Efficient Operation of Lithium-Ion Batteries Based on GPV-Forecasted PV Output

Authors

  • Ahmad Syahiman Mohd Shah Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia.
  • Mohamad Shaiful Abdul Karim Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia.
  • Mohd Shawal Jadin Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia.
  • Airul Sharizli Abdullah Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia.
  • Ruhaizad Ishak Faculty of Electrical and Electronic Engineering, Universiti Malaysia Pahang, Pekan, Pahang, Malaysia.
  • Yuki Ishikawa Department of Electrical and Electronic Engineering, Ibaraki University, Hitachi, Ibaraki, Japan.
  • Hiroki Takahashi Department of Electrical and Electronic Engineering, Ibaraki University, Hitachi, Ibaraki, Japan.
  • Suguru Odakura Department of Electrical and Electronic Engineering, Ibaraki University, Hitachi, Ibaraki, Japan.
  • Naoto Kakimoto Department of Electrical and Electronic Engineering, Ibaraki University, Hitachi, Ibaraki, Japan.

Keywords:

Batteries, Energy Management, Photovoltaic, PV Forecasting,

Abstract

Load forecasting is essential in order to fulfil a demand of the consumer. Nevertheless, for a small-scale Battery Energy Storage System (BESS) based on sole photovoltaic (PV), it needs a very strong effort to always meet a consumer's demand due to unstable meteorological conditions. An ideal PV system requires a constructive control strategy in order to alleviate its fluctuating output. In this study, an energy control scheme that executes next-day forecast of generation for the purpose of fully utilizing the stored energy in the batteries has been proposed. Experimental equipment was structured and the operation was completely administered by RX621 microcontroller. The implemented system worked very well without any distractions and it succeeded in controlling and preventing the batteries from being over-charged or overdischarged. Impressively, average consumption for September 2015 is considerably high, which suggests that the proposed control succeeded in utilizing energy corresponded to 98.6 % of the monthly-average generation.

References

J. Han, C-S. Choi, I. Lee and S-H. Kim, “Smart Home Energy Management System Including Renewable Energy Based on ZigBee and PLC,” IEEE Trans. Consum. Electron., vol. 60, no. 2, pp. 198-202, May 2014.

J. Han, C-S. Choi and I. Lee, “More Efficient Home Energy Management System Based on Zigbee Communication and Infrared Remote Controls,” IEEE Trans. Consum. Electron., vol. 57, no. 1, pp. 85-89, Feb. 2011.

H. Kim, S. K. Lee, H. Kim and H. Kim, “Implementing home energy management system with UPnP and mobile applications,” ScienceDirect Comput Commun., vol. 36, pp. 51-62, 2012.

H-L. Jou, Y-H. Chang, J-C. Wu and K-D. Wu, “Operation strategy for a lab-scale grid-connected photovoltaic generation system integrated with battery energy storage,” ScienceDirect Energy Convers. Manag., vol. 111, pp. 853-861, 2013.

H. Ohtake, K. Shimose, J. G. d. S. Fonseca Jr., T. Takashima, T. Oozeki and Y. Yamada, “Accuracy of the solar irradiance forecasts of the Japan Meteorological Agency mesoscale model for the Kanto region, Japan,” ScienceDirect Solar Energy, vol. 98, pp. 138-152, Dec. 2013.

J. Almorox, “Estimating global solar irradiation from common meteorological data in Aranjuez, Spain,” Turkish J. Phys., vol. 35, pp. 53-64, 2011.

A. S. B. M. Shah, H. Yokoyama and N. Kakimoto, “High-Precision Forecasting Model of Solar Irradiance Based on Grid Point Value Data Analysis for an Efficient Photovoltaic System,” IEEE Trans. Sustain. Energy, vol. 6, no. 2, pp. 474-481, Apr. 2015.

A. S. M. Shah, Y. Ishikawa, S. Odakura and N. Kakimoto, “Numerical Model of Energy Control for Lithium-Ion Batteries Based on PV System,” Int. J. SIM. Syst. Sci. Technol., to be published.

Q. Guo, S. Chen and X. Qin, “ZnOSnO2/graphene composites as high capacity anode materials for lithium-ion batteries,” ScienceDirect Mater. Lett., vol. 128, pp. 50-53, 2014.

K. Darcovich, E. R. Henquin, B. Kenney, I. J. Davidson, N. Saldanha and I. B-Morrison, “Higher-capacity lithium-ion battery chemistries for improved residential energy storage with micro-cogeneration,” ScienceDirect Appl. Energy, vol. 111, pp. 853-861, 2013.

X. Li, D. Hui and X. Lai, “Battery Energy Storage Station (BESS)- Based Smoothing Control of Photovoltaic (PV) and Wind Power Generation Fluctuations,” IEEE Trans. Sustain. Energy, vol. 4, no. 2, pp. 464-473, Apr. 2013.

N. Kakimoto, S. Matsumura, K. Kobayashi and M. Shoji, “Two-state Markov Model of Solar Radiation and Consideration on Storage Size,” IEEE Trans. Sustain. Energy, vol. 5, no. 1, pp. 171-181, Jan. 2014.

S. Piller, M. Perrin and A. Jossen, “Methods for state-of-charge determination and their applications,” J. Power Sources, vol. 96, pp. 113-120, 2001.

H. Wang, Y. Liu, H. Fu and G. Li, “Estimation of State of Charge of Batteries for Electric Vehicles,” Int. J. Control Autom., vol. 6, no.2, pp. 185-194, Apr. 2013.

J. W. Overall, “The Used of The skew T, Log P Diagram in Analysis and Forecasting,” HQ AWS/XT, Scott AFB, IL, Tech. Rep., AWS/TR- 79/006, Mar. 1990.

S. Daimon, “Time-Sequence Forecast based on Cloud’s Sectional View: Utilization of Numerical Prediction (in Japanese),” Tenki, vol. 54, pp. 975-976, Nov. 2007.

Hitachi City Hall. (2015, Mar.) Index of Observed Weather Database for Hitachi (Japanese) [Online]. Available: http://www.jsdi.or.jp/~hctenso/.

M. Tomokazu, M. Yukitaka and H. Keizoh, “Estimation of State of Charge of Batteries for Electric Vehicles (in Japanese),” Toshiba Rev., vol. 68, no. 10, pp. 54-57, 2013.

Renesas Elect. Corp. (2010, Feb.). RX62N, RX621. [Online]. Available: http://am.renesas.com/products/mpumcu/rx/rx600/rx62162n/index.jsp

Japan Meteorology Agency (JMA). (2015, Feb.) Index of Weather Data based on GPV Numerical Prediction [Online]. Available: http://database.rish.kyoto-u.ac.jp/arch/jmadata/data/gpv/original/.

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Published

2018-01-18

How to Cite

Mohd Shah, A. S., Abdul Karim, M. S., Jadin, M. S., Abdullah, A. S., Ishak, R., Ishikawa, Y., Takahashi, H., Odakura, S., & Kakimoto, N. (2018). Efficient Operation of Lithium-Ion Batteries Based on GPV-Forecasted PV Output. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-2), 161–167. Retrieved from https://jtec.utem.edu.my/jtec/article/view/3344