Lithium-ion energy storage battery in PV-smart building application Mohamed A. H. El-Sayed   2019/07/15

Abstract

Photovoltaic (PV) panels with energy storage batteries represents a feasible solution for powering domestic loads. The service life of the batteries and the power management are the main challenges by developing the energy supply system of smart homes. Therefore, in this paper an efficient algorithm is developed in order to power a house by extracting the maximum power from the PV panels, enhancing the battery service life and minimizing the power supply from the smart grid. The smart metering, advanced inverter and rule-based energy management strategy ensure safe and optimal operation of the energy supply system. Matlab/Simulink model of typical PV array, lithium-ion battery, inverter with the associated controllers are developed to evaluate the performance of the proposed system. Starting from the actual solar irradiance data, the maximum power of PV array will be extracted as a function of the available irradiance and ambient temperature. The daily battery state of charge (SOC) and its internal temperature are calculated depending on the load, PV power and the battery charge/discharge modes. Simulation results show that the proposed algorithm can enhance the performance of energy supply system, extract the maximum solar power and minimize the power from smart grid.

Authors and affiliations

Mohamed A. H. El-Sayed
Department of Electrical Engineering, College of Engineering and Petroleum, Kuwait University

Key words

PV array, MPPT controller, Li-ion storage battery, energy management, hybrid power system.

References

[1] Bach, B., Willhelmer, D. and Palensky, P. (2010), “Smart buildings, smart cities and governing innovation in the new millenium”, 8th IEEE International Conference on Industrial Informatics (INDIN), IEEE, Osaka, pp. 8-14
[2] A. Abdon, X. Zhang, D. Parra, M.K. Patel, C. Bauer, J. Worlitschek, "Techno-economic and environmental assessment of stationary electricity storage technologies for different time scales", Energy, Jul. 2017.
[3] Liu, W.-H.E.; Liu, K.; Pearson, D.,” Consumer-centric smart grid “, IEEE PES Innovative Smart Grid Technologies (ISGT), 2011, Page(s): 1 – 6.
[4] S. Saponara and T. Bacchillone. Network architecture, security issues, and hardware implementation of a home area network for smart grid. Journal of Computer Networks and Communications, 2012,
[5] K. Mets, M. Strobbe, T. Verschueren, T. Roelens, F. De Turck, and C. Develder. Distributed multi-agent algorithm for residential energy management in smart grids. In Network Operations and Management Symposium (NOMS'2012), pages 435- 443, 2012.
[6] M. Ahangari Hassas , K. Pourhossein, Control and Management of Hybrid Renewable Energy Systems: Review and Comparison of Methods, Journal of Operation and Automation in Power Engineering Vol. 5, No. 2, Dec. 2017, Pages: 131-138
[7] Wang, Z., Wang, L., Dounis, A.I. and Yang, R. (2012), “Multi-agent control system with information fusion based comfort model for smart buildings”, Applied Energy, Vol. 99, pp. 247-254.
[8] Tarun Huria, Massimo Ceraolo , Javier Gazzarri, Robyn Jackey , High Fidelity Electrical Model with Thermal Dependence for Characterization and Simulation of High Power Lithium Battery Cells, 4-8 March 2012, 2012 IEEE International Electric Vehicle Conference, Greenville, SC, USA
[9] G. Fortino and A. Guerrieri. Decentralized management of building indoors through embedded software agents. Computer Science and Information Systems, 9(3):1331{1359, 2012.
[10] Soares A., A. Gomes, and C.H. Antunes. 2012. Integrated management of residential energy resources. EPJ web of conferences. 33:05005.
[11] Mohamed A. El-Sayed, Steven Leeb, Evaluation of Maximum Power Point Tracking Algorithms for Photovoltaic Electricity Generation in Kuwait, Renewable Energy and Power Quality Journal (RE&PQJ) ISSN 2172-038 X, No.12, April 2014
[12] Mohamed A. El-Sayed, Steven Leeb, Fuzzy Logic Based Maximum Power Point Tracking Using Boost Converter for Solar Photovoltaic System in Kuwait", Renewable Energy and Power Quality Journal (RE&PQJ) ISSN 2172-038 X, No.13, April 2015
[13] Ryu Ishizaki, Lei Lin, Naoki Kawarabayashi, Masahiro Fukui, "An SOC Estimation System for Lithium ion Batteries Considering Thermal Characteristics", The 19th Workshop on Synthesis And System Integration of Mixed Information technologies, SASIMI 2015, 16 - 17 March, 2015. Yilan, Taiwan.
[14] A. L. Emelina, M. A. Bykov, M. L. Kovba, B. M. Senyavin, E. V. Golubina, "Thermochemical properties of lithium cobaltate". Russian Journal of Physical Chemistry, volume 85, issue 3, pp 357–363, (2011).
[15] Cong Zhu, Xinghu Li, Lingjun Song, Liming Xiang, Development of a theoretically based thermal model for lithium ion battery pack, Journal of Power Sources, Volume 223, 1 February 2013, Pages 155-164.
[16] P. Kreczanik, P. Venet, A. Hijazi and G. Clerc, "Study of Supercapacitor Aging and LifetimeEstimation According to Voltage, Temperature, and RMS Current," in IEEE Transactions on Industrial Electronics, vol. 61, no. 9, pp. 4895-4902, Sept. 2014.