Optimal Battery Sizing of a Grid-Connected Residential Photovoltaic System for Cost Minimization using PSO Algorithm
Abstract
This paper proposes a new optimization technique that uses Particle Swarm Optimization (PSO) in residential grid-connected photovoltaic systems. The optimization technique targets the sizing of the battery storage system. With the liberation of power systems, the residential grid-connected photovoltaic system can supply power to the grid during peak hours or charge the battery during non-peak hours for later domestic use or for selling back to the grid during peak hours. However, this can only be achieved when the battery energy system in the residential photovoltaic system is optimized. The developed PSO algorithm aims at optimizing the battery capacity that will lower the operation cost of the system. The computational efficiency of the developed algorithm is demonstrated using real PV data from Strathmore University. A comparative study of a PV system with and without battery energy storage is carried out and the simulation results demonstrate that PV system with battery is more efficient when optimized with PSO.
Keywords:
grid-connected PV, electricity surplus, sizing, battery energy storage, electricity prices, net metering, PSODownloads
References
Y. Ru, J. Kleissl, S. Martinez, “Storage size determination for grid-connected photovoltaic systems”, IEEE Transactions on Sustainable Energy, Vol. 4, No. 1, pp. 68–81, 2013 DOI: https://doi.org/10.1109/TSTE.2012.2199339
D. Abdoulaye, Z. Koalaga, F. Zougmore, “Grid-connected photovoltaic (PV) systems with batteries storage as solution to electrical grid outages in Burkina Faso”, 1st International Symposium on Electrical Arc and Thermal Plasmas in Africa, Ouagadougou, Burkina Faso, October 17-21, 2012 DOI: https://doi.org/10.1088/1757-899X/29/1/012015
Y. Riffonneau, S. Bacha, F. Barruel, S. Ploix, “Optimal power flow management for grid connected PV systems with batteries”, IEEE Transactions on Sustainable Energy, Vol. 2, No. 3, pp. 309–320, 2011
Y. Choi, H. Kim, “Optimal scheduling of energy storage system for self-sustainable base station operation considering battery wear-out cost”, Eighth International Conference on Ubiquitous and Future Networks, Vienna, Austria, July 5-8, 2016 DOI: https://doi.org/10.3390/en9060462
S. Grillo, A. Pievatolo, E. Tironi, “Optimal storage scheduling using Markov decision processes”, IEEE Transactions on Sustainable Energy, Vol. 7, No. 2, pp. 755–764, 2016 DOI: https://doi.org/10.1109/TSTE.2015.2497718
M. Gitizadeh, H. Fakharzadegan, “Battery capacity determination with respect to optimized energy dispatch schedule in grid-connected photovoltaic (PV) systems”, Energy, Vol. 65, pp. 665–674, 2014 DOI: https://doi.org/10.1016/j.energy.2013.12.018
F. Mavromatakis, G. Viskadouros, G. Xanthos, “Photovoltaic systems and net metering in Greece”, Engineering, Technology & Applied Science Research, Vol. 8, No. 4, pp. 3168–3171, 2018 DOI: https://doi.org/10.48084/etasr.2197
J. Li, “Optimal sizing of grid-connected photovoltaic battery systems for residential houses in Australia”, Renewable Energy, Vol. 136, pp. 1245-1254, 2019 DOI: https://doi.org/10.1016/j.renene.2018.09.099
M. A. Mohamed, A. M. Eltamaly, A. I. Alolah, “PSO-based smart grid application for sizing and optimization of hybrid renewable energy systems”, PLoS One, Vol. 11, No. 8, pp. 1–22, 2016 DOI: https://doi.org/10.1371/journal.pone.0159702
L. A. Wong, H. Shareef, A. Mohamed, A. A. Ibrahim, “Optimal placement and sizing of energy storage system in distribution network with photovoltaic based distributed generation using improved firefly algorithms”, World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, Vol. 11, No. 7, pp. 864–872, 2017
M. O. Badawy, F. Cingoz, Y. Sozer, “Battery storage sizing for a grid tied PV system based on operating cost minimization”, IEEE Energy Conversion Congress and Exposition, Milwaukee, USA, September 18-22, 2016 DOI: https://doi.org/10.1109/ECCE.2016.7854896
V. S. Borra, K. Debnath, “Comparison between the dynamic programming and Particle Swarm Optimization for solving unit commitment problems”, IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, Amman, Jordan, April 9-11, 2019 DOI: https://doi.org/10.1109/JEEIT.2019.8717481
P. Ahmadi, M. H. Nazari, S. H. Hosseinian, “Optimal resources planning of residential complex energy system in a day-ahead market based on Invasive Weed Optimization algorithm”, Engineering, Technology & Applied Science Research, Vol. 7, No. 5, pp. 1934–1939, 2017 DOI: https://doi.org/10.48084/etasr.1324
K. Thirugnanam, H. Saini, P. Kumar, “Mathematical modeling of Li-Ion battery for charge/discharge rate and capacity fading characteristics using Genetic Algorithm approach”, IEEE Transportation Electrification Conference and Expo, Dearborn, USA, June 18-20, 2012 DOI: https://doi.org/10.1109/ITEC.2012.6243431
D. T. Ton, C. J. Hanley, G. H. Peek, J. D. Boyes, Solar energy grid Integration Systems: Energy Storage (SEGIS-ES), Sandia National Laboratories, 2008 DOI: https://doi.org/10.2172/1217673
E. McKenna, M. McManus, S. Cooper, M. Thomson, “Economic and environmental impact of lead-acid batteries in grid-connected domestic PV systems”, Applied Energy, Vol. 104, pp. 239–249, 2013 DOI: https://doi.org/10.1016/j.apenergy.2012.11.016
P. Mohanty, K. R. Sharma, M. Gujar, M. Kolhe, A. N. Azmi, “PV system design for off-grid applications”, in: Solar photovoltaic system applications: A guidebook for off-frid electrification, Springer, 2015 DOI: https://doi.org/10.1007/978-3-319-14663-8
Y. Riffonneau, S. Bacha, F. Barruel, S. Ploix, “Optimal power flow management for grid connected PV systems with batteries”, IEEE Transactions on Sustainable Energy, Vol. 2, No. 3, pp. 309-320, 2011 DOI: https://doi.org/10.1109/TSTE.2011.2114901
L. Ravi, C. V. Kumar, M. R. Babu, “Stochastic optimal management of renewable microgrid using simplified Particle Swarm Optimization algorithm”, 4th International Conference on Electrical Energy Systems, Chennai, India, February 7-9, 2018 DOI: https://doi.org/10.1109/ICEES.2018.8443258
K. Yenchamchalit, Y. Kongjeen, K. Bhumkittipich, N. Mithulananthan, “Optimal sizing and location of the charging station for plug-in electric vehicles using the Particle Swarm Optimization technique”, International Electrical Engineering Congress, Krabi, Thailand, March 7-9, 2018 DOI: https://doi.org/10.1109/IEECON.2018.8712336
D. Truong, “Hybrid PSO-optimized ANFIS-based model to improve dynamic voltage stability”, Engineering, Technology & Applied Science Research, Vol. 9, No. 4, pp. 4384–4388, 2019 DOI: https://doi.org/10.48084/etasr.2833
Downloads
How to Cite
Metrics
Abstract Views: 1178PDF Downloads: 579 Optimal battery sizing of a grid-connected Residential PV system for cost minimization using PSO Downloads: 0
Metrics Information
License
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
