OPTIMIZING WIND POWER PLANTS: COMPARATIVE ENHANCEMENT IN LOW WIND SPEED ENVIRONMENTS
Mustafa Hussein Ibrahim
mustafahussein@uomosul.edu.iqUniversity of Mosul, Department of New and Renewable Energies (Iraq)
https://orcid.org/0000-0002-9950-6524
Muhammed A. Ibrahim
Ninevah University, Department of System and Control Engineering (Iraq)
https://orcid.org/0000-0003-4818-1245
Salam Ibrahim Khather
Ninevah University, Department of System and Control Engineering (Iraq)
https://orcid.org/0000-0002-9082-2360
Abstract
The study aims to optimize wind farm efficiency in low wind speed regions using the HOMER Pro tool to examine the impact of wind turbine ratings on overall efficiency of wind farms. boosting wind farm efficiency is essential for improving economic viability and grid integration. We propose the establishment of three wind farms, each possessing equal capacities but different in individual turbine capacities 1.5 kW, 3.4 kW and 5.1 kW, then optimize their performance in simulation environment. Through employing HOMER Pro optimization algorithm, we assess all wind farms over the period of one year, taking into account wind speed, temperature and geospatial coordinates. Although all wind farms have equal total capacities, simulation results revealed disparities in their generation abilities, reaching up to 22%, favouring the farm with smaller turbines. Furthermore, the results demonstrated that as wind speed decreases, the disparity in power generation between wind farms increases, reaching 51.9% in November, the month with the lowest wind speeds. These findings provide a comprehensive understanding of wind farm behaviour, particularly regarding turbine sizes, and contribute to the research community's efforts to enhance wind farm power production in low wind speed regions. They also help find solutions to enable the embrace of wind energy and decrease fossil fuel consumption in such regions, fulfilling their international sustainability commitments.
Keywords:
wind turbine optimization, wind farms, HOMER, low wind speed regions, wind turbine sizingReferences
[1] The Atmospheric Science Data Center (ASDC): NASA Earth Science Data. NASA [https://earthdata.nasa.gov/eosdis/daacs/asdc] (available: 24.03.2024).
Google Scholar
[2] Al-Ansari N., Pusch R., Knutsson S.: Suggested landfill sites for hazardous waste in Iraq. Natural Science 5(4), 2013, 463–477.
Google Scholar
[3] Al-Taai O. T., Wadi Q. M., Al-Tmimi A. I.: Assessment of a viability of wind power in Iraq. American Journal of Electrical Power and Energy Systems 3(3), 2014, 60–70 [https://doi.org/10.11648/j.epes.20140303.12].
Google Scholar
[4] Al-ubeidi K. M. Y.: Assessment of Wind speed for Electricity Generation in Technical Institute/Mosul. Journal of Kerbala University 10(3), 2012.
Google Scholar
[5] Arroyo A. et al.: CO2 footprint reduction and efficiency increase using the dynamic rate in overhead power lines connected to wind farms. Applied Thermal Engineering 130, 2018, 1156–1162.
Google Scholar
[6] Byrne R. et al.: A comparison of four microscale wind flow models in predicting the real-world performance of a large-scale peri-urban wind turbine, using onsite LiDAR wind measurements. Sustainable Energy Technologies and Assessments 46, 2021, 101323 [https://doi.org/10.1016/j.seta.2021.101323].
Google Scholar
[7] Da Silva A. I. R. D. et al.: Aerodynamic interference caused by wake effects of repowered wind farms on the annual energy production in neighboring wind farms. Sustainable Energy Technologies and Assessments 64, 2024, 103704 [https://doi.org/10.1016/j.seta.2024.103704].
Google Scholar
[8] Dihrab S. S., Sopian K.: Electricity generation of hybrid PV/wind systems in Iraq. Renewable Energy 35(6), 2010, 1303–1307.
Google Scholar
[9] Hassoon A. F.: Assessment potential wind energy in the north area of Iraq. International Journal of Energy and Environment 4(5), 2013, 807–814.
Google Scholar
[10] Hu W. et al.: Wind farm layout optimization in complex terrain based on CFD and IGA-PSO. Energy 288, 2024, 129745.
Google Scholar
[11] Ibrahim M. H., Ibrahim M. A.: Solar-Wind Hybrid Power System Analysis Using Homer for Duhok, Iraq. Przegląd Elektrotechniczny 97(9), 2021.
Google Scholar
[12] Ibrahim M. H., Ibrahim M. A.: Modelling and Analysis of SA-SPV System with bi-directional inverter for lighting load. Przegląd Elektrotechniczny 98(5), 2022.
Google Scholar
[13] Ibrahim M. H., Ibrahim M. A., Khather S. I.: Hydrogen solar pump in nocturnal irrigation: A sustainable solution for arid environments. Energy Conversion and Management 304, 2024, 118219.
Google Scholar
[14] Iqbal R. et al.: Comparative study based on techno-economics analysis of different shipboard microgrid systems comprising PV/wind/fuel cell/battery/diesel generator with two battery technologies: A step toward green maritime transportation. Renewable Energy 221, 2024, 119670.
Google Scholar
[15] Kazem H. A., Chaichan M. T.: Status and future prospects of renewable energy in Iraq. Renewable and Sustainable Energy Reviews 16(8), 2012, 6007–6012.
Google Scholar
[16] Li C., Liu L., Lu X.: A grouping strategy for reinforcement learning-based collective yaw control of wind farms. Theoretical and Applied Mechanics Letters 14(1), 2024, 100491 [https://doi.org/10.1016/j.taml.2024.100491].
Google Scholar
[17] Mittal P., Christopoulos G., Subramanian S.: Energy enhancement through noise minimization using acoustic metamaterials in a wind farm. Renewable Energy 224, 2024, 120188 [https://doi.org/10.1016/j.renene.2024.120188].
Google Scholar
[18] Wafa'a W. A. A., Fouad S. F.: Tectonic and structural evolution of Al-Jazira area. Iraqi Bulletin of Geology and Mining 3, 2009.
Google Scholar
[19] United Nations: "Sustainable Development Goals" United Nations Sustainable Development, 2024 [https://sdgs.un.org/goals].
Google Scholar
[20] Sagbansua L., Balo F.: Decision making model development in increasing wind farm energy efficiency. Renewable Energy 109, 2017, 354–362.
Google Scholar
[21] Wang Q. et al.: Synchronized optimization of wind farm start-stop and yaw control based on 3D wake model. Renewable Energy 223, 2024, 120044.
Google Scholar
[22] Yadav H. K. et al.: Diurnal variations in wind power density analysis for optimal wind energy integration in different Indian sites. Sustainable Energy Technologies and Assessments 64, 2024, 103744.
Google Scholar
[23] Zahedi A., AL-bonsrulah H. A., Tafavogh M.: Conceptual design and simulation of a stand-alone Wind/PEM fuel Cell/Hydrogen storage energy system for off-grid regions, a case study in Kuhin, Iran. Sustainable Energy Technologies and Assessments 57, 2023, 103142.
Google Scholar
[24] Zhang D. et al.: Bilevel optimization of non-uniform offshore wind farm layout and cable routing for the refined LCOE using an enhanced PSO. Ocean Engineering 299, 2024, 117244.
Google Scholar
[25] Zhang Z. et al.: Identification method of all-operating-point admittance model for wind farms considering frequency-coupling characteristics. International Journal of Electrical Power & Energy Systems 158, 2024, 109953.
Google Scholar
[26] Zhu L. et al.: Multi-criteria evaluation and optimization of a novel thermodynamic cycle based on a wind farm, Kalina cycle and storage system: an effort to improve efficiency and sustainability. Sustainable Cities and Society 96, 2023, 104718 [https://doi.org/10.1016/j.scs.2023.104718].
Google Scholar
Authors
Mustafa Hussein Ibrahimmustafahussein@uomosul.edu.iq
University of Mosul, Department of New and Renewable Energies Iraq
https://orcid.org/0000-0002-9950-6524
Authors
Muhammed A. IbrahimNinevah University, Department of System and Control Engineering Iraq
https://orcid.org/0000-0003-4818-1245
Authors
Salam Ibrahim KhatherNinevah University, Department of System and Control Engineering Iraq
https://orcid.org/0000-0002-9082-2360
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