Optimal Energy Storage Sizing in Photovoltaic and Wind Hybrid Power System Meeting Demand-Side Management Program in Viet Nam

  • Nguyen Minh Cuong Electrical Faculty, Thai Nguyen University of Technology, Thai Nguyen, Viet Nam
  • Thai Quang Vinh Institute of Information Technology, Vietnam Academy of Science and Technology, Hanoi, Viet Nam
  • Le Tien Phong Electrical Faculty, Thai Nguyen University of Technology, Thai Nguyen, Viet Nam
  • Vu Phuong Lan Electrical Faculty, Thai Nguyen University of Technology, Thai Nguyen, Viet Nam


This paper proposes a new method to determine optimal energy storage sizing in photovoltaic and wind hybrid power generation systems. These generations are placed in a scheme of three blocks to forecast, measure, dispatch/control and distribute power flows in whole system to meet requirements of the demand-side management program in Viet Nam. Data about electric load power, power of solar irradiance, ambient temperature, wind speed and other weather conditions must be forecasted in a high accuracy. An algorithm to determine the optimal sizing is designed basing on forecasting data, constraints, the relation of quantities in whole system and the capability to charge/discharge energy of energy storage. The optimal sizing in this research helps to rearrange load diagrams that compensates deficient energy completely in stages having high and medium price levels. It can be applied at each bus to reduce cost for buying electricity from electric power system. The new proposal is illustrated by simulation results in a case study carried out by MATLAB 2017a.


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[1] Jingpeng Yue, Zhijian Hu, Chendan Li, J. C. Vasquez, Josep M. Guerrero (2017), “Economic Power Schedule and Transactive Energy through Intelligent Centralized Energy Management System for DC Residential Distribution System”, Energy, ISSN: 0360-5442, Vol. 10, 916.
[2] Felix Iglesias Vazquez, Peter Palensky, Sergio Cantos (2012), "Demand Side Management for Stand-Alone Hybrid PowerSystems Based on Load Identification", Energy, 5, 4517, ISSN: 0360-5442.
[3] Zafar Iqbal, Nadeem Javaid, Saleem Iqbal, Sheraz Aslam, Zahoor Ali Khan, Wadood Abdul, Ahmad Almogren, and Atif Alamri (2018), “A Domestic Microgrid with Optimized Home Energy Management System”, Energy, 11, 1002, ISSN: 0360-5442.
[4] Andrzej Ozadowicz (2017), “A New Concept of Active Demand Side Management for Energy Efficient Prosumer Microgrids with Smart Building Technologie”, Energy, 10, 1771, ISSN: 0360-5442.
[5] Olivier Gergaud, Gaël Robin, Bernard Multon, Hamid Ben Ahmed (2003), “Energy Modeling of a Lead-Acid Battery within Hybrid Wind/Photovoltaic Systems”, European Power Electronic Conference, ISBN: 90-75815-07-7.
[6] Nadeem Javaid, Sakeena Javaid 1, Abdul Wadood, Imran Ahmed, Ahmad Almogren, Atif Alamri, Iftikhar Azim Niaz (2017), “A hybrid genetic wind driven heuristic optimization algorithm for demand side management in smart grid”, Energy, 10, 3, ISSN: 0360-5442.
[7] http://npc.com.vn/bieugiabandien.aspx
[8] https://www.evn.com.vn/c3/evn-va-khach-hang/Gia-ban-dien-theo-gio-9-81.aspx
[9] Jong Hwan Lim (2012), “Optimal Combination and Sizing of a New and Renewable Hybrid Generation System”, International Journal of Future Generation Communication and Networking, Vol. 5, No. 2, June, ISSN: 2207-9645.
[10] Guido Carpinelli, Anna Rita di Fazio, Shahab Khormali, and Fabio Mottola (2014), “Optimal Sizing of Battery Storage Systems for Industrial Applications when Uncertainties Exist”, Energy, ISSN: 0360-5442, Vol. 7.
[11] Jeremy Dulout, Amjad Anvari-Moghaddam, Adriana Luna, Bruno Jammes, Corinne Alonso, Josep Guerrero (2017), “Optimal sizing of a lithium battery energy storage system for grid-connected photovoltaic systems”, IEEE Second International Conference on DC Microgrids (ICDCM), ISBN: 978-1-5090-4479-5.
[12] Rajesh Kamble, Gauri Karve, Amarnath Chakradeo, Geetanjali Vaidya (2018), “Optimal sizing of Battery Energy Storage System in Microgrid by using Particle Swarm Optimization Technique”, Journal of Integrated Science and Technology, Vol. 6, ISSN: 2321-4635.
[13] Safa Fezai, Jamel Belhadj (2014), “Optimal sizing of a Stand-alone photovoltaic system using statistical approach”, International Journal of Renewable Energy Research, Vol. 4, No. 2, ISSN: 1309-0127.
[14] Xin Liu, Hong-Kun Chen, Bing-Qing Huang, and Yu-Bo Tao (2017), “Optimal Sizing for Wind/PV/Battery System Using Fuzzy c-Means Clustering with Self-Adapted Cluster Number”, International Journal of Rotating Machinery, ISSN: 1023-621X.
[15] Le Tien Phong, Ngo Duc Minh (2014), “Research on designing an energy management systemfor isolated PV source”, Journal of Science and Technology, Vol. 127, No 13, ISSN: 1859-2171.
[16] Yuan-Kang Wu, Chao-Rong Chen, and Hasimah Abdul Rahman (2014), “A Novel Hybrid Model for Short-Term Forcasting in PV Power Generation”, International Journal of Photoenergy, ISSN: 1110-662X Volume 2014.
[17] Imane Drouiche, Aissa Chouder, Samia Harrouni (2013), “A dynamic model of a grid connected PV system based on outdoor measurement using Labview”, 3rd International Conference on Electric Power and Energy Conversion Systems, IEEE Xplore, ISBN: 978-1-4799-0688-8.
[18] Mehryar Parsi (2016), “Daily solar radiation forecasting using historical data and examining three methods”, IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), ISSN: 2278-1684, Volume 13, Issue 5.
[19] S. Prakash, N. P. Gopinath, J. Suganthi (2018), “Wind and Solar Energy Forecasting System Using Artificial Neural Nethworks”, International Pure and Applied Mathematics, ISSN: 1314-3395, Volume 118, No. 5.
[20] Peter D. Lund, Juuso Lindgren, Jani Mikkola, Jyri Salpakari (2015), “Review of energy system flexibility measures to enable high levels of variable renewable electricity”, Renewable and Sustainable Energy Reviews, ISSN: 1364-0321, Vol. 45.
How to Cite
MINH CUONG, Nguyen et al. Optimal Energy Storage Sizing in Photovoltaic and Wind Hybrid Power System Meeting Demand-Side Management Program in Viet Nam. International Journal of Research and Engineering, [S.l.], v. 5, n. 9, p. 508-515, nov. 2018. ISSN 2348-7860. Available at: <https://digital.ijre.org/index.php/int_j_res_eng/article/view/358>. Date accessed: 11 dec. 2018. doi: https://doi.org/10.21276/ijre.2018.5.9.3.