Analysis and mitigation of greenhouse gases by replacing traditional energy with a hybrid energy system using battery optimization
DOI:
https://doi.org/10.17159/2413-3051/2025/v36i1a20374Abstract
Greenhouse gases (GHGs) are the main cause of global warming. Reducing emissions would contribute to environmental sustainability and could also have economic advantages. GHGs can be reduced by using the hybrid energy system (HES). In developing countries, analysing energy transitions and unmet energy needs should focus on identifying strategies for transitioning to more sustainable energy systems while ensuring access for all. This study looks at the mitigation of GHG emissions by using clean HES energy with battery optimisation. The paper presents an improved Lyapunov optimisation (LO) algorithm to optimally estimate the number of photovoltaic panels and battery banks for enhanced energy management. To increase system efficiency, the losses of power and over-production and under-utilised energy have been considered. The stability analysis is evaluated using the LO algorithm, specifically focusing on the changes predicted by the energy index of the self-reliance report, optimising the system’s performance under varying environmental conditions.
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Abd El Sattar Badr M. (2020) Hybrid Wind and Solar Systems Optimization Modeling, Simulation and Optimization of Wind Farms and Hybrid Systems. IntechOpen; http://dx.doi.org/10.5772/intechopen.89136. https://www.intechopen.com/chapters/69047 DOI: https://doi.org/10.5772/intechopen.89136
Ahmad, R. J. (2021). Economic dispatch in grid-connected and heat network-connected CHP microgrids with storage systems and responsive loads considering reliability and uncertainties. Sustain. Cities Soc. 73, 103101. doi:10.1016/j.scs.2021.103101 DOI: https://doi.org/10.1016/j.scs.2021.103101
Alghamdi, A.S. (2023) Optimal Power Flow of Hybrid Wind/Solar/Thermal Energy Integrated Power Systems Consid-ering Costs and Emissions via a Novel and Efficient Search Optimization Algorithm. Appl. Sci. 13, 4760. https://doi.org/10.3390/app13084760 DOI: https://doi.org/10.3390/app13084760
Al-Rawashdeh, Hani, Al-Khashman, Omar Ali, Arrfou, Laith M., Gomaa, Mohamed R., Rezk, Hegazy, Shalby, Moham-mad, Al Bdour, Jehad T., Louzazni, Mohamed. (2023) Different Scenarios for Reducing Carbon Emissions, Optimal Sizing, and Design of a Stand-Alone Hybrid Renewable Energy System for Irrigation Purposes. International Jour-nal of Energy Research. 6338448 27 https://doi.org/10.1155/2023/6338448 DOI: https://doi.org/10.1155/2023/6338448
Ates,E.Karaarslan, N. (2023) Investigation of Hybrid Renewable Energy Green House for Reducing Residential Carbon Emissions. International Journal of Thermo fluids. 21, 100558. https://doi.org/10.1016/j.ijft.2023.100558. DOI: https://doi.org/10.1016/j.ijft.2023.100558
Balasubramanian K, Murugesan N, Samuel AMR, Sampath M. (2025) Lyapunov-based energy optimization for hybrid renewable energy system for coastal area. Proceedings of the Institution of Mechanical Engineers, Part A. 2025;0(0). https://doi.org/10.1177/09576509251333506 DOI: https://doi.org/10.1177/09576509251333506
Elsayed Said Mohamed, AA. Belal, Sameh Kotb Abd-Elmabod, Mohammed A El-Shirbeny, A. Gad, Mohamed B Zahran. (2021) Smart farming for improving agricultural management. The Egyptian Journal of Remote Sensing and Space Science, 24(3) 971-981. ISSN 1110-9823, https://doi.org/10.1016/j.ejrs.2021.08.007. DOI: https://doi.org/10.1016/j.ejrs.2021.08.007
Energy data Info (2023) https://energydata.info/dataset?vocab_country_names=IND.
He, Ya-Ling., Wang, Wenqi., Jiang, Rui, Li, Mingjia, Tao, Wenquan. (2023) Liquid-based high-temperature receiver technologies for next-generation concentrating solar power: A review of challenges and potential solutions. Front. Energy. 17(1), 16-42. https://doi.org/10.1007/s11708-023-0866-8 DOI: https://doi.org/10.1007/s11708-023-0866-8
IPCC (2023) https://www.ipcc.ch/report/ar6/syr
Jyoti B. Fulzele, M.B. Daigavane.(2018) Design and Optimization of Hybrid PV-Wind Renewable Energy System. Mate-rials Today proceedings. (1) 810-818 https://doi.org/10.1016/j.matpr.2017.11.151 DOI: https://doi.org/10.1016/j.matpr.2017.11.151
Krishna Kumar Jaiswal. et al., (2022), Renewable and sustainable clean energy development and impact on social, economic, and environmental health. Energy Nexus, 7 100118. ISSN 2772-4271, https://doi.org/10.1016/j.nexus.2022.100118. DOI: https://doi.org/10.1016/j.nexus.2022.100118
Mikalai Filonchyk, Michael Peterson, Haowen Yan, Andrei Gusev, Lifeng Zhang, Yi He, Shuwen Yang. (2024)Greenhouse gas emissions and reduction strategies for the world's largest greenhouse gas emitters. Science of The Total Environment. 944, 173895, ISSN 0048-9697. https://doi.org/10.1016/j.scitotenv.2024.173895. DOI: https://doi.org/10.1016/j.scitotenv.2024.173895
Mikalai Filonchyk, Michael Peterson, Lifeng Zhang, Volha Hurynovich, Yi He.(2024) Greenhouse gases emissions and global climate change: Examining the influence of CO2, CH4, and N2O. Science of The Total Environment, 935, 173359, ISSN 0048-9697.https://doi.org/10.1016/j.scitotenv.2024.173359. DOI: https://doi.org/10.1016/j.scitotenv.2024.173359
Moreroa, M., and Motshekga, S. (2024). The feasibility of using biogas generated from livestock manure as an alterna-tive energy source: A South African perspective. Journal of Energy in Southern Africa, 35(1), 1-16. https://doi.org/10.17159/2413-3051/2023/v34i1a17021 DOI: https://doi.org/10.17159/2413-3051/2023/v34i1a17021
Patel, K.Das, Narottam and Khan, Mohammed. (2019) Optimization of Hybrid Solar, Wind and Diesel Energy Systems from Economic Point of View. 29th Australasian Universities Power Engineering Conference (AUPEC), Nadi, Fiji. 1-6. https://doi/ 10.1109/AUPEC48547.2019.211861. DOI: https://doi.org/10.1109/AUPEC48547.2019.211861
Rajee, S.A.M, Merline,A and Devi, M.M.Y.(2023)Game theoretic model for power optimization in next-generation het-erogeneous network. Sing. Imag. Vid. Process.17(7) 3721– 3729.https:doi: 10.1007/s11760-023-02599-8. DOI: https://doi.org/10.1007/s11760-023-02599-8
Rui Yang, Kun Li, Ke Du, Boyang Shen. (2021) An ameliorative whale optimization algorithm (AWOA) for HES energy management strategy optimization. Regional Studies in Marine Science. 48 102033, ISSN 2352-4855. https://doi.org/10.1016/j.rsma.2021.102033. DOI: https://doi.org/10.1016/j.rsma.2021.102033
Samuel Amalorpava Mary Rajee and Arulraj Merline. (2020) Machine intelligence technique for blockage effects in next-generation heterogeneous networks. Radioengineering, 29(3),555-563. https://doi.org/10.13164/re.2020.0555 DOI: https://doi.org/10.13164/re.2020.0555
Solar Farms India (2021) https://github.com/microsoft/solar-farmsmapping/blob/main/data/solar_farms_india_2021.geojson.
Thanh-Tuan Nguyen and Tobias Boström. (2021) Multiobjective Optimization of a Hybrid Wind/Solar Battery Energy System in the Arctic. Hindawi, | 8829561. | https://doi.org/10.1155/2021/8829561 DOI: https://doi.org/10.1155/2021/8829561
Tripp, C. and Guittet, D. and King, J. and Barker, A (2022) A simplified, efficient approach to hybrid wind and solar plant site optimization. Wind Energ. Sci., 7, 697–713. https://doi.org/10.5194/wes-7-697-2022, DOI: https://doi.org/10.5194/wes-7-697-2022
Vendoti Suresh, Muralidhar M., R. Kiranmayi. (2020) Modelling and optimization of an off-grid hybrid renewable en-ergy system for electrification in a rural areas, Energy Reports. 6 594-604 ISSN 2352-4847. https://doi.org/10.1016/j.egyr.2020.01.013. (https://www.sciencedirect.com/science/article/pii/S2352484718304499) DOI: https://doi.org/10.1016/j.egyr.2020.01.013
Verma, M et al., (2021) Optimization of wind power plant sizing and placement by the application of multi-objective genetic algorithm (GA) in Madhyapradesh India Sustainable computing. Informatics and systems. 32, 100606. https://doi.org/10.1016/j.suscom.2021.100606. DOI: https://doi.org/10.1016/j.suscom.2021.100606
Xu, X., et al., (2020) Optimized sizing of a standalone PV-wind-hydropower station with pumped-storage installation hybrid energy system, Renew. Energy, 147(1), 1418–1431. https://doi.org/10.1016/j.renene.2019.09.099. DOI: https://doi.org/10.1016/j.renene.2019.09.099
Zhou, Y., et al.,(2021) A review on global solar radiation prediction with machine learning models in a comprehensive perspective. Energy Convers. Manag. 235 113960. https://doi.org/10.1016/j.enconman.2021.113960. DOI: https://doi.org/10.1016/j.enconman.2021.113960
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