10.1007/s40095-022-00503-7

A novel approach of synchronization of the sustainable grid with an intelligent local hybrid renewable energy control

  • Mostafa Esmaeili Shayan1,
  • Gholamhassan Najafi*1,
  • Barat Ghobadian1,
  • Shiva Gorjian1,
  • Mohamed Mazlan2,
  1. Department of Biosystem Engineering, Tarbiat Modares University, Tehran, IR
  2. Advanced Material Research Cluster, Faculty of Bioengineering and Technology, University of Malaysia, Kelantan, MY

Published in Issue 2022-05-31

How to Cite

Shayan, M. E., Najafi, G., Ghobadian, B., Gorjian, S., & Mazlan, M. (2022). A novel approach of synchronization of the sustainable grid with an intelligent local hybrid renewable energy control. International Journal of Energy and Environmental Engineering, 14(1 (March 2023). https://doi.org/10.1007/s40095-022-00503-7
Crossref
Scopus
Google Scholar
Europe PMC

Abstract

Abstract Energy management, emission reductions, and sustainable development are directly linked. The use of renewable energy and intelligent control systems serves two goals: sustainable development and energy supply. In this paper, we propose an improved intelligent hybrid renewable energy management system to utilize local renewable energy. The penetration of renewable energy in this study starts from 20 and 50% and reaches 100%. The innovation of this research is the use of a dynamic decision algorithm in an intelligent system microcontroller that can determine the maximum possibility of hybridization of local solar and wind energy sources and optimize the electricity demand of the residential unit. The results show that the proposed control strategy in the first scenario, with average daily fuel consumption of 1.11 L, the total energy produced by the hybrid renewable energy conversion system is equal to 1697 kWh/year, and the NPV is $ 553.68 and the IRR is 49.9. 21% with a payback period of 15.71 years. In the second scenario, with average daily fuel consumption of 0.694 L, the energy production is equivalent to 1652 kWh/year. The NPV is equal to $ 341.47 and IRR is equal to 19.5% with a ROI of 17.61 years. In the third scenario, the energy production of the system was equal to 1933 kWh/year with NPV equal to − 372.9 dollars and IRR equal to 15.08%. The intelligent power control system received the electricity generated by the renewable energy subsystems and provides the electricity needed by the green cottage based on the proposed decision algorithm.

Keywords

  • Sustainable energy,
  • Energy efficiency,
  • Microgrid,
  • Renewable energy,
  • Control strategy,
  • Green cottage

References

  1. Esmaeili Shayan et al. (2021) Phase change material mixed with chloride salt graphite foam infiltration for latent heat storage applications at higher temperatures and pressures (pp. 1-11) https://doi.org/10.1007/S40095-021-00462-5
  2. Shayan et al. (2022) Flexible photovoltaic system on non-conventional surfaces: a techno-economic analysis https://doi.org/10.3390/SU14063566
  3. Shayan et al. (2022) Sustainable design of a near-zero-emissions building assisted by a smart hybrid renewable microgrid (pp. 471-480) https://doi.org/10.14710/IJRED.2022.43838
  4. Cho and Kim (2019) Multi-site and multi-period optimization model for strategic planning of a renewable hydrogen energy network from biomass waste and energy crops (pp. 527-540) https://doi.org/10.1016/j.energy.2019.07.053
  5. Azadbakht et al. (2013) Investigation of long shaft failure in John Deere 955 grain combine harvester under static load (pp. 70-73) https://doi.org/10.13189/UJAR.2013.010305
  6. Jafari and Malekjamshidi (2020) Optimal energy management of a residential-based hybrid renewable energy system using rule-based real-time control and 2D dynamic programming optimization method (pp. 254-266) https://doi.org/10.1016/j.renene.2019.06.123
  7. Ghasemzadeh, F., Esmaeili Shayan, M.: Nanotechnology in the service of solar energy systems. In: Nanotechnology and the Environment. IntechOpen, London (2020)
  8. Esmaeili Shayan et al. (2021) The biomass supply chain network auto-regressive moving average algorithm (pp. 15-22)
  9. Human et al. (2021) Genetic fuzzy rule extraction for optimised sizing and control of hybrid renewable energy hydrogen systems (pp. 3576-3594) https://doi.org/10.1016/j.ijhydene.2020.10.238
  10. Dumitrescu et al. (2021) Fuzzy logic for intelligent control system using soft computing applications https://doi.org/10.3390/S21082617
  11. Esmaeili Shayan and Hojati (2021) Floating solar power plants: a way to improve environmental and operational flexibility (pp. 337-348) https://doi.org/10.5829/IJEE.2021.12.04.07
  12. Arias and Bae (2021) Solar photovoltaic power prediction using big data tools https://doi.org/10.3390/SU132413685
  13. Long et al. (2019) Unequal age-based household emission and its monthly variation embodied in energy consumption—a cases study of Tokyo, Japan (pp. 350-362) https://doi.org/10.1016/J.APENERGY.2019.04.019
  14. Li and Wang (2021) Design and operation of hybrid renewable energy systems: current status and future perspectives https://doi.org/10.1016/J.COCHE.2021.100669
  15. Tleis, N. D. Power Systems Modelling and Fault Analysis. Elsevier Ltd (2008). ISBN: 9780750680745
  16. Esmaeili and Najafi (2019) Energy-economic optimization of thin layer photovoltaic on domes and cylindrical towers (pp. 84-91)
  17. Petrollese et al. (2018) Use of weather forecast for increasing the self-consumption rate of home solar systems: an Italian case study (pp. 746-758) https://doi.org/10.1016/j.apenergy.2017.12.075
  18. Wadawa et al. (2021) Robustification of the H∞ controller combined with fuzzy logic and PI&PID-Fd for hybrid control of wind energy conversion system connected to the power grid based on DFIG (pp. 7539-7571) https://doi.org/10.1016/J.EGYR.2021.10.120
  19. Mahmoudi et al. (2021) Optimization of a hybrid energy system with/without considering back-up system by a new technique based on fuzzy logic controller https://doi.org/10.1016/J.ENCONMAN.2020.113723
  20. Balakishan et al. (2021) Smart fuzzy control based hybrid PV-wind energy generation system https://doi.org/10.1016/J.MATPR.2021.07.074
  21. Azadbakht et al. (2015) Energy consumption during impact cutting of canola stalk as a function of moisture content and cutting height (pp. 147-152) https://doi.org/10.1016/j.jssas.2013.10.002
  22. Luo (2021) Design of an adaptive controller for double-fed induction wind turbine power (pp. 1622-1626) https://doi.org/10.1016/J.EGYR.2021.09.047
  23. Wang et al. (2021) Maximizing the total power generation of faulty wind turbines via reduced power operation (pp. 36-44) https://doi.org/10.1016/J.ESD.2021.09.006
  24. Esameili Shayan et al. (2021) Design of an integrated photovoltaic site: case of Isfahan’s Jarghouyeh photovoltaic plant (pp. 229-250)
  25. Deng and Ge (2020) Global wind power development leads to high demand for neodymium praseodymium (NdPr): a scenario analysis based on market and technology development from 2019 to 2040 https://doi.org/10.1016/j.jclepro.2020.123299
  26. Ardaneh et al. (2022) Numerical analysis of the pitch angle effect on the performance improvement and flow characteristics of the 3-PB Darrieus vertical axis wind turbine https://doi.org/10.1016/J.ENERGY.2021.122339
  27. Csáji et al. (2020) A sampling-and-discarding approach to stochastic model predictive control for renewable energy systems (pp. 7142-7147) https://doi.org/10.1016/j.ifacol.2020.12.523
  28. Güler and Irmak (2020) Design, implementation and model predictive based control of a mode-changeable DC/DC converter for hybrid renewable energy systems https://doi.org/10.1016/j.isatra.2020.12.023
  29. Jaalam et al. (2016) A comprehensive review of synchronization methods for grid-connected converters of renewable energy source (pp. 1471-1481) https://doi.org/10.1016/J.RSER.2016.01.066
  30. Chang et al. (2019) Electricity price prediction based on hybrid model of Adam optimized LSTM neural network and wavelet transform https://doi.org/10.1016/J.ENERGY.2019.07.134
  31. Ghulomzoda et al. (2021) A novel approach of synchronization of microgrid with a power system of limited capacity https://doi.org/10.3390/SU132413975
  32. Alberizzi et al. (2020) Optimal sizing of a hybrid renewable energy system: importance of data selection with highly variable renewable energy sources https://doi.org/10.1016/j.enconman.2020.113303
  33. Gurung and Qiao (2018) Solar charging batteries: advances, challenges, and opportunities (pp. 1217-1230) https://doi.org/10.1016/j.joule.2018.04.006
  34. Esmaeili Shayan et al. (2017) Ahmad power quality in flexible photovoltaic system on curved surfaces (pp. 105-136)
  35. Esmaeili Shayan et al. (2020) Nuclear power plant or solar power plant IntechOpen
  36. Ghasemzadeh et al. (2020) Photovoltaic temperature challenges and bismuthene monolayer properties (pp. 190-195)
  37. Esmaeili Shayan et al. (2020) Solar energy and its purpose in net-zero energy building IntechOpen
  38. Joshi et al. (2019) Does involvement of local community ensure sustained energy access? A critical review of a solar PV technology intervention in rural India (pp. 272-281) https://doi.org/10.1016/j.worlddev.2019.05.028
  39. Villena-Ruiz et al. (2022) Extensive model validation for generic IEC 61400-27-1 wind turbine models https://doi.org/10.1016/J.IJEPES.2021.107331
  40. Merida García et al. (2021) The environmental and economic benefits of a hybrid hydropower energy recovery and solar energy system (PAT-PV), under varying energy demands in the agricultural sector https://doi.org/10.1016/J.JCLEPRO.2021.127078
  41. Rafiei et al. (2022) Hybrid solar desalination system for generation electricity and freshwater with nanofluid application: energy, exergy, and environmental aspects https://doi.org/10.1016/J.SETA.2021.101716
  42. Pastore et al. (2021) H2NG environmental-energy-economic effects in hybrid energy systems for building refurbishment in future national power to gas scenarios https://doi.org/10.1016/J.IJHYDENE.2021.11.154
  43. Pravin et al. (2020) A reactive scheduling and control framework for integration of renewable energy sources with a reformer-based fuel cell system and an energy storage device (pp. 147-165) https://doi.org/10.1016/j.jprocont.2020.01.005
  44. Koh et al. (2021) Higher 2nd life lithium titanate battery content in hybrid energy storage systems lowers environmental-economic impact and balances eco-efficiency https://doi.org/10.1016/J.RSER.2021.111704
  45. Tedesco and Casavola (2020) Load/frequency control in the presence of renewable energy systems: a reference-offset governor approach (pp. 12548-12553) https://doi.org/10.1016/j.ifacol.2020.12.1808
  46. Feist et al. (2021) A quasi-coupled wind wave experimental framework for testing offshore wind turbine floating systems https://doi.org/10.1016/J.TAML.2021.100294
  47. Polo et al. (2020) Benchmarking on improvement and site-adaptation techniques for modeled solar radiation datasets (pp. 469-479) https://doi.org/10.1016/j.solener.2020.03.040
  48. Esmaeili Shayan et al. (2021) Possibility of supplying energy to border villages by solar energy sources (pp. 279-289) https://doi.org/10.22059/EES.2021.246079
  49. Bashir, M., Sadeh, J.: Optimal sizing of hybrid wind/photovoltaic/battery considering the uncertainty of wind and photovoltaic power using Monte Carlo. In: Proceedings of the 2012 11th International Conference on Environment and Electrical Engineering, EEEIC 2012—Conference Proceedings, pp. 1081–1086 (2012).
  50. Fan et al. (2022) Random reselection particle swarm optimization for optimal design of solar photovoltaic modules https://doi.org/10.1016/J.ENERGY.2021.121865
  51. Jahangir et al. (2019) techno-economic comparison of a photovoltaic/thermal organic Rankine cycle with several renewable hybrid systems for a residential area in Rayen, Iran (pp. 244-261) https://doi.org/10.1016/j.enconman.2019.05.010
  52. Tsoumakas, G., Katakis, I., Vlahavas, I.: Effective and efficient multilabel classification in domains with large number of labels. In: Workshop on Mining Multidimensional Data, pp. 30–44 (2008).
  53. Bahari et al. (2021) Exergo-economic analysis and optimization of a combined solar collector with steam and Organic Rankine Cycle using particle swarm optimization (PSO) algorithm https://doi.org/10.1016/J.CLET.2021.100221
  54. Maiti et al. (2022) Alternate computation of the unit vectors synthesis towards synchronization of current-controlled grid-tie converter for renewable power system: An embedded outlook https://doi.org/10.1016/J.JESTCH.2021.06.003
  55. Kumar Rasappan et al. (2022) A Novel ultra sparse matrix converter as a power transferring device for gearless wind energy conversion systems based on renewable energy applications https://doi.org/10.1016/J.SETA.2021.101830
  56. Cvetanovic and Janda (2022) A fast finite sample count symmetric component extraction method for use in grid side converters https://doi.org/10.1016/J.IJEPES.2021.107857
  57. Shi et al. (2016) Energy conversion characteristics of a hydropneumatic transformer in a sustainable-energy vehicle (pp. 77-85) https://doi.org/10.1016/J.APENERGY.2016.03.034
  58. Corigliano et al. (2020) Holistic geospatial data-based procedure for electric network design and least-cost energy strategy (pp. 1-15) https://doi.org/10.1016/j.esd.2020.06.008
  59. Velilla et al. (2019) Monitoring system to evaluate the outdoor performance of solar devices considering the power rating conditions (pp. 79-85) https://doi.org/10.1016/J.SOLENER.2019.10.051
  60. Villena-Ruiz et al. (2020) Field validation of a standard Type 3 wind turbine model implemented in DIgSILENT-PowerFactory following IEC 61400–27-1 guidelines https://doi.org/10.1016/J.IJEPES.2019.105553
  61. Suer et al. (2021) Carbon footprint of scenarios towards climate-neutral steel according to ISO 14067 https://doi.org/10.1016/J.JCLEPRO.2021.128588