Optimal sizing for a grid-connected hybrid renewable energy system: A case study of the residential sector in Durban, South Africa
DOI:
https://doi.org/10.17159/2413-3051/2021/v32i4a10356Abstract
Many countries, including South Africa, have introduced policies and incentives to increase their renewable energy capacities in order to address environmental concerns and reduce pollutant emissions into the atmosphere. In addition, consumers in South Africa have faced the ever-increasing price of electricity and unreliability of the grid since 2007 due to the lack of sufficient electricity production. As a result, employing hybrid renewable energy systems (HRESs) have gained popularity. This research focuses on grid-connected HRESs based on solar photovoltaic (PV) panels and wind turbines as a potential way of reducing the dependency of residential sector consumers on the grid. It aims to identify the optimal sizing of renewable energy sources to be cost-effective for consumers over a certain period of time, using Durban as a case study. Two artificial intelligence methods have been used to obtain the optimal sizing for the available PV panels, wind turbines and inverters. The results shown that the combination of PV panels and battery storage can be a profitable option. A system using higher rated power PV panels can start to become profitable in a shorter lifetime, but employing batteries can only be cost-effective if a long enough lifetime is considered.
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References
Ahadi, A., Kang, S.-K. & Lee, J.-H. 2016. A novel approach for optimal combinations of wind, PV, and energy storage system in diesel-free isolated communities. Applied Energy, 170: 101-115. DOI: https://doi.org/10.1016/j.apenergy.2016.02.110
Akram, U., Khalid, M. & Shafiq, S. 2017a. An innovative hybrid wind-solar and battery-supercapacitor microgrid system—development and optimization. IEEE Access, 5: 25897-25912. DOI: https://doi.org/10.1109/ACCESS.2017.2767618
Akram, U., Khalid, M. & Shafiq, S. 2017b. Optimal sizing of a wind/solar/battery hybrid grid-connected microgrid system. IET Renewable Power Generation, 12: 72-80. DOI: https://doi.org/10.1049/iet-rpg.2017.0010
Akram, U., Khalid, M. & Shafiq, S. 2018. An improved optimal sizing methodology for future autonomous residential smart power systems. IEEE Access, 6: 5986-6000. DOI: https://doi.org/10.1109/ACCESS.2018.2792451
Al Busaidi, A. S., Kazem, H. A. & Khan, M. F. 2014. A review of optimum sizing techniques for off-grid hybrid PV-wind renewable energy systems. International Journal of Students Research in Technology & Management, 2: 93-102.
Alsayed, M., Cacciato, M., Scarcella, G. & Scelba, G. 2013. multicriteria optimal sizing of photovoltaic-wind turbine grid connected systems. IEEE Transactions on Energy Conversion, 28: 370-379. DOI: https://doi.org/10.1109/TEC.2013.2245669
Arabali, A., Ghofrani, M., Etezadi-Amoli, M. & Fadali, M. S. 2013. Stochastic performance assessment and sizing for a hybrid power system of solar/wind/energy storage. IEEE Transactions on Sustainable Energy, 5: 363-371. DOI: https://doi.org/10.1109/TSTE.2013.2288083
Askari, I. B. & Ameri, M. 2012. Techno-economic feasibility analysis of stand-alone renewable energy systems (pv/bat, wind/bat and hybrid pv/wind/bat) in Kerman, Iran. Energy Sources, Part B: Economics, Planning, and Policy, 7: 45-60. DOI: https://doi.org/10.1080/15567240903330384
Askarzadeh, A. 2017. Solution for sizing a PV/diesel HPGS for isolated sites. IET Renewable Power Generation, 11: 143-151. DOI: https://doi.org/10.1049/iet-rpg.2016.0319
Atia, R. & Yamada, N. 2016. Sizing and analysis of renewable energy and battery systems in residential microgrids. IEEE Transactions on Smart Grid, 7: 1204-1213. DOI: https://doi.org/10.1109/TSG.2016.2519541
Bahramara, S., Moghaddam, M. P. & Haghifam, M. R. 2016. Optimal planning of hybrid renewable energy systems using HOMER: A review. Renewable and Sustainable Energy Reviews, 62: 609-620. DOI: https://doi.org/10.1016/j.rser.2016.05.039
Barakat, S., Ibrahim, H. & Elbaset, A. A. 2020. Multi-objective optimization of grid-connected PV-wind hybrid system considering reliability, cost, and environmental aspects. Sustainable Cities and Society, 60: 102178. DOI: https://doi.org/10.1016/j.scs.2020.102178
Brooks, M. J., Du Clou, S., Van Niekerk, W. L., Gauché, P., Leonard, C., Mouzouris, M. J., Meyer, R., Van Der Westhuizen, N., Van Dyk, E. E. & Vorster, F. J. 2015. SAURAN: A new resource for solar radiometric data in Southern Africa. Journal of Energy in Southern Africa, 26: 2-10. DOI: https://doi.org/10.17159/2413-3051/2015/v26i1a2208
Chen, S. X., Gooi, H. B. & Wang, M. 2011. Sizing of energy storage for microgrids. IEEE Transactions on Smart Grid, 3: 142-151. DOI: https://doi.org/10.1109/TSG.2011.2160745
Domestic Electrical Load Study [Online]. Available: https://www.datafirst.uct.ac.za/dataportal/index.php/catalog/DELS [Accessed 12-12-2020 2020].
Elliston, B., Macgill, I. & Diesendorf, M. 2013. Least cost 100% renewable electricity scenarios in the Australian Na-tional Electricity Market. Energy Policy, 59: 270-282. DOI: https://doi.org/10.1016/j.enpol.2013.03.038
EThekwini Electricity Tariffs [Online]. Available: http://www.durban.gov.za/City_Services/electricity/Tariffs/Pages/default.aspx [Accessed 12-12-2020 2020].
Fadaee, M. & Radzi, M. A. M. 2012. Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review. Renewable and Sustainable Energy Reviews, 16: 3364-3369. DOI: https://doi.org/10.1016/j.rser.2012.02.071
Gan, L. K., Shek, J. K. H. & Mueller, M. A. 2016. Optimised operation of an off-grid hybrid wind-diesel-battery system using genetic algorithm. Energy Conversion and Management, 126: 446-462. DOI: https://doi.org/10.1016/j.enconman.2016.07.062
García Clúa, J. G., Mantz, R. J. & De Battista, H. 2018. Optimal sizing of a grid-assisted wind-hydrogen system. Energy Conversion and Management, 166: 402-408. DOI: https://doi.org/10.1016/j.enconman.2018.04.047
Hove, T. & Tazvinga, H. 2012. A techno-economic model for optimising component sizing and energy dispatch strate-gy for PV-diesel-battery hybrid power systems. Journal of Energy in Southern Africa, 23: 18-28. DOI: https://doi.org/10.17159/2413-3051/2012/v23i4a3175
Hua, Z., Ma, C., Lian, J., Pang, X. & Yang, W. 2019. Optimal capacity allocation of multiple solar trackers and storage capacity for utility-scale photovoltaic plants considering output characteristics and complementary demand. Ap-plied Energy, 238: 721-733. DOI: https://doi.org/10.1016/j.apenergy.2019.01.099
Jacob, A. S., Banerjee, R. & Ghosh, P. C. 2018. Sizing of hybrid energy storage system for a PV based microgrid through design space approach. Applied Energy, 212: 640-653. DOI: https://doi.org/10.1016/j.apenergy.2017.12.040
Khare, V., Nema, S. & Baredar, P. 2017. Optimisation of the hybrid renewable energy system by HOMER, PSO and CPSO for the study area. International Journal of Sustainable Energy, 36: 326-343. DOI: https://doi.org/10.1080/14786451.2015.1017500
Kimera, R., Okou, R., Sebitosi, A. B. & Awodele, K. O. 2014. Considerations for a sustainable hybrid mini-grid system: A case for Wanale village, Uganda. Journal of Energy in Southern Africa, 25: 33-43. DOI: https://doi.org/10.17159/2413-3051/2014/v25i1a2686
Ma, G., Xu, G., Chen, Y. & Ju, R. 2016. Multi-objective optimal configuration method for a standalone wind–solar–battery hybrid power system. IET Renewable Power Generation, 11: 194-202. DOI: https://doi.org/10.1049/iet-rpg.2016.0646
Mahesh, A. & Sandhu, K. S. 2015. Hybrid wind/photovoltaic energy system developments: Critical review and find-ings. Renewable and Sustainable Energy Reviews, 52: 1135-1147. DOI: https://doi.org/10.1016/j.rser.2015.08.008
Maleki, A., Khajeh, M. G. & Ameri, M. 2016. Optimal sizing of a grid independent hybrid renewable energy system incorporating resource uncertainty, and load uncertainty. International Journal of Electrical Power & Energy Sys-tems, 83: 514-524. DOI: https://doi.org/10.1016/j.ijepes.2016.04.008
Mandal, S., Das, B. K. & Hoque, N. 2018. Optimum sizing of a stand-alone hybrid energy system for rural electrifica-tion in Bangladesh. Journal of Cleaner Production, 200: 12-27. DOI: https://doi.org/10.1016/j.jclepro.2018.07.257
Merei, G., Berger, C. & Sauer, D. U. 2013. Optimization of an off-grid hybrid PV–wind–diesel system with different battery technologies using genetic algorithm. Solar Energy, 97: 460-473. DOI: https://doi.org/10.1016/j.solener.2013.08.016
Nnadi, D. B., Odeh, C. I. & Omeje, C. 2014. Use of hybrid solar-wind energy generation for remote area electrification in South-Eastern Nigeria. Journal of Energy in Southern Africa, 25: 61-69. DOI: https://doi.org/10.17159/2413-3051/2014/v25i2a2670
Ogunjuyigbe, A. S. O., Ayodele, T. R. & Akinola, O. A. 2016. Optimal allocation and sizing of PV/Wind/Split-diesel/Battery hybrid energy system for minimizing life cycle cost, carbon emission and dump energy of remote residential building. Applied Energy, 171: 153-171. DOI: https://doi.org/10.1016/j.apenergy.2016.03.051
Paliwal, P., Patidar, N. P. & Nema, R. K. 2014. Determination of reliability constrained optimal resource mix for an autonomous hybrid power system using Particle Swarm Optimization. Renewable Energy, 63: 194-204. DOI: https://doi.org/10.1016/j.renene.2013.09.003
Panayiotou, G., Kalogirou, S. & Tassou, S. 2012. Design and simulation of a PV and a PV–wind standalone energy system to power a household application. Renewable Energy, 37: 355-363. DOI: https://doi.org/10.1016/j.renene.2011.06.038
Rajanna, S. & Saini, R. P. 2016. Development of optimal integrated renewable energy model with battery storage for a remote Indian area. Energy, 111: 803-817. DOI: https://doi.org/10.1016/j.energy.2016.06.005
Sanajaoba, S. & Fernandez, E. 2016. Maiden application of cuckoo search algorithm for optimal sizing of a remote hybrid renewable energy System. Renewable Energy, 96: 1-10. DOI: https://doi.org/10.1016/j.renene.2016.04.069
Sanchez, V. M., Chavez-Ramirez, A. U., Duron-Torres, S. M., Hernandez, J., Arriaga, L. G. & Ramirez, J. M. 2014. Tech-no-economical optimization based on swarm intelligence algorithm for a stand-alone wind-photovoltaic-hydrogen power system at south-east region of Mexico. International Journal of Hydrogen Energy, 39: 16646-16655. DOI: https://doi.org/10.1016/j.ijhydene.2014.06.034
Senjyu, T., Hayashi, D., Urasaki, N. & Funabashi, T. 2006. Optimum configuration for renewable generating systems in residence using genetic algorithm. IEEE Transactions on Energy Conversion, 21: 459-466. DOI: https://doi.org/10.1109/TEC.2006.874250
Sharafi, M. & Elmekkawy, T. Y. 2014. Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach. Renewable Energy, 68: 67-79. DOI: https://doi.org/10.1016/j.renene.2014.01.011
Siddaiah, R. & Saini, R. P. 2016. A review on planning, configurations, modeling and optimization techniques of hy-brid renewable energy systems for off grid applications. Renewable and Sustainable Energy Reviews, 58: 376-396. DOI: https://doi.org/10.1016/j.rser.2015.12.281
Sinha, S. & Chandel, S. S. 2015. Review of recent trends in optimization techniques for solar photovoltaic–wind based hybrid energy systems. Renewable and Sustainable Energy Reviews, 50: 755-769. DOI: https://doi.org/10.1016/j.rser.2015.05.040
Southern African Universities Radiometric Network [Online]. Available: https://sauran.ac.za/ [Accessed 12-12-2020 2020].
Tito, S. R., Lie, T. T. & Anderson, T. N. 2016. Optimal sizing of a wind-photovoltaic-battery hybrid renewable energy system considering socio-demographic factors. Solar Energy, 136: 525-532. DOI: https://doi.org/10.1016/j.solener.2016.07.036
Whelan, B. & Muchapondwa, E. 2011. Enhancing consumers' voluntary use of small-scale wind turbines to generate their own electricity in South Africa. Journal of Energy in Southern Africa, 22: 13-21. DOI: https://doi.org/10.17159/2413-3051/2011/v22i2a3210
Xu, F., Liu, J., Lin, S., Dai, Q. & Li, C. 2018. A multi-objective optimization model of hybrid energy storage system for non-grid-connected wind power: A case study in China. Energy, 163: 585-603. DOI: https://doi.org/10.1016/j.energy.2018.08.152
Xu, L., Ruan, X., Mao, C., Zhang, B. & Luo, Y. 2013. An improved optimal sizing method for wind-solar-battery hybrid power system. IEEE transactions on Sustainable Energy, 4: 774-785. DOI: https://doi.org/10.1109/TSTE.2012.2228509
Zahraee, S. M., Khalaji Assadi, M. & Saidur, R. 2016. Application of artificial intelligence methods for hybrid energy system optimization. Renewable and Sustainable Energy Reviews, 66: 617-630. DOI: https://doi.org/10.1016/j.rser.2016.08.028
Zhao, B., Zhang, X., Li, P., Wang, K., Xue, M. & Wang, C. 2014. Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island. Applied Energy, 113: 1656-1666. DOI: https://doi.org/10.1016/j.apenergy.2013.09.015
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