Parçacık sürü optimizasyonu temelli ultra hızlı yenilenebilir enerji kaynağı optimizasyon aracı tasarımı

Yıl 2024, Cilt: 39 Sayı: 4, 2289 - 2304, 20.05.2024

Cemil Altın

https://doi.org/10.17341/gazimmfd.1256203

Öz

Bu çalışmada, Hibrit Yenilenebilr Enerji Siatemleri optimizasyonunda kullanılmak üzere bu alanda en sık kullanılan HOMER programının olumsuz yönlerini bertaraf eden metasezgisel Parçacık Sürü Optimizasyonu tabanlı optimizasyon aracı tasarımı yapılmıştır. Güvenilirliğinin ortaya konması nedeniyle aynı yükü beslemek için gerekli hibrit sistem, hem geliştirilen araç ile hemde HOMER optimizasyon yazılımı ile optimize edilerek sonuçlar karşılaştırılmıştır. İşlem hızı bakımından yapılan karşılaştırmada aynı sistemi optimize etmede, HOMER yazılımının 936 saniyede elde etmiş olduğu sonucu 17 saniyede elde ederek tasarlanan sistemin daha hızlı sonuca ulaştığı görülmüştür. Ekonomik yönden yapılan karşılaştırmada ise iki ayrı aracın yapmış olduğu optimizasyon sonucunda; Enerji maliyetinde 1.737 % , Toplam Net Bugün ki Maliyette 0.85 % ve Başlangıç Sermayesinde ise 1.895 % lik fark bulunmakta olup sonuçlar arasında önemli bir farkın bulunmadığı gözlenmiştir. Elektriksel sonuçların kıyasında ise Beslenen yüklerde 0.031 %, Beslenemeyen yüklerde 1.071 % lik fark çıkmış olup elektriksel anlamda da sonuçların güvenilirliği ortaya konmuştur. Sonuçlar bu alandaki detaylı optimizasyon çalışmaları için umut vericidir. Ayrıca HOMER yazılımının sunmakta olduğu, ekonomik ve elektriksel detaylar, gerçeği temsil eden özgün bir sevk stratejisi sayesinde tasarlanan araç ile de kullanıcıya sunulmaktadır. Güvenilirlik parametresi olarak HOMER yazılımının içerdiği fakat daha önce metasezgisel algoritmalarla yapılan optimizasyon süreçlerinde hiç kullanılmamış olan kapasite eksikliği parametresi kullanılmaktadır. Kapasite eksikliği parametresi ilk defa metasezgisel algoritma ile yenilenebilir enerji kaynaklarının optimizasyonunda kullanılmıştır. Maliyet fonksiyonu olarak Enerji Maliyeti kullanılmıştır. Kısacası HOMER programına alternatif çok daha hızlı sonuca ulaşabilen ve HOMER programındaki hassasiyet, hantallık ve zorlu arama uzayı oluşturma süreçlerini bertaraf eden özgün, güvenilir bir optimizasyon aracı tasarlanmıştır. Bu araç sayesinde ayrıca, vekil modelleri, makine öğrenmesi veya derin öğrenme tabanlı optimizasyon sistemlerini eğitmek için gerekli optimizasyon çıktıları çok hızlı bir şekilde elde edilerek fazla sayıda veri üretilmesi kolaylaşacaktır.

Anahtar Kelimeler

HOMER, PSO, optimizasyon, yenilenebilir enerji, hibrit sistem

Kaynakça

• 1. Hoseinzadeh S., Astiaso Garcia D., Techno-economic assessment of hybrid energy flexibility systems for islands’ decarbonization: A case study in Italy , Sustainable Energy Technologies and Assessments, 51, 101929, 2022.
• 2. Can Ö., Eroğlu H., Öztürk A., Automatic generation controller based on whale optimization algorithm in PV-thermal power systems, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (2), 915–926, 2022.
• 3. Batista N. E., Carvalho P. C. M., Fernández-Ramírez L. M., Braga A. P. S., Optimizing methodologies of hybrid renewable energy systems powered reverse osmosis plants , Renewable and Sustainable Energy Reviews, 182, 113377, 2023.
• 4. Bourennani F., Rahnamayan S., Naterer G. F., Optimal Design Methods for Hybrid Renewable Energy Systems , 12 (2), 148–159, 2014.
• 5. Oladeji I., Zamora R., Lie T. T., Security constrained optimal placement of renewable energy sources distributed generation for modern grid operations , Sustainable Energy, Grids and Networks, 32, 100897, 2022.
• 6. Gjorgiev B., Li, B., Sansavini G., Calibration of cascading failure simulation models for power system risk assessment , Proceedings of the 29th European Safety and Reliability Conference (ESREL), 1911–1918, 2019.
• 7. Karimi D., Hajizadeh A., Kene R. O., Olwal T. O., Energy Management and Optimization of Large-Scale Electric Vehicle Charging on the Grid , World Electric Vehicle Journal 14 (4), 95, 2023.
• 8. Zheng S., Fu S., Pu Y., Li D., Arıcı M., Wang D., Yıldız Ç., Energy-saving microgrid system for underground in-situ heating of oil shale integrating renewable energy source: An analysis focusing on net present value , Journal of the Taiwan Institute of Chemical Engineers, 104717, 2023.
• 9. Bapin Y., Bagheri M., Zarikas V., Optimal Allocation of Spinning Reserves in Interconnected Energy Systems with Demand Response Using a Bivariate Wind Prediction Model , Energies 12 (20), 3816, 2019.
• 10. Bapin Y., Applıcatıon Of Probabılıstıc Methods For Effectıve And Relıable Operatıon Of Electrıcal And Electromechanıcal Systems , Nazarbayev University School of Engineering and Digital Sciences, 2021.
• 11. Shahhoseini A., Azimi-Shaghaghi A., Yazdanipour S., Techno-Economic Study and Sensitivity Analysis of an On-Grid Photovoltaic-Battery-Diesel Hybrid System Under Blackouts Conditions: A Case Study on an Industrial Unit in Iran , SSRN Electronic Journal, 2022.
• 12. Gusain C., Mohan Tripathi M., Nangia U., Study of Meta-heuristic Optimization Methodologies for Design of Hybrid Renewable Energy Systems , Thermal Science and Engineering Progress, 39, 101711, 2023.
• 13. Bouaouda A., Sayouti Y., Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art , Archives of Computational Methods in Engineering, 29 (6), 4049–4083, 2022.
• 14. Agajie T.F., Ali A., Fopah-Lele A., Amoussou I., Khan B., Velasco C.L.R., Tanyi E., A Comprehensive Review on Techno-Economic Analysis and Optimal Sizing of Hybrid Renewable Energy Sources with Energy Storage Systems, Energies 16 (2), 642, 2023.
• 15. Mandelli S., Barbieri J., Mereu R., Colombo E., Off-grid systems for rural electrification in developing countries: Definitions, classification and a comprehensive literature review , Renewable and Sustainable Energy Reviews, 58, 1621–1646, 2016.
• 16. Tabak A., Kayabasi E., Guneser M. T., Ozkaymak M., Grey wolf optimization for optimum sizing and controlling of a PV/WT/BM hybrid energy system considering TNPC, LPSP, and LCOE concepts, https://doi.org/10.1080/15567036.2019.1668880, 44 (1), 1508–1528, 2019.
• 17. Wei H., Chen S., Pan T., Tao J., Zhu M., Capacity configuration optimisation of hybrid renewable energy system using improved grey wolf optimiser , International Journal of Computer Applications in Technology, 68 (1), 1–11, 2022.
• 18. Dong W., Li Y., Xiang J., Optimal Sizing of a Stand-Alone Hybrid Power System Based on Battery/Hydrogen with an Improved Ant Colony Optimization , Energies, 9 (10), 785, 2016.
• 19. Javed M. S., Ma T., Techno-economic assessment of a hybrid solar-wind-battery system with genetic algorithm , Energy Procedia, 158, 6384–6392, 2019.
• 20. Hlal I. M., Ramachandaramurthy V. K., Hafiz Nagi F., Bin Tuan Abdullah T. A. R., Optimal Techno-Economic Design of Standalone Hybrid Renewable Energy System Using Genetic Algorithm , IOP Conference Series: Earth and Environmental Science, 268 (1), 12012, 2019.
• 21. Samy M. M., Barakat S., Ramadan H. S., A flower pollination optimization algorithm for an off-grid PV-Fuel cell hybrid renewable system , International Journal of Hydrogen Energy, 44 (4), 2141–2152, 2019.
• 22. Fathy A., Kaaniche K., Alanazi T. M., Recent Approach Based Social Spider Optimizer for Optimal Sizing of Hybrid PV/Wind/Battery/Diesel Integrated Microgrid in Aljouf Region , IEEE Access, 8, 57630–57645, 2020.
• 23. Kharrich M., Kamel S., Abdeen M., Mohammed O. H., Akherraz M., Khurshaid T., Rhee S. B., Developed approach based on equilibrium optimizer for optimal design of hybrid PV/Wind/Diesel/Battery Microgrid in Dakhla, Morocco , IEEE Access, 9, 13655–13670, 2021.
• 24. Al-Akayshee A. S., Kuznetsov O. N., Sultan H. M., Application of Equilibrium Optimization Algorithm for Optimal Design of PV/Hydroelectric Pumped Storage Energy system, Case Study-Iraq , Proceedings of the 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2021, 1354–1359, 2021.
• 25. Mouachi R., Jallal M. A., Gharnati F., Raoufi M., Multiobjective Sizing of an Autonomous Hybrid Microgrid Using a Multimodal Delayed PSO Algorithm: A Case Study of a Fishing Village , Computational Intelligence and Neuroscience, 2020, 2020.
• 26. Taslimi M., Ahmadi P., Ashjaee M., Rosen M. A., Design and mixed integer linear programming optimization of a solar/battery based Conex for remote areas and various climate zones , Sustainable Energy Technologies and Assessments, 45, 101104, 2021.
• 27. Rahmani N., Mostefai M., Multi-Objective MPSO/GA Optimization of an Autonomous PV-Wind Hybrid Energy System , Engineering, Technology & Applied Science Research, 12 (4), 8817–8824, 2022.
• 28. Bo G., Cheng P., Dezhi K., Xiping W., Chaodong L., Mingming G., Ghadimi N., Optimum structure of a combined wind/photovoltaic/fuel cell-based on amended Dragon Fly optimization algorithm: a case study, https://doi.org/10.1080/15567036.2022.2105453, 44 (3), 7109–7131, 2022.
• 29. Xu Y. P., Ouyang P., Xing S. M., Qi L. Y., Khayatnezhad M., Jafari H., Optimal structure design of a PV/FC HRES using amended Water Strider Algorithm , Energy Reports, 7, 2057–2067, 2021.
• 30. Jamshidi M., Askarzadeh A., Techno-economic analysis and size optimization of an off-grid hybrid photovoltaic, fuel cell and diesel generator system , Sustainable Cities and Society, 44, 310–320, 2019.
• 31. Lee K., Kum D., Complete design space exploration of isolated hybrid renewable energy system via dynamic programming , Energy Conversion and Management, 196, 920–934, 2019.
• 32. El-Sattar H. A., Kamel S., Hassan M. H., Jurado F., Optimal sizing of an off-grid hybrid photovoltaic/biomass gasifier/battery system using a quantum model of Runge Kutta algorithm , Energy Conversion and Management, 258, 115539, 2022.
• 33. Maleki A., Askarzadeh A., Artificial bee swarm optimization for optimum sizing of a stand-alone PV/WT/FC hybrid system considering LPSP concept , Solar Energy, 107, 227–235, 2014.
• 34. Ayan S., Toylan H., Size optimization of a stand-alone hybrid photovoltaic/wind/battery renewable energy system using a heuristic optimization algorithm , International Journal of Energy Research, 46 (11), 14908–14925, 2022.
• 35. Cetinbas I., Tamyurek B., Demirtas M., The Hybrid Harris Hawks Optimizer-Arithmetic Optimization Algorithm: A New Hybrid Algorithm for Sizing Optimization and Design of Microgrids , IEEE Access, 10, 19254–19283, 2022.
• 36. Mokhtara C., Negrou B., Settou N., Settou B., Samy M. M., Design optimization of off-grid Hybrid Renewable Energy Systems considering the effects of building energy performance and climate change: Case study of Algeria , Energy, 219, 119605, 2021.
• 37. Kamal M. M., Ashraf I., Fernandez E., Optimal sizing of standalone rural microgrid for sustainable electrification with renewable energy resources , Sustainable Cities and Society, 88, 104298, 2023.
• 38. Rateele T. N., Thamae L. Z., An optimization approach for the economic dispatch incorporating renewable energy resources into Lesotho power sources portfolio , Heliyon, 9 (4), e14748, 2023.
• 39. Tezer T., Yaman R., Yaman G., Evaluation of approaches used for optimization of stand-alone hybrid renewable energy systems , Renewable and Sustainable Energy Reviews, 73, 840–853, 2017.
• 40. Köse B., Aygün H., Pak S., Parameter estimation of the wind speed distribution model by dragonfly algorithm, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (3), 1747–1756, 2023.
• 41. Wadi M., Elmasry W., Tamyiğit F.A., Important considerations while evaluating wind energy potential, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (2), 947–962, 2022.
• 42. Saheb D., Koussa M., Hadji S., Technical and economical study of a stand-alone wind energy system for remote rural area electrification in Algeria , Renewable Energy and Power Quality Journal, 1 (12), 638–643, 2014.
• 43. Kennedy J., Eberhart R., Particle swarm optimization , Proceedings of ICNN’95 - International Conference on Neural Networks, 4, 1942–1948.
• 44. Altunbey Özbay F., Özbay E., A new approach for gender detection from voice data: Feature selection with optimization methods, Journal of the Faculty of Engineering and Architecture of Gazi University, 38 (2), 1179–1192, 2022.
• 45. Manwell J. F., McGowan J. G., Lead acid battery storage model for hybrid energy systems , Solar Energy, 50 (5), 399–405, 1993.
• 46. Dimitrios G., Interdepartmental Master Program in Business Administration , Interdepartmental Master Program in Business Administration, 2019.
• 47. Katsigiannis Y.A., Kanellos F.D., Papaefthimiou S., A software tool for capacity optimization of hybrid power systems including renewable energy technologies based on a hybrid genetic algorithm—tabu search optimization methodology , Energy Systems, 7 (1), 33–48, 2016.
• 48. Singh S., Singh M., Kaushik S. C., Feasibility study of an islanded microgrid in rural area consisting of PV, wind, biomass and battery energy storage system , Energy Conversion and Management, 128, 178–190, 2016.
• 49. Javed M. S., Song A., Ma T., Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm , Energy, 176, 704–717, 2019.
• 50. Hoarcă I. C., Bizon N., Șorlei I. S.,Thounthong P., Sizing Design for a Hybrid Renewable Power System Using HOMER and iHOGA Simulators , Energies 16 (4), 1926, 2023.
• 51. Rathod A. A., Subramanian B., Scrutiny of Hybrid Renewable Energy Systems for Control, Power Management, Optimization and Sizing: Challenges and Future Possibilities , Sustainability, 14 (24), 16814, 2022.
• 52. Akorede M. F., Oladeji A. S., Ariyo B. O., Omeiza I. O. A., Marzband M., Review of Researches on Techno-Economic Analysis and Environmental Impact of Hybrid Energy Systems , Jordan Journal of Electrical Engineering, 6 (2), 78–108, 2020.
• 53. Iweh C. D., Clarence S. G., Roger A. H., The Optimization of Hybrid Renewables for Rural Electrification: Techniques and the Design Problem , International Journal of Engineering Trends and Technology, 70 (9), 222–239, 2022.