–305, DOI: 10.1504/IJBIC.2011.042260.
[34] Ehsan Valian, Saeed Tavakoli, Shahram Mohanna, and Atiyeh Haghi: Improved cuckoo search for reliability optimization problems. Computers & Industrial Engineering, 64(1), (2013), 459–468, DOI: 10.1016/j.cie.2012.07.011.
[35] Xiangtao Li, Jianan Wang, and Minghao Yin: Enhancing the performance of cuckoo search algorithm using orthogonal learning method. Neural Computing and Applications, 24(6), (2014), 1233–1247, DOI: 10.1007/s00521-013-1354-6.
[36] Hui Wang, Wenjun Wang, Hui Sun, Zhihua Cui, Shahryar Rahna- mayan, and Sanyou Zeng: A new cuckoo search algorithm with hybrid strategies for flow shop scheduling problems. Soft Computing, 21(15), (2017), 4297–4307, DOI: 10.1007/s00500-016-2062-9.
[37] Wang Jianzhou, He Jiang, Yujie Wu, and Yao Dong: Forecasting solar radiation using an optimized hybrid model by cuckoo search algorithm. Energy, 81 (2015), 627–644, DOI: 10.1016/j.energy.2015.01.006.
[38] Wen Long, Shaohong Cai, Jianjun Jiao, Ming Xu, and Tiebin Wu: A new hybrid algorithm based on grey wolf optimizer and cuckoo search for parameter extraction of solar photovoltaic models. Energy Conversion and Management, 203 (2020), 112243, DOI: 10.1016/j.enconman.2019.112243.
[39] Diego Oliva, Ahmed A. Ewees, Mohamed Abd El Aziz, Aboul Ella Hassanien, and Marco Perez-Cisneros: A chaotic improved artificial bee colony for parameter estimation of photovoltaic cells. Energies, 10(7), (2017), 865, DOI: 10.3390/en10070865.
[40] Xiaofang Yuan, Yuqing He, and Liangjiang Liu: Parameter extraction of solar cell models using chaotic asexual reproduction optimization. Neural Computing and Applications, 26(5), (2015), 1227–1239, DOI: 10.1007/s00521-014-1795-6.
[41] Xiaofang Yuan, Yongzhong Xiang, and Yuqing He: Parameter extraction of solar cell models using mutative-scale parallel chaos optimization algorithm. Solar Energy, 108 (2014), 238–251, DOI: 10.1016/j.solener.2014.07.013.
[42] Alireza Askarzadeh and Alireza Rezazadeh: Artificial bee swarm optimization algorithm for parameters identification of solar cell models. Applied Energy, 102 (2013), 943–949, DOI: 10.1016/j.apenergy.2012.09.052.
[43] Santhan Kumar Cherukuri and Srinivasa Rao Rayapudi: Enhanced grey wolf optimizer based MPPT algorithm of PV system under partial shaded condition. International Journal of Renewable Energy Development, 6(3), (2017), 203–212, DOI: 10.14710/ijred.6.3.203-212.
[44] Adeel Feroz Mirza, Qiang Ling, M. Yaqoob Javed, and Majad Man- soor: Novel MPPT techniques for photovoltaic systems under uniform irradiance and Partial shading. Solar Energy, 184 (2019), 628–648, DOI: 10.1016/j.solener.2019.04.034.
Go to article

Authors and Affiliations

Khadidja Bentata
1
Ahmed Mohammedi
2 3
Tarak Benslimane
4 5
ORCID: ORCID
  1. Laboratory Materials and Sustainable Development (LMDD), Electrical Engineering Department, Faculty of Science and Applied Sciences, University of Bouira, Algeria
  2. Electrical Engineering Department, Faculty of Science and Applied Sciences, University of Bouira, Algeria
  3. LTII Laboratory, University of Bejaia, Algeria
  4. Electrical Engineering Department, University of M’sila, Algeria
  5. SGRE Laboratory, University of Béchar, Algeria

Partial Shading Detection in Solar System Using Single Short Pulse of Load

Mateusz Bartczak
Metrology and Measurement Systems | 2017 | vol. 24 | No 1 | DOI: 10.1515/mms-2017-0016
Keywords maximum power point partial shading load pulse test station I−V curve
Download PDF Download RIS Download Bibtex

Abstract

A single photovoltaic panel under uniform illumination has only one global maximum power point, but the same panel in irregularly illuminated conditions can have more maxima on its power-voltage curve. The irregularly illuminated conditions in most cases are results of partial shading. In the work a single short pulse of load is used to extract information about partial shading. This information can be useful and can help to make some improvements in existing MPPT algorithms. In the paper the intrinsic capacitance of a photovoltaic system is used to retrieve occurrence of partial shading.

Go to article

Authors and Affiliations

Mateusz Bartczak

Control and optimisation of photovoltaic water pumping system using sliding mode

L. Zarour K. Abed M. Hacil A. Borni
Bulletin of the Polish Academy of Sciences Technical Sciences | 2019 | 67 | No. 3 | 605-611 | DOI: 10.24425/bpasts.2019.129658
Keywords photovoltaic pumping system modelling optimization maximum power point MPPT sliding mode control
Download PDF Download RIS Download Bibtex

Abstract

A sliding mode controller for the photovoltaic pumping system has been proposed in this paper. This system is composed of a photovoltaic generator supplying a three-phase permanent magnet synchronous motor coupled to a centrifugal pump through a three-phase voltage inverter. The objective of this study is to minimise the number of regulators and apply the sliding mode control by exploiting the specification of the field oriented control scheme (FOC). The first regulator is used to force the photovoltaic generator to operate at the maximum power point, while the second is used to provide the field oriented control to improve the system performance.The whole system is analysed and its mathematical model is done. Matlab is used to validate the performance and robustness of the proposed control strategy.

Go to article

Authors and Affiliations

L. Zarour
K. Abed
M. Hacil
A. Borni

Maximum power point tracking techniques for low-cost solar photovoltaic applications – Part II: Mathematical Calculation and Measurement and Comparison, criteria on choices and suitable MPPT techniques

Tole Sutikno Arsyad Cahya Subrata Giovanni Pau Awang Jusoh Kashif Ishaque
Archives of Electrical Engineering | 2023 | vol. 72 | No 2 | 299-322 | DOI: 10.24425/aee.2023.145410
Keywords incremental conductance maximum power point tracking measurement and comparison perturb and observe solar photovoltaic (PV) trial-and-error
Download PDF Download RIS Download Bibtex

Abstract

In the last decade, there has been a substantial surge in the advancement of research into the maximum power point tracking (MPPT) controller. The MPPT approaches, on the other hand, continue to be in high demand due to the ease and simplicity with which tracking techniques can be implemented on the maximum power point (MPP). Diverse MPPT approaches and their modifications from various literature are categorized and thoroughly explored in this work, which is divided into two sections. The discussions are centered on the primary goal of attaining the most extraordinary feasible MPPT technique that produces the best results at the lowest possible expense. In order to determine which MPPT approaches to use, evaluations from earlier literature are used to guide the decision. In this section, we will examine the evaluation of the MPPT technique in two sections. Previously, in Part I, we explored the MPPT techniques based on constant parameters and trial-and- error. Part II of this article will examine the MPPT technique, which is based on mathematical computation, measurement, and comparison, and the algorithm development that has occurred in recent years. Furthermore, this section’s assessment for selecting MPPT approaches is based on previous literature reviews. To aid with this selection, the following criteria for the MPPT approach are proposed: sensors and analog/digital requirements, costeffectiveness, simplicity, stability, efficiency, and tracking speed. This enables the reader to select the MPPT technique that is most appropriate for their application.
Go to article

Authors and Affiliations

Tole Sutikno
1
ORCID: ORCID
Arsyad Cahya Subrata
1
ORCID: ORCID
Giovanni Pau
2
ORCID: ORCID
Awang Jusoh
3
ORCID: ORCID
Kashif Ishaque
4
ORCID: ORCID
  1. Department of Electrical Engineering, Universitas Ahmad Dahlan Yogyakarta, Indonesia
  2. Faculty of Engineering and Architecture, Kore University of Enna, Italy
  3. School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  4. Capital University of Science & Technology, Islamabad, Pakistan

Maximum power point tracking techniques for low-cost solar photovoltaic applications – Part I: constant parameters and trial-and-error

Tole Sutikno Arsyad Cahya Subrata Giovanni Pau Awang Jusoh Kashif Ishaque
Archives of Electrical Engineering | 2023 | vol. 72 | No 1 | 125-145 | DOI: 10.24425/aee.2023.143693
Keywords incremental conductance maximum power point tracking measurement and comparison perturb and observe solar photovoltaic (PV) trial-and-error
Download PDF Download RIS Download Bibtex

Abstract

The development of research on the maximum power point tracking (MPPT) controller has increased significantly in this decade. The MPPT technique, however, is still demanding because of the ease and simplicity of implementing tracking technique on the maximum power point (MPP). In this paper, MPPT techniques and their modifications from various literature are classified and examined in detail. The discussions are focused on the main objective of obtaining the best possible MPPT technique with the best results at a low cost. The assessment for the selection of MPPT techniques is based on assessments from the previous literature. The discussion of the MPPT technique assessment is divided into two parts. In Part I, the MPPT technique based on constant parameters, and trial-and-error will be discussed in detail, along with its algorithm development in recent times.
Go to article

Authors and Affiliations

Tole Sutikno
1
ORCID: ORCID
Arsyad Cahya Subrata
1
ORCID: ORCID
Giovanni Pau
2
ORCID: ORCID
Awang Jusoh
3
ORCID: ORCID
Kashif Ishaque
4
ORCID: ORCID
  1. Department of Electrical Engineering, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
  2. Faculty of Engineering and Architecture, Kore University of Enna, Italy
  3. School of Electrical Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Johor Bahru, Malaysia
  4. Capital University of Science and Technology, Islamabad, Pakistan

A performance analysis of a hybrid golden section search methodology and a nature-inspired algorithm for MPPT in a solar PV system

Hazem H. Mostafa Amr M. Ibrahim Wagdi R. Anis
Archives of Electrical Engineering | 2019 | vol. 68 | No 3 | 611-627 | DOI: 10.24425/aee.2019.129345
Keywords hybrid optimization golden sections search multi-verse optimization algo-rithm maximum power point tracking perturb and observe photovoltaic (PV)
Download PDF Download RIS Download Bibtex

Abstract

This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS-PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.

Go to article

Authors and Affiliations

Hazem H. Mostafa
Amr M. Ibrahim
Wagdi R. Anis

Simulation of the proposed combined Fuzzy Logic Control for Maximum Power Point Tracking and Battery Charge Regulation used in CubeSat

Abderrahmane Seddjar Kamel Djamel Eddine Kerrouche Lina Wang
Archives of Electrical Engineering | 2020 | vol. 69 | No 3 | 521-543 | DOI: 10.24425/aee.2020.133916
Keywords combined Fuzzy Logic Control Electrical Power System Photovoltaic system Maximum Power Point Tracking Battery Charge Regulation Perturb and Observe CubeSat
Download PDF Download RIS Download Bibtex

Abstract

One of the most critical systems of any satellite is the Electrical Power System (EPS) and without any available energy, the satellite would simply stop to function. Therefore, the presented research within this paper investigates the areas relating to the satellite EPS with the main focus towards the CubeSat platform. In this paper, an appropriate EPS architecture with the suitable control policy for CubeSat missions is proposed. The suggested control strategy combines two methods, the Maximum Power Point Tracking (MPPT) and the Battery Charge Regulation (BCR), in one power converter circuit, in order to extract the maximum power of the Photovoltaic (PV) system and regulate the battery voltage from overcharging. This proposed combined control technique is using a Fuzzy Logic Control (FLC) strategy serving two main purposes, the MPPT and BCR. Without an additional battery charger circuit and without switching technique between the two controllers, there are no switching losses and the efficiency of the charging characteristic can be increased by selecting this proposed combined FLC. By testing a space-based PV model with the proposed EPS architecture, some simulation results are compared to demonstrate the superiority of the proposed control strategy over the conventional strategies such as Perturb and Observe (P&O) and FLC with a Proportional Integral Derivative (PID) controller.

Go to article

Authors and Affiliations

Abderrahmane Seddjar
Kamel Djamel Eddine Kerrouche
Lina Wang

This page uses 'cookies'. Learn more