Kontrol Tegangan pada Sistem Hybrid Panel Surya-Turbin Angin Menggunakan Manajemen Penyimpanan Baterai

Soedibyo Soedibyo, Rezi Delfianti, Feby Agung Pamuji, Mochamad Ashari


The purpose of this paper is to determine the control strategy of the renewable energy systems of hybrid solar panel power and wind turbines in maximizing voltage balance. The voltage control strategy needs to be designed, mainly when different load changes occur. If it is not done, it will affect the balance of power supplied to the load and usually damage the equipment used. Solar and wind energy sources significantly influence the stability of the applied voltage’s quality due to the fluctuating nature of renewable energy. This paper proposes control strategies for the use of PIs and the signal conditioning devices that are modified using the battery charging and discharging modeling while taking into account battery lifetime using PSIM software so that optimal voltage results from hybrid solar panel and wind turbine systems are obtained. The battery will be used as energy storage when the hybrid output power is over, which will then be used again when the hybrid output power is less than the load requirement. The signal conditioning device in this study uses five power converters, one AC to DC converter, two DC-DC boost converters, one bidirectional converter, 1 DC-AC bidirectional converter. Maximum output power uses MPPT, which is applied to the boost converter, whereas to regulate the voltage through charging and discharging the battery through the bidirectional buck-boost converter. This strategy provides the appropriate voltage on the AC side.


voltage; solar panel; wind turbines; pi modified; charging-discharging

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L. Xu, X. Ruan, C. Mao, B. Zhang, and Y. Luo, “An improved optimal sizing method for wind-solar-battery hybrid power system,” IEEE Trans. Sustain. Energy, vol. 4, no. 3, pp. 774–785, 2013.

S. Ananda, N. Lakshminarasamma, V. Radhakrishna, M. S. Srinivasan, P. Satyanarayana, and M. Sankaran, “Generic Lithium ion battery model for energy balance estimation in spacecraft,” Proc. 2018 IEEE Int. Conf. Power Electron. Drives Energy Syst. PEDES 2018, pp. 1–5, 2018.

K. C. Bae, S. C. Choi, J. H. Kim, C. Y. Won, and Y. C. Jung, “LiFePO4 dynamic battery modeling for battery simulator,” Proc. IEEE Int. Conf. Ind. Technol., pp. 354–358, 2014.

Y. M. Mendi, “Flexible energy saving solution: An assessment of energy storage systems for photovoltaics & benefits to the grid-connected systems,” EEEIC 2016 - Int. Conf. Environ. Electr. Eng., 2016.

A. H. Ranjbar, A. Banaei, A. Khoobroo, and B. Fahimi, “Online estimation of state of charge in li-ion batteries using impulse response concept,” IEEE Trans. Smart Grid, vol. 3, no. 1, pp. 360–367, 2012.

C. F. Abe, J. B. Dias, P. Poggi, and B. Pillot, “Combining Identification and Translation Methods of the Single-Diode Model to Compute the Average Temperature of Photovoltaic Modules from the Open-Circuit Voltage,” IEEE J. Photovoltaics, vol. 9, no. 5, pp. 1398–1404, 2019.

F. Ding, P. Li, B. Huang, F. Gao, C. Ding, and C. Wang, “Modeling and simulation of grid-connected hybrid photovoltaic/battery distributed generation system,” 2010 China Int. Conf. Electr. Distrib. CICED 2010, pp. 1–10, 2010.

S. Almazrouei and A. Hamid, “Energy Management for Large-Scale Grid Connected PV-Batteries System,” 2017 Int. Renew. Sustain. Energy Conf., pp. 1–5, 2017.

D. T. Cotfas, P. A. Cotfas, C. Samoila, and D. Ursutiu, “Energy balance for different positions of photovoltaic panels,” pp. 12–15, 2012.

K. Plachta, “Autonomous tracking controller for photovoltaic systems using global positioning system,” 2018 IEEE Int. Conf. Environ. Electr. Eng. 2018 IEEE Ind. Commer. Power Syst. Eur. (EEEIC / I&CPS Eur., pp. 1–5, 2018.

DOI: https://doi.org/10.17529/jre.v16i3.16010


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