Techno-Economic Investigation Using Several Metaheuristic Algorithms for Optimal Sizing of Stand-Alone Microgrid Incorporating Hybrid Renewable Energy Sources and Hybrid Energy Storage System
Increasing energy demand worldwide has resulted in more penetration of renewable sources for developing non-polluted electric energy despite their prices are not economically competitive to traditional generation systems due to intermittent nature of renewable resources. Energy storage systems are used to counteract the intermittent nature of renewable sources. Therefore, the optimal sizing and design of stand-alone renewable generating systems is a significant concern to get a more cost-effective system. This paper focuses on achieving the optimum design and size of a microgrid to meet the load requirements and reducing the total cost including capital, investment, operational and maintenance costs. For this aim, the sizing problem is formulated to be solved using three well-known metaheuristic algorithms, namely, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO) and Cuckoo Search Optimization (CSO). The employed microgrid comprises hybrid renewable energy sources of PV/Wind systems integrated with a hybrid energy storage system of Battery and FC/Electrolyzer set for supplying AC loads located in Zafarana, Egypt. On the basis of real meteorological data of the studied location, the produced energies from the renewable sources are estimated using MATLAB developed algorithms. The simulation results showed that the optimized design using CSO can robustly and efficiently yield the optimal design of a microgrid.
Copyright © 2020 Praise Worthy Prize - All rights reserved.
R. Bhosale and V. Agarwal, Control of fuel cell and electrolyzer based hydrogen storage system with ultra-capacitor for voltage stability and enhanced transient stability of a DC micro grid, in 2018 International Conference on Power, Instrumentation, Control and Computing (PICC), 2018, pp. 1–6.
S. Atcitty, J. Neely, D. Ingersoll, A. Akhil, and K. Waldrip, Battery Energy Storage System, in Power Electronics for Renewable and Distributed Energy Systems, Springer, 2013, pp. 333–366.
P. Paliwal, N. P. Patidar and R. K. Nema, Determination of reliability constrained optimal resource mix for an autonomous hybrid power system using particle swarm optimization, Renewable Energy, vol. 63, pp. 194-204, 2014.
V. M. Sanchez, A. U. Chavez-Ramirez, S. M. Duron-Torres, J. Hernandez, L. G. Arriaga, and J. M. Ramirez, Techno-economical optimization based on swarm intelligence algorithm for a stand-alone wind-photovoltaic-hydrogen power system at south-east region of Mexico, Int. J. Hydrogen Energy, vol. 39, no. 29, pp. 16646–16655, 2014.
A. Askarzadeh and L. A. Dos Santos Coelho, A novel framework for optimization of a grid independent hybrid renewable energy system: A case study of Iran, Solar Energy, vol. 112, pp. 383-396, 2015.
A.Hassan, Magdi S., M. Kandil and S. Mohamed, Modified particle swarm optimisation technique for optimal design of small renewable energy system supplying a specific load at Mansoura University, IET Renewable Power Generation, vol. 9, no. 5, pp. 474-483, 2015.
A. C. Nagabhushana, R. Jyoti, and A. B. Raju, Economic analysis and comparison of proposed HRES for stand-alone applications at various places in Karnataka state, in ISGT2011-India, IEEE 2011, pp. 380–385.
H. Ren, Q. Wu, W. Gao, and W. Zhou, Optimal operation of a grid-connected hybrid PV/fuel cell/battery energy system for residential applications, Energy, vol. 113, pp. 702–712, 2016.
Koutroulis, E., Kolokotsa, D., Potirakis, A., Kalaitzakis, K., Methodology for optimal sizing of stand-alone photovoltaic/wind-generator systems using genetic algorithms, Solar Energy, vol. 80, no. 9, pp. 1072-1088, 2016.
H. Z. Al Garni, A. Awasthi, and M. A. M. Ramli, Optimal design and analysis of grid-connected photovoltaic under different tracking systems using HOMER, Energy Convers. Manag., vol. 155, pp. 42–57, 2018.
K. Anoune, A. Laknizi, M. Bouya, A. Astito, and A. Ben Abdellah, Sizing a PV-Wind based hybrid system using deterministic approach, Energy Convers. Manag., vol. 169, pp. 137–148, 2018.
M. D. A. Al-Falahi, S. D. G. Jayasinghe, and H. Enshaei, A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system, Energy Convers. Manag., vol. 143, pp. 252–274, 2017.
M. Ghofrani and N. N. Hosseini, Optimizing hybrid renewable energy systems: a review, Sustain. energy-technological issues, Appl. case Stud., pp. 161–176, 2016.
S. Sanajaoba and E. Fernandez, Maiden application of Cuckoo Search algorithm for optimal sizing of a remote hybrid renewable energy System, Renewable Energy, vol. 96, pp. 1–10, 2016.
P. Paliwal, N. P. Patidar, and R. K. Nema, Determination of reliability constrained optimal resource mix for an autonomous hybrid power system using particle swarm optimization, Renew. energy, vol. 63, pp. 194–204, 2014.
O. Hazem Mohammed, Y. Amirat, and M. Benbouzid, Economical evaluation and optimal energy management of a stand-alone hybrid energy system handling in genetic algorithm strategies, Electronics, vol. 7, no. 10, p. 233, 2018.
J. Zeng, M. Li, J. F. Liu, J. Wu, and H. W. Ngan, Operational optimization of a stand-alone hybrid renewable energy generation system based on an improved genetic algorithm, in IEEE PES general meeting, 2010, pp. 1–6.
The Modern-Era Retrospective analysis for Research and Applications,windspeed,Temperature and solar radiation data, [Online, Accessed Aug. 2019].
R. A. Younis, D. K. Ibrahim, and E. M. Aboul-Zahab, Power Management Regulation Control Integrated with Demand Side Management for Stand-alone Hybrid Microgrid Considering Battery Degradation, Int. J. Renew. Energy Res., vol. 9, no. 4, pp. 1912–1923,2019.
Wind speed extrapolation, Roughness definitions according to the EuropeanWindAtlas. [Online]. [Accessed Aug. 2019].
M.-A. Yazdanpanah, Modeling and sizing optimization of hybrid photovoltaic/wind power generation system, J. Ind. Eng. Int., vol. 10, no. 1, p. 49, 2014.
M. B. Eteiba, S. Barakat, M. M. Samy, and W. I. Wahba, Optimization of an off-grid PV/Biomass hybrid system with different battery technologies, Sustain. cities Soc., vol. 40, pp. 713–727, 2018.
M. R. Islam, R. Saidur, and N. A. Rahim, Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function, Energy, vol. 36, no. 2, pp. 985–992, 2011.
S. H. A. K. a. P. S. Pishgar-Komleh, Wind speed and power density analysis based on Weibull and Rayleigh distributions (a case study: Firouzkooh county of Iran), Renewable and Sustainable Energy Reviews, no. 42, pp. 313-322, 2015.
Abdel-Karim Ismail, and Mahmoud S Daud, Design of isolated hybrid systems minimizing costs and pollutant emissions, Renewable Energy, vol. 44, pp. 215–224, 2012.
A. K. Kaviani, G. H. Riahy, and S. H. M. Kouhsari, Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages, Renewable Energy, vol. 34, no. 11, pp. 2380–2390, 2009.
M. D. A. Al-Falahi et al., Techno-economic feasibility study of battery-powered ferries, in 2018 IEEE 4th Southern Power Electronics Conference (SPEC), 2018, pp. 1–7..
A. Maleki and A. Askarzadeh, Comparative study of artificial intelligence techniques for sizing of a hydrogen-based stand-alone photovoltaic/wind hybrid system, International Journal of Hydrogen Energy, vol. 39, no. 19, pp. 9973-9984, 2014.
O. H. Mohammed, Y. Amirat, and M. Benbouzid, Particle swarm optimization of a hybrid wind/tidal/PV/battery energy system. Application to a remote area in Bretagne, France, Energy Procedia, vol. 162, pp. 87–96, 2019.
M. A. Hossain, H. R. Pota, S. Squartini, and A. F. Abdou, Modified PSO algorithm for real-time energy management in grid-connected microgrids, Renewable Energy, vol. 136, pp. 746–757, 2019.
H. T. Rauf, U. Shoaib, M. I. Lali, M. Alhaisoni, M. N. Irfan, and M. A. Khan, “Particle Swarm Optimization With Probability Sequence for Global Optimization, IEEE Access, vol. 8, pp. 110535–110549, 2020.
A. Yahiaoui, F. Fodhil, K. Benmansour, M. Tadjine, and N. Cheggaga, Grey wolf optimizer for optimal design of hybrid renewable energy system PV-Diesel Generator-Battery: Application to the case of Djanet city of Algeria, Sol. Energy, vol. 158, pp. 941–951, 2017.
N. M. Hatta, A. M. Zain, R. Sallehuddin, Z. Shayfull, and Y. Yusoff, Recent studies on optimisation method of Grey Wolf Optimiser (GWO): a review (2014–2017), Artif. Intell. Rev., vol. 52, no. 4, pp. 2651–2683, 2019.
A. Tabak, E. Kayabasi, M. T. Guneser, and M. Ozkaymak, Grey wolf optimization for optimum sizing and controlling of a PV/WT/BM hybrid energy system considering TNPC, LPSP, and LCOE concepts, Energy Sources, Part A Recover. Util. Environ. Eff., pp. 1–21, 2019.
O. Nadjemi, T. Nacer, A. Hamidat, and H. Salhi, Optimal hybrid PV/wind energy system sizing: Application of cuckoo search algorithm for Algerian dairy farms, Renew. Sustain. Energy Rev., vol. 70, pp. 1352–1365, 2017.
M. A. Mohamed, A. M. Eltamaly, A. I. Alolah, and A. Y. Hatata, A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems, Int. J. green energy, vol. 16, no. 1, pp. 86–100, 2019.
M. Shadman, A. Mahmoudi, and S. Nikkhah, Optimal Management of Distributed Generations in a Residential Complex Using Cuckoo Search Algorithm, in 2019 Iranian Conference on Renewable Energy & Distributed Generation (ICREDG), 2019, pp. 1–7.
Techno-economic data for batteries, [Online]. [Accessed December 2019].
Techno-economic data for renewable energy sources, [Online]. [Accessed December 2019].
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2021 Praise Worthy Prize