Wind Farm Layout Optimization Using Multiobjective Modified Electric Charged Particles Optimization Algorithm Based on Game Theory Indexing in Real Onshore Area

Designing onshore wind farms presents unique challenges related to interactions between terrain and landscape characteristics. This research focuses on optimizing the layout of onshore wind farms while considering the effect of the terrain and land characteristics. Three real onshore site areas in S...

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Published in:	Sustainability Vol. 16; no. 23; p. 10222
Main Authors:	Hidayat, Taufal, Ramli, Makbul A. M., Hardi, Apri Zulmi, Bouchekara, Houssem R. E. H., Milyani, Ahmad H.
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.12.2024
Subjects:	Analysis Buildings and facilities Charged particles Design Efficiency Energy Game theory Genetic algorithms Integer programming Land use Mathematical optimization Noise control Offshore Optimization algorithms Plant layout Turbines Wind farms Wind power Saudi Arabia
ISSN:	2071-1050, 2071-1050
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Abstract	Designing onshore wind farms presents unique challenges related to interactions between terrain and landscape characteristics. This research focuses on optimizing the layout of onshore wind farms while considering the effect of the terrain and land characteristics. Three real onshore site areas in South Sulawesi, Indonesia, are selected for wind farm design and optimization. A novel optimization algorithm, the Multiobjective Modified Electric Charged Particles Optimization (MOMECPO), is introduced to minimize both the Levelized Cost of Electricity (LCOE) and noise levels. This algorithm employs a new game theory-based indexing method to effectively sort the Pareto solution set. The results show that the proposed algorithm enhances the exploration and exploitation capabilities of the solutions obtained. Our optimal solutions demonstrate that MOECPO achieves LCOE values of 6.78, 7.73, and 5.56 US cents/kWh for Sites 1, 2, and 3, respectively. Correspondingly, noise levels are recorded at 53.71 dBA, 52.53 dBA, and 55.25 dBA for the same sites. These values outperform seven other comparative algorithms, with NSGA achieving the closest performance among them, yielding LCOE values of 6.865, 7.815, and 5.579 US cents/kWh, and noise levels of 53.858, 52.556, and 55.197 dBA for Sites 1, 2, and 3, respectively. As for the terrain effect, our findings reveal that sites with complex terrains tend to have higher AEP and lower LCOE due to the steeper slopes. However, this site also experiences increased noise levels because of the higher energy production.
AbstractList	Designing onshore wind farms presents unique challenges related to interactions between terrain and landscape characteristics. This research focuses on optimizing the layout of onshore wind farms while considering the effect of the terrain and land characteristics. Three real onshore site areas in South Sulawesi, Indonesia, are selected for wind farm design and optimization. A novel optimization algorithm, the Multiobjective Modified Electric Charged Particles Optimization (MOMECPO), is introduced to minimize both the Levelized Cost of Electricity (LCOE) and noise levels. This algorithm employs a new game theory-based indexing method to effectively sort the Pareto solution set. The results show that the proposed algorithm enhances the exploration and exploitation capabilities of the solutions obtained. Our optimal solutions demonstrate that MOECPO achieves LCOE values of 6.78, 7.73, and 5.56 US cents/kWh for Sites 1, 2, and 3, respectively. Correspondingly, noise levels are recorded at 53.71 dBA, 52.53 dBA, and 55.25 dBA for the same sites. These values outperform seven other comparative algorithms, with NSGA achieving the closest performance among them, yielding LCOE values of 6.865, 7.815, and 5.579 US cents/kWh, and noise levels of 53.858, 52.556, and 55.197 dBA for Sites 1, 2, and 3, respectively. As for the terrain effect, our findings reveal that sites with complex terrains tend to have higher AEP and lower LCOE due to the steeper slopes. However, this site also experiences increased noise levels because of the higher energy production.
Audience	Academic
Author	Hidayat, Taufal Ramli, Makbul A. M. Milyani, Ahmad H. Bouchekara, Houssem R. E. H. Hardi, Apri Zulmi
Author_xml	– sequence: 1 givenname: Taufal orcidid: 0000-0003-0193-2929 surname: Hidayat fullname: Hidayat, Taufal – sequence: 2 givenname: Makbul A. M. surname: Ramli fullname: Ramli, Makbul A. M. – sequence: 3 givenname: Apri Zulmi orcidid: 0000-0003-4738-610X surname: Hardi fullname: Hardi, Apri Zulmi – sequence: 4 givenname: Houssem R. E. H. orcidid: 0000-0001-7702-990X surname: Bouchekara fullname: Bouchekara, Houssem R. E. H. – sequence: 5 givenname: Ahmad H. orcidid: 0000-0002-1926-9486 surname: Milyani fullname: Milyani, Ahmad H.
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Cites_doi	10.1016/j.energy.2016.07.062 10.1016/j.renene.2018.03.052 10.3390/ijerph14070753 10.1002/we.339 10.1016/j.jweia.2017.12.016 10.1016/j.enconman.2013.10.003 10.3390/su16072611 10.1109/TPWRS.2015.2452920 10.1016/j.apenergy.2019.114189 10.5194/wes-4-663-2019 10.3390/en12101925 10.1016/j.apenergy.2020.114896 10.1080/03052150902822141 10.5194/wes-8-255-2023 10.1016/j.enconman.2016.11.014 10.1109/CEC.2002.1004388 10.2172/897434 10.1016/0045-7949(87)90223-9 10.1016/j.rser.2010.11.045 10.1016/j.renene.2012.07.021 10.1016/j.rser.2012.11.040 10.2172/1527336 10.1016/j.renene.2022.11.084 10.2172/1756710 10.1016/j.enpol.2012.01.061 10.1109/4235.996017 10.3390/app8112053 10.1088/1742-6596/753/6/062011 10.1016/j.energy.2014.01.082 10.1109/TSTE.2018.2885946 10.1088/1742-6596/1618/4/042039 10.1016/j.renene.2015.06.026 10.1016/j.energy.2020.119214 10.1016/j.renene.2017.07.057 10.3390/su142013688 10.1049/iet-rpg.2017.0787 10.1115/1.4027847
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References	ref_50 Khan (ref_3) 2013; 19 Chen (ref_5) 2014; 77 Kwong (ref_22) 2014; 136 Huang (ref_23) 2020; 11 ref_10 Stanley (ref_27) 2019; 4 ref_52 ref_51 Mittal (ref_19) 2017; 132 Rao (ref_46) 1987; 25 Sisbot (ref_26) 2010; 13 ref_16 Brogna (ref_12) 2019; 259 Langer (ref_42) 2023; 202 Song (ref_14) 2013; 50 Nyborg (ref_20) 2022; 8 Wilson (ref_37) 2018; 126 Kuo (ref_15) 2018; 174 ref_21 Yang (ref_35) 2016; 31 Tingey (ref_18) 2017; 144 ref_29 Song (ref_36) 2014; 67 Dwijanarko (ref_44) 2020; 3 ref_34 Wu (ref_17) 2020; 267 ref_33 ref_32 Moreno (ref_25) 2021; 216 Vogt (ref_38) 2011; 15 Hou (ref_6) 2016; 113 Deb (ref_30) 2002; 6 Dykes (ref_24) 2020; 1618 ref_45 Feng (ref_11) 2014; 524 ref_43 ref_41 Grassi (ref_39) 2012; 45 ref_40 ref_1 Deb (ref_31) 2013; 18 Annamdas (ref_47) 2009; 41 ref_2 Tang (ref_13) 2018; 12 ref_49 ref_48 ref_9 Romero (ref_4) 2016; 85 ref_8 Zaaijer (ref_28) 2016; 753 ref_7
References_xml	– volume: 524 start-page: 012146 year: 2014 ident: ref_11 article-title: Wind Farm Layout Optimization in Complex Terrain: A Preliminary Study on a Gaussian Hill publication-title: J. Phys. – ident: ref_9 – volume: 113 start-page: 487 year: 2016 ident: ref_6 article-title: Optimization of Offshore Wind Farm Layout in Restricted Zones publication-title: Energy doi: 10.1016/j.energy.2016.07.062 – ident: ref_32 – volume: 126 start-page: 681 year: 2018 ident: ref_37 article-title: Evolutionary Computation for Wind Farm Layout Optimization publication-title: Renew. Energy doi: 10.1016/j.renene.2018.03.052 – volume: 3 start-page: 440 year: 2020 ident: ref_44 article-title: Analisa Biaya Pembukaan Lahan Tanpa Bakar Di Desa Telaga Langsat Kecamatan Takisung Kabupaten Tanah Laut publication-title: J. Sylva Sci. – ident: ref_51 – ident: ref_16 doi: 10.3390/ijerph14070753 – volume: 13 start-page: 297 year: 2010 ident: ref_26 article-title: Optimal Positioning of Wind Turbines on Gökceada Using Multi-Objective Genetic Algorithm publication-title: Wind Energy doi: 10.1002/we.339 – volume: 174 start-page: 94 year: 2018 ident: ref_15 article-title: A Novel Wake Model for Wind Farm Design on Complex Terrains publication-title: J. Wind Eng. Ind. Aerodyn. doi: 10.1016/j.jweia.2017.12.016 – volume: 77 start-page: 484 year: 2014 ident: ref_5 article-title: A System-Level Cost-of-Energy Wind Farm Layout Optimization with Landowner Modeling publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2013.10.003 – ident: ref_1 – ident: ref_49 doi: 10.3390/su16072611 – volume: 31 start-page: 2135 year: 2016 ident: ref_35 article-title: Wind Farm Layout Optimization and Its Application to Power System Reliability Analysis publication-title: IEEE Trans. Power Syst. doi: 10.1109/TPWRS.2015.2452920 – volume: 259 start-page: 114189 year: 2019 ident: ref_12 article-title: A New Wake Model and Comparison of Eight Algorithms for Layout Optimization of Wind Farms in Complex Terrain publication-title: Appl. Energy doi: 10.1016/j.apenergy.2019.114189 – ident: ref_52 – volume: 18 start-page: 602 year: 2013 ident: ref_31 article-title: An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point Based Non-Dominated Sorting Approach, Part I: Solving Problems with Box Constraints publication-title: IEEE Trans. Evol. Comput. – ident: ref_48 – volume: 4 start-page: 663 year: 2019 ident: ref_27 article-title: Massive Simplification of the Wind Farm Layout Optimization Problem publication-title: Wind Energy Sci. doi: 10.5194/wes-4-663-2019 – ident: ref_8 doi: 10.3390/en12101925 – volume: 267 start-page: 114896 year: 2020 ident: ref_17 article-title: Optimizing the Layout of Onshore Wind Farms to Minimize Noise publication-title: Appl. Energy doi: 10.1016/j.apenergy.2020.114896 – volume: 41 start-page: 737 year: 2009 ident: ref_47 article-title: Multi-Objective Optimization of Engineering Systems Using Game Theory and Particle Swarm Optimization publication-title: Eng. Optim. doi: 10.1080/03052150902822141 – ident: ref_45 – volume: 8 start-page: 255 year: 2022 ident: ref_20 article-title: Optimization of Wind Farm Operation with a Noise Constraint publication-title: Wind Energy Sci. Discuss. doi: 10.5194/wes-8-255-2023 – volume: 132 start-page: 147 year: 2017 ident: ref_19 article-title: Optimizing the Number and Locations of Turbines in a Wind Farm Addressing Energy-Noise Trade-off: A Hybrid Approach publication-title: Energy Convers. Manag. doi: 10.1016/j.enconman.2016.11.014 – ident: ref_34 – ident: ref_29 doi: 10.1109/CEC.2002.1004388 – ident: ref_41 doi: 10.2172/897434 – volume: 25 start-page: 119 year: 1987 ident: ref_46 article-title: Game Theory Approach for Multiobjective Structural Optimization publication-title: Comput. Struct. doi: 10.1016/0045-7949(87)90223-9 – volume: 15 start-page: 1696 year: 2011 ident: ref_38 article-title: GIS-Based Approach for the Evaluation of Wind Energy Potential: A Case Study for the Kujawsko-Pomorskie Voivodeship publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2010.11.045 – volume: 50 start-page: 551 year: 2013 ident: ref_14 article-title: Bionic Optimization for Micro-Siting of Wind Farm on Complex Terrain publication-title: Renew. Energy doi: 10.1016/j.renene.2012.07.021 – volume: 19 start-page: 370 year: 2013 ident: ref_3 article-title: Iterative Non-Deterministic Algorithms in on-Shore Wind Farm Design: A Brief Survey publication-title: Renew. Sustain. Energy Rev. doi: 10.1016/j.rser.2012.11.040 – ident: ref_40 doi: 10.2172/1527336 – volume: 202 start-page: 320 year: 2023 ident: ref_42 article-title: Introducing Site Selection Flexibility to Technical and Economic Onshore Wind Potential Assessments: New Method with Application to Indonesia publication-title: Renew. Energy doi: 10.1016/j.renene.2022.11.084 – ident: ref_2 doi: 10.2172/1756710 – volume: 45 start-page: 73 year: 2012 ident: ref_39 article-title: Large Scale Technical and Economical Assessment of Wind Energy Potential with a GIS Tool: Case Study Iowa publication-title: Energy Policy doi: 10.1016/j.enpol.2012.01.061 – ident: ref_21 – volume: 6 start-page: 182 year: 2002 ident: ref_30 article-title: A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/4235.996017 – ident: ref_10 doi: 10.3390/app8112053 – volume: 753 start-page: 062011 year: 2016 ident: ref_28 article-title: Roadmap to the Multidisciplinary Design Analysis and Optimisation of Wind Energy Systems publication-title: J. Phys. Conf. Ser. doi: 10.1088/1742-6596/753/6/062011 – volume: 67 start-page: 454 year: 2014 ident: ref_36 article-title: Optimization of Wind Farm Micro-Siting for Complex Terrain Using Greedy Algorithm publication-title: Energy doi: 10.1016/j.energy.2014.01.082 – volume: 11 start-page: 126 year: 2020 ident: ref_23 article-title: 3-D Layout Optimization of Wind Turbines Considering Fatigue Distribution publication-title: IEEE Trans. Sustain. Energy doi: 10.1109/TSTE.2018.2885946 – ident: ref_50 – ident: ref_33 – volume: 1618 start-page: 042039 year: 2020 ident: ref_24 article-title: Optimization of Wind Farm Design for Objectives beyond LCOE publication-title: J. Phys. Conf. Ser. doi: 10.1088/1742-6596/1618/4/042039 – volume: 85 start-page: 359 year: 2016 ident: ref_4 article-title: The Impact of Land Use Constraints in Multi-Objective Energy-Noise Wind Farm Layout Optimization publication-title: Renew. Energy doi: 10.1016/j.renene.2015.06.026 – volume: 216 start-page: 119214 year: 2021 ident: ref_25 article-title: Multi-Objective Lightning Search Algorithm Applied to Wind Farm Layout Optimization publication-title: Energy doi: 10.1016/j.energy.2020.119214 – volume: 144 start-page: 547 year: 2017 ident: ref_18 article-title: Trading Off Sound Pressure Level and Average Power Production for Wind Farm Layout Optimization publication-title: Renew. Energy doi: 10.1016/j.renene.2017.07.057 – ident: ref_43 – ident: ref_7 doi: 10.3390/su142013688 – volume: 12 start-page: 1065 year: 2018 ident: ref_13 article-title: Optimisation of Wind Farm Layout in Complex Terrain via Mixed-Installation of Different Types of Turbines publication-title: IET Renew. Power Gener. doi: 10.1049/iet-rpg.2017.0787 – volume: 136 start-page: 091010 year: 2014 ident: ref_22 article-title: Multi-Objective Wind Farm Layout Optimization Considering Energy Generation and Noise Propagation with NSGA-II publication-title: J. Mech. Des. Trans. ASME doi: 10.1115/1.4027847
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SubjectTerms	Analysis Buildings and facilities Charged particles Design Efficiency Energy Game theory Genetic algorithms Integer programming Land use Mathematical optimization Noise control Offshore Optimization algorithms Plant layout Turbines Wind farms Wind power
Title	Wind Farm Layout Optimization Using Multiobjective Modified Electric Charged Particles Optimization Algorithm Based on Game Theory Indexing in Real Onshore Area
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