DOI: https://doi.org/10.14710/ijred.2021.31316

Simulation-Based Optimization of Hybrid Renewable Energy System for Off-grid Rural Electrification

1National Centre for Hydropower Research and Development, University of Ilorin, Ilorin, Nigeria

2Advanced Power and Green Energy Research Group, Department of Electrical and Electronics Engineering, University of Ilorin, Ilorin, Nigeria

3Department of Telecommunication Engineering, Federal University of Technology Minna, Nigeria

4 Department of Water Resources and Environmental Engineering, University of Ilorin, Ilorin, Nigeria

View all affiliations
Received: 1 Jul 2020; Revised: 17 Jan 2021; Accepted: 18 Mar 2021; Available online: 20 Apr 2021; Published: 1 Nov 2021.
Editor(s): H. Hadiyanto
Open Access Copyright (c) 2021 The Authors. Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
Abstract

There is a need to develop an optimization tool that can be applied in the feasibility study of a hybrid renewable energy system to find the optimal capacity of different renewable energy resources and support the decision makers in their performance investigation. A multi-objective function which minimizes the Levelized Cost of Energy (LCOE) and Loss of Load Probability Index (LLPI) but maximizes the novel Energy Match Ratio (EMR) was formulated. Simulation-based optimization method combined with ε-constraint technique was developed to solve the multi-objective optimization problem. In the study, ten-year hourly electrical load demand, using the end-use model, is estimated for the communities. The performance of the developed algorithm was evaluated and validated using Hybrid Optimization Model for Electric Renewables (HOMER®) optimization software. The developed algorithm minimized the LCOE by 6.27% and LLPI by 167% when compared with the values of LCOE ($0.444/kWh) and LLPI (0.000880) obtained from the HOMER® optimization tool. Also, the LCOE with the proposed approach was calculated at $0.417/kWh, which is lower than the $0.444/kWh obtained from HOMER®. From environmental perspective, it is found that while 141,370.66 kg of CO2 is saved in the base year, 183,206.51 kg of CO2 is saved in the ninth year.The study concluded that the approach is computationally efficient and performed better than HOMER® for this particular problem.The proposed approach could be adopted for carrying out feasibility studies and design of HRES for Off-Grid electrification, especially in the rural areas where access to the grid electricity is limited

Fulltext View|Download
Keywords: Renewable energy technologies; optimization; energy match ratio; loss-of-load probability; rural electrification; off-grid;
Funding: National Centre for Hydropower Research and Development, University of Ilorin

Article Metrics:

Article Info
Section: Original Research Article
Language : EN
Recent articles
An Enhanced Solar Hybrid Brayton and Rankine Cycles with Integrated Magnetohydrodynamic Conversion System for Electrical Power Generation Isolation and Identification of Cellulase Producing and Sugar Fermenting Bacteria for Second-Generation Bioethanol Production Energy Loss Reduction of Distribution Systems Equipped with Multiple Distributed Generations Considering Uncertainty using Manta-Ray Foraging Optimization Influence of Various Basin Types on Performance of Passive Solar Still: A Review Experimental Study on Solar Heat Battery using Phase Change Materials for Parabolic Dish Collectors Studying the Effect of Light Incidence Angle on Photoelectric Parameters of Solar Cells by Simulation More recent articles
Most cited articles
Biohydrogen Production by Reusing Immobilized Mixed Culture in Batch System Corrosion of the metal parts of diesel engines in biodiesel-based fuels Biogas Production from Cow Manure Enhancement of Energy Efficiency and Food Product Quality Using Adsorption Dryer with Zeolite Determining the Optimum Tilt Angles to Maximize the Incident Solar Radiation - Case of Study Pristina More cited articles
  1. Abdelkader, A., Rabeh, A., Ali, D.M., & Mohammed, J. (2018). Multi-objective genetic algorithm based sizing optimization of a stand-alone wind/PV power supply system with enhanced battery/supercapacitor hybrid energy. Energy, 163 (15) 351-363; https://doi.org/10.1016/j.energy.2018.08.135
  2. Abdul Razak, N. A. b., Murtadha, M., b. O., & Muslim, I. (2010). Optimal sizing and operation strategy of hybrid renewable energy system using homer. In Power Engineering and Optimization Conference (PEOCO), 23-24 June, Shah Alam, Malaysia; DOI: 10.1109/PEOCO.2010.5559240
  3. Ahmadi, M. H., Ghazvini, M., Sadeghzadeh, M., Nazari, M. A., Kumar, R., Naeimi, A. (2018). Solar power technology for electricity generation: A critical review. Electrochemical sciences advances, wiley online 6(5), 340-361
  4. Akuru, U. B., Onukwube, I. E., Okoro, O. I., & Obe, E. S. (2017). Towards 100% renewable energy in Nigeria. Renewable and Sustainable Energy Reviews 71, 943–953; https://doi.org/10.1016/j.rser.2016.12.123
  5. Amer, M., Namaane, A., & M'sirdi, N. K. (2013). Optimization of hybrid renewable energy systems (HRES) using PSO for cost reduction. Energy Procedia, 318-327; https://doi.org/10.1016/j.egypro.2013.11.032
  6. Ardakani, F. J., Riahy, G., & Abedi, M. (2010). Design of an optimum hybrid renewable energy system considering reliability indices. In 18th IEEE Iranian Conference on Electrical Engineering (ICEE) May, 842–847; DOI: 10.1109/IRANIANCEE.2010.5506958
  7. Ariyo, B.O., Akorede, M.F., Omeiza, I.O., Amuda, S.A., & Oladeji, S.A. (2018). Optimization analysis of a stand-alone hybrid energy system for the senate building, university of Ilorin, Nigeria. Journal of Building Engineering 1(19), 285-294; https://doi.org/10.1016/j.jobe.2018.05.015
  8. Askarzadeh, A., & dos Santos, C. L. (2015). A novel framework for optimization of a grid independent hybrid renewable energy system: A case study of Iran. Solar Energy, 112, 383–396; https://doi.org/10.1016/j.solener.2014.12.013
  9. Aziz, A. S., Tajuddin, M. F. N., Adzman, M. R., Azmi, A., & Ramli, M. A.M. (2019). Optimization and sensitivity analysis of standalone hybrid energy systems for rural electrification: A case study of Iraq. Renewable Energy 138, 775-792; https://doi.org/10.1016/j.renene.2019.02.004
  10. Azoumah, Y., Yamegueu, D., Ginies, P., Coulibaly, Y., & Girard P. (2011). Sustainable electricity generation for rural and peri-urban populations of sub-Saharan Africa: The "flexy-energy" concept. Energy Policy 39, 131–141; https://doi.org/10.1016/j.enpol.2010.09.021
  11. Balat, M., & Balat, H. (2010). Progress in biodiesel processing. Applied Energy 87, 1815–1835; DOI: 10.1016/j.apenergy.2010.01.012
  12. Bashir, M., & Sadeh, J. (2011). Optimal sizing of hybrid wind/photovoltaic/battery considering the uncertainty of wind and photovoltaic power using Monte Carlo. In 11th IEEE International Conference on Environment and Electrical Engineering (EEEIC) May, 1081–1086; DOI: 10.1109/EEEIC.2012.6221541
  13. Bashir, M., & Sadeh, J. (2012). Size optimization of new hybrid stand-alone renewable energy system considering a reliability index. In 11th IEEE International Conference on Environment and Electrical Engineering (EEEIC) May, 989–994; DOI: 10.1109/EEEIC.2012.6221521
  14. Boonbumroong, U., Pratinthong, N., Thepa, S., Jivacate, C., & Pridasawas, W. (2011). Particle swarm optimization for AC-coupling stand-alone hybrid power systems. Solar Energy, 85(3), 560–569; https://doi.org/10.1016/j.solener.2010.12.027
  15. Borhanazad, H., Saad, M., & Velappa, G.G. (2014). Optimization of Micro-Grid System using MOPSO. Renewable Energy 71, 295-306; https://doi.org/10.1016/j.renene.2014.05.006
  16. Bourennani, F., Rahnamayan, S., & Naterer, G. F. (2015). Optimal design methods for hybrid renewable energy systems. International Journal of Green Energy, 12(2), 148-159; https://doi.org/10.1080/15435075.2014.888999
  17. Cho, J., & Kleit, A.N. (2015). Energy storage systems in energy and ancillary markets: a backwards induction approach. Applied Energy, 147, 176–183; http://dx.doi.org/10.1016/j.apenergy.2015.01.114
  18. Coello, C.C., Lamont, G.B., & Van-Veldhuizen, D.A. (2007). Evolutionary algorithms for solving multi-objective problems. 2nd ed. New York: Springer; https://www.springer.com/gp/book/9780387332543
  19. Dalton, G.J., Lockington, D.A. & Baldock, T.E. (2008). Feasibility analysis of stand-alone renewable energy supply options for a large hotel. Renewable Energy, 33(7), 1475-1490; https://doi.org/10.1016/j.renene.2007.09.014
  20. Das, M., Singh, M. A. K., & Biswas, A. (2019). Techno-economic optimization of an off-grid hybrid renewable energy system using metaheuristic optimization approaches – Case of a radio transmitter station in India. Energy Conversion and Management 185, 339–352; https://doi.org/10.1016/j.enconman.2019.01.107
  21. Das, R., Wang, Y., Putrus, G., Kotter, R., Marzband, M., Herteleer, B., Warmerdam, J. (2020). Multi-objective techno-economic-environmental optimization of electric vehicle for energy services. Applied Energy 257, 113965. https://doi.org/10.1016/j.apenergy.2019.113965
  22. Demiroren, A., & Yilmaz, U. (2010). Analysis of change in electric energy cost with using renewable energy sources in Gokceada, Turkey: As island example. Renewable and Sustainable Energy Reviews, 14(1), 323-33; https://doi.org/10.1016/j.rser.2009.06.030
  23. Eberhart, R., & Kennedy, J. (1995). A new optimizer using particle swarm theory. MHS’95. In proceedings of the Sixth International Symposium on Micro Machine and Human Science, 39–43. Available on line at: http://dx.doi.org/10.1109/MHS.1995.494215
  24. Fodhil, F., Hamidat, A., & Nadjemi, O. (2019). Potential, optimization and sensitivity analysis of photovoltaic-diesel-battery hybrid energy system for rural electrification in Algeria. Energy 169, 613-624; https://doi.org/10.1016/j.energy.2018.12.049
  25. Forough, A. B., & Roshandel, R. (2017). Multi objective receding horizon optimization for optimal scheduling of hybrid renewable energy system. Energy and Buildings 150, 583–597; https://doi.org/10.1016/j.enbuild.2017.06.031
  26. Gao, Y., Du, W., & Yan, G. (2015). Selectively-informed particle swarm optimization. Scientific reports 5:
  27. Gholinejad, R., Loni, A., Adabi J., Marzband, M. (2020). A hierarchical energy management system for multiple home energy hubs in neighborhood grids Hamid. Journal of Building Engineering 28, 101028. DOI: 10.1016/j.jobe.2019.101028
  28. Hadidian-Moghaddam, M. J., Arabi-Nowdeh, S., & Bigdeli, M. (2016). Optimal sizing of a stand-alone hybrid photovoltaic/wind system using new grey wolf optimizer considering reliability. Journal of Renewable and Sustainable Energy 8, 035903. Available on line at: https://doi.org/10.1063/1.4950945
  29. Hakimi, S. M., & Moghaddas-Tafreshi, S. M. (2009). Optimal sizing of a stand-alone hybrid power system via particle swarm optimization for Kahnouj area in south-east of Iran. Renewable energy 34(7), 1855–1862; https://doi.org/10.1016/j.renene.2008.11.022
  30. Himri, Y., Stambouli, A.B., Draoui, B. & Himri, S. (2008). Techno-economical study of hybrid power system for a remote village in Algeria, Energy, 33(7), 1128-36; https://doi.org/10.1016/j.energy.2008.01.016
  31. Huang, Z., Xie, Z., Zhang, C., Chan, S. H., Milewski, J., Xiea, Y. Yang, Y., & Hu, X. (2019). Modeling and multi-objective optimization of a stand-alone PV-hydrogen-retired EV battery hybrid energy system. Energy Conversion and Management, 181, 80–92; https://doi.org/10.1016/j.enconman.2018.11.079
  32. Jadidbonab, M., Mohammadi-Ivatloo, B., Marzband, M., Siano, P. (2020). Short-term Self-Scheduling of Virtual Energy Hub Plant within Thermal Energy Market. IEEE Transactions on Industrial Electronics, 1-13. DOI: 10.1109/TIE.2020.2978707
  33. Kaabeche, A. & Bakelli, Y. (2019). Renewable hybrid system size optimization considering various electrochemical energy storage technologies. Energy Conversion and Management, 193, 2019, 162-175; https://doi.org/10.1016/j.enconman.2019.04.064
  34. Kamal, B. (2012). Carbon Trading -It Pays to have Green Grid. Paper presented at the International Training Programme on “Rural Electrification with Small Hydropower” for participants from African countries Under India ‐ Africa Forum Summit ‐ II, at Alternate Hydro Energy Centre Indian Institute of Technology, Roorkee, India
  35. Kamel, S., & Dahl, C. (2005). The economics of hybrid power systems for sustainable desert agriculture in Egypt. Energy, 30 (8), 1271–81; https://doi.org/10.1016/j.energy.2004.02.004
  36. Kamjoo, A., Maheri, A., Dizqah, A., & Putrus, G. (2016). Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming. International Journal of Electrical Power Energy Systems, 74, 187-194; DOI: 10.1016/j.ijepes.2015.07.007
  37. Katsigiannis, Y.A., Georgilakis, P.S., & Karapidakis, E.S. (2010). Multi objective genetic algorithm solution to the optimum economic and environmental performance problem of small autonomous hybrid power systems with renewable. IET Renewable Power Generation 4(5), 404–419; DOI: 10.1049/iet-rpg.2009.0076
  38. Kaveh, K. D., Amir-Reza, A., & Madjid, T. (2013). A new multi-objective particle swarm optimization method for solving reliability redundancy allocation problems. Reliability Engineering System Safety, 111, 58-75; https://doi.org/10.1016/j.ress.2012.10.009
  39. Kaviani, A. K., Riahy, G. H., & Kouhsari, S. M. (2009). Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages. Renewable Energy, 34(11), 2380– 2390; https://doi.org/10.1016/j.renene.2009.03.020
  40. Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization-Neural Networks. Proceedings of IEEE International Conference, 4, pp. 1942–1948. Available on line at: http://dx.doi.org/10.1109/ ICNN.1995.488968
  41. Khan, M. J., & Igba, M. T. (2005). Pre-feasibility study of stand-alone hybrid energy systems for applications in Newfoundland. Renewable Energy 30, 835–854; https://doi.org/10.1016/j.renene.2004.09.001
  42. Kusakana, K., Munda, J. L., & Jimoh, A. A. (2009). Feasibility study of a hybrid PV-micro hydro system for rural electrification. IEEE AFRICON 2009, 23 - 25 September, Nairobi, Kenya; DOI: 10.1109/AFRCON.2009.5308185
  43. Lan, H., Wen, S., Hong, Y., Yu, D.C. & Zhang, L. (2015). Optimal sizing of hybrid PV/diesel/battery in ship power system. Applied Energy 158, 26–34; https://doi.org/10.1016/j.apenergy.2015.08.031
  44. Lee, T. Y., & Chen, C. L. (2009). Wind-photovoltaic capacity coordination for a time-of-use rate industrial user. IET Renewable Power Generation, 3(2),152–167; DOI: 10.1049/iet-rpg:20070068
  45. Limmeechokchai, B., & Chawana, S. (2007). Sustainable energy development strategies in the rural Thailand: The case of the improved cooking stoves and the small biogas digester. Renewable and Sustainable Energy Reviews, 11(5), 818-837; https://doi.org/10.1016/j.rser.2005.06.002
  46. Mahmoudi, S. M., Maleki, A., Ochbelagh, D. R. (2021). Optimization of a hybrid energy system with/without considering back-up system by a new technique based on fuzzy logic controller. Energy Conversion and Management 229, 113723
  47. Maleki, A., & Askarzadeh, A. (2014). Optimal sizing of a PV/wind/diesel system with battery storage for electrification to an off-grid remote region: a case study of Rafsanjan, Iran. Sustainable Energy Technologies and Assessments, 7, 147–53; https://doi.org/10.1016/j.seta.2014.04.005
  48. Marzband, M., Azarinejadian, F., Savaghebi, M., Pouresmaeil, E., Guerrero, J. M., Lightbody G. (2018). Smart transactive energy framework in grid-connected multiple home microgrids under independent and coalition operations. Renewable Energy 126, 95-106. https://doi.org/10.1016/j.renene.2018.03.021
  49. Masoud, S., & Tarek, Y. E. (2014). A dynamic MOPSO algorithm for multiobjective optimal design of hybrid renewable energy systems. International Journal of Energy Research, 38(15), 1949–1963; https://doi.org/10.1002/er.3202
  50. Mirzaei, M. A., Sadeghi-Yazdankhah, A., Mohammadi-Ivatloo, B., Marzband, M., Shafie-khah, M., Catalão, J. P. S. (2019). Integration of emerging resources in IGDT-based robust scheduling of combined power and natural gas systems considering flexible ramping products, Energy 189, 116195. https://doi.org/10.1016/j.energy.2019.116195
  51. Mohamed, M. A, Eltamaly, A. M., & Alolah, A. I. (2016). PSO-based smart grid application for sizing and optimization of hybrid renewable energy systems. PLoS ONE 11(8):e0159702; https://doi.org/10.1371/journal.pone.0159702
  52. Nandi, S., & Ghosh, H.R. (2010). Prospect of wind-PV-battery hybrid system as an alternative to grid extension in Bangladesh. Energy, 35(7), 3040-3047; https://doi.org/10.1016/j.energy.2010.03.044
  53. Nazari-Heris, M., Mirzaei, M. A., Mohammadi-Ivatloo, B., Marzband, M., Asadi, S. (2020). Economic-environmental effect of power to gas technology in coupled electricity and gas systems with price-responsive shiftable loads. Journal of Cleaner Production 244, 118769, 2020. https://doi.org/10.1016/j.jclepro.2019.118769
  54. Nfah, E. M., Ngundam, J. M., Vandenbergh, M., & Schmid, J. (2008). Simulation of off-grid generation options for remote villages in Cameroon. Renewable Energy, 33 (5), 1064-72; https://doi.org/10.1016/j.renene.2007.05.045
  55. Perera, A. T. D., Attalage, R. A., Perera, K. K. C. K., & Dassanayake, V.P.C. (2013). A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems. Applied Energy, 107, 412-425; https://doi.org/10.1016/j.apenergy.2013.02.049
  56. Ren, H., Lu, Y., Wu, Q., Yan, X., & Zhou, A. (2018). Multi-objective optimization of a hybrid distributed energy system using NSGA-II algorithm. Frontiers Energy, 12(4), 518-528; https://doi.org/10.1007/s11708-018-0594-7
  57. Roberts, J. J., Marotta Cassula, A., Silveira, J. L., da Costa Bortoni, E., & Mendiburu, A. Z. (2018). Robust multi-objective optimization of a renewable based hybrid power system. Applied Energy, 223, 52-68; https://doi.org/10.1016/j.apenergy.2018.04.032
  58. Sadeghzadeh, M., Ahmadi, M. H., Kahani, M., Sakhaeinia, H., Chaji, H., Chen, L. (2019). Smart modeling by using artificial intelligent techniques on thermal performance of flat‐plate solar collector using nanofluid. Energy Science and Engineering, 7(5), 1649-1658
  59. Sambo, A. S. (2009). The Place of Renewable Energy in the Nigerian Energy Sector. Paper presented at the World Future Council Workshop on Renewable Energy Policies, 10thOctober, Addis Ababa, Ethiopia
  60. Setiawan, A., Zhao, Y., & Nayar, C. M. (2009). Design, economic analysis and environmental considerations of mini-grid hybrid power system with reverse osmosis desalination plant for remote areas. Renewable Energy, 34(2), 374-83; https://doi.org/10.1016/j.renene.2008.05.014
  61. Shaahid, S.M., & Elhadidy, M.A. (2007). Technical and economic assessment of grid-independent hybrid photovoltaic-diesel-battery power systems for commercial loads in desert environments. Renewable and Sustainable Energy Reviews, 11(8), 1794-1810; https://doi.org/10.1016/j.rser.2006.03.001
  62. 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
  63. Singh, R., Bansal, R. C. (2019). Optimization of an Autonomous Hybrid Renewable Energy System Using Reformed Electric System Cascade Analysis. IEE Transactions on Industrial Informatics, 15(1), pp. 399-409. https://doi.org/10.1109/TII.2018.2867626
  64. Starke, A. R., Cardemil, J. M., Escobar, R., & Colle, S. (2018). Multi-objective optimization of hybrid CSP+PV system using genetic algorithm. Energy, 147(C), 490-503; https://doi.org/10.1016/j.renene.2014.01.011
  65. Suhane, P., Rangnekar, S., Mittal, A., & Khare, A. (2016). Sizing and performance analysis of standalone wind-photovoltaic based hybrid energy system using ant colony optimization. The Institution of Engineering and Technology, 10(7), 964-972; DOI: 10.1049/iet-rpg.2015.0394
  66. Tregambi, C., Bareschino, P., Mancusi, E., Pepe, F., Montagnaro, F., Solimene, R., Salatino, P. (2021). Modelling of a concentrated solar power – photovoltaics hybrid plant for carbon dioxide capture and utilization via calcium looping and methanation. Energy Conversion and Management, 230, 113792
  67. Tsai, T-C., Beza, T. M., Molla, E. M., Kuo, C-C. (2020). Analysis and Sizing of Mini-Grid Hybrid Renewable Energy System for Islands. IEEE, 8, 70013 – 70029. https://doi.org/10.1109/ACCESS.2020.2983172
  68. Turkey, B.E. & Telli, A.Y. (2011). Economics analysis of standalone and grid-connected hybrid energy systems. Renewable Energy, 36(7), 1931-1943; https://doi.org/10.1016/j.renene.2010.12.007
  69. Wang, L., & Singh, C. (2009). Multicriteria design of hybrid power generation systems based on a modified particle swarm optimization algorithm. IEEE Transactions on Energy Conversion, 24(1), 163–172; doi: 10.1109/TEC.2008.2005280
  70. Weis, T. M., & Ilinca, A. (2008). The utility of energy storage to improve the economics of wind-diesel power plants in Canada. Renewable Energy, 33(7), 1544-1557; https://doi.org/10.1016/j.renene.2007.07.018
  71. Wu, T., Bu, S., Wei, X., Wang, G., Zhou, B. (2021). Multitasking multi-objective operation optimization of integrated energy system considering biogas-solar-wind renewables. Energy Conversion and Management, 229, 2021, 113736. https://doi.org/10.1016/j.enconman.2020.113736
  72. Zahraee, S. M., Assadi, M. K., & Saidur, R. (2016). Application of artificial intelligence methods for hybrid energy system optimization. Renewable and Sustainable Energy Reviews, 66, 617-630; https://doi.org/10.1016/j.rser.2016.08.028
  73. Zakeri, B., & Syri, S. (2015). Electrical energy storage systems: a comparative life cycle cost analysis. Renewable and Sustain Energy Reviews 42, pp. 569–596. Available on line at: http://dx.doi.org/10.1016/j.rser.2014.10.011
  74. Zhao, P., Wang, J., & Dai., Y. (2015). Capacity allocation of a hybrid energy storage system for power system peak shaving at high wind power penetration level. Renewable Energy 75, pp. 541–549. Available on line at: http://dx.doi.org/10.1016/j.renene.2014.10.040
  75. Zhu, J. (2015) Optimization of power system operation. Vol. 47. John Wiley & Sons, 2015. https://www.wiley.com/en-us/Optimization+of+Power+System+Operation%2C+2nd+Edition-p-9781118854150

Last update:

  1. HOMER optimization of standalone PV/Wind/Battery powered hydrogen refueling stations located at twenty selected French cities

    Fakher Oueslati. International Journal of Renewable Energy Development, 12 (6), 2023. doi: 10.14710/ijred.2023.58218

  2. Comprehensive Renewable Energy

    Kosmas Kavadias, Panagiotis Triantafyllou. 2022. doi: 10.1016/B978-0-12-819727-1.00162-X

  3. Nanofluids-based solar collectors as sustainable energy technology towards net-zero goal: Recent advances, environmental impact, challenges, and perspectives

    Zafar Said, Misbah Iqbal, Aamir Mehmood, Thanh Tuan Le, Hafiz Muhammad Ali, Dao Nam Cao, Phuoc Quy Phong Nguyen, Nguyen Dang Khoa Pham. Chemical Engineering and Processing - Process Intensification, 191 , 2023. doi: 10.1016/j.cep.2023.109477

  4. An Improvement in Power Quality and By-Product of the Run-Off River Micro Hydro Power Plant

    Ignatius Riyadi Mardiyanto, Jangkung Raharjo, Sri Utami, Wahyu Budi Mursanto, Agoeng Hardjatmo Rahardjo. Energy Engineering, 120 (6), 2023. doi: 10.32604/ee.2023.027756

  5. Effects of Injection Strategies on Mixture Formation and Combustion in a Spark-Ignition Engine Fueled with Syngas-Biogas-Hydrogen

    Thanh Xuan Nguyen-Thi, Thi Minh Tu Bui. International Journal of Renewable Energy Development, 12 (1), 2023. doi: 10.14710/ijred.2023.49368

  6. Energy-Related Material Flow Simulation in Production and Logistics

    Cedric Schultz, Martin Rösch, Lukas Bank. 2024. doi: 10.1007/978-3-031-34218-9_7

  7. Nanotechnology-based biodiesel: A comprehensive review on production, and utilization in diesel engine as a substitute of diesel fuel

    Thanh Tuan Le, Minh Ho Tran, Quang Chien Nguyen, Huu Cuong Le, Van Quy Nguyen, Dao Nam Cao, Prabhu Paramasivam. International Journal of Renewable Energy Development, 13 (3), 2024. doi: 10.61435/ijred.2024.60126

  8. Analysis of grid/solar photovoltaic power generation for improved village energy supply: A case of Ikose in Oyo State Nigeria

    Abraham O. Amole, Stephen Oladipo, Olakunle E. Olabode, Kehinde A. Makinde, Peter Gbadega. Renewable Energy Focus, 44 , 2023. doi: 10.1016/j.ref.2023.01.002

  9. Technical, Economic, and Intelligent Optimization for the Optimal Sizing of a Hybrid Renewable Energy System with a Multi Storage System on Remote Island in Tunisia

    Mohamed Hajjaji, Dhafer Mezghani, Christian Cristofari, Abdelkader Mami. Electronics, 11 (20), 2022. doi: 10.3390/electronics11203261

  10. Techno-economic and environmental feasibility study with demand-side management of photovoltaic/wind/hydroelectricity/battery/diesel: A case study in Sub-Saharan Africa

    Djeudjo Temene Hermann, Njomo Donatien, Talla Konchou Franck Armel, Tchinda René. Energy Conversion and Management, 258 , 2022. doi: 10.1016/j.enconman.2022.115494

  11. Design of Hybrid (PV-Diesel) System for Tourist Island in Karimunjawa Indonesia

    Nurul Hiron, Nundang Busaeri, Sutisna Sutisna, Nurmela Nurmela, Aceng Sambas. Energies, 14 (24), 2021. doi: 10.3390/en14248311

  12. An Economic and Environmental Study of a Hybrid System (Wind and Diesel) in the Algerian Desert Region using HOMER Software

    Issam Griche, Mohamed Rezki, Kamel Saoudi, Ghania Boudechiche, Fares Zitouni. Engineering, Technology & Applied Science Research, 13 (2), 2023. doi: 10.48084/etasr.5651

Last update: 2024-04-24 03:37:44

No citation recorded.