Bir Hibrit Enerji Sisteminin Parçacık Sürüsü Optimizasyon Algoritması- Genetik Algoritma ve Gri Kurt Optimizasyon Algoritma Tekniği ile Enerji Yönetimi ve Optimizasyonu: Yalova Üniversitesi için bir vaka çalışması

Yıl 2022, , 853 - 879, 15.12.2022

Aykut Fatih Güven , Nuran Yörükeren

https://doi.org/10.31466/kfbd.1169643

Cited By: 3

Öz

Bu makale, bir üniversite kampüsünün enerji ihtiyacını karşılamak üzere tasarlanmış bir Hibrit Yenilenebilir Enerji Sisteminin (HRES) detaylı bir fizibilite araştırmasını sunmaktadır. HRES, Rüzgar Türbini (WT), Fotovoltaik (PV), Dizel Jeneratör, Batarya ve invertör bileşenlerini içerir. Güç dengesi kısıtlamasına bağlı olarak, Sistemin Yıllık Maliyetini azaltmak ve optimum WT gücünü, PV panel gücünü ve pil sayısını belirlemek için farklı optimizasyon teknikleri uygulanır. Seviyelendirilmiş Enerji Maliyeti ve Toplam Net Bugünkü Maliyeti en aza indirecek şekilde bir enerji yönetimi stratejisi sunulmakta ve Güç Kaynağı Kaybı Olasılığının operasyonun güvenilirliğini doğruladığı düşünülmektedir. Bileşenlerin optimum boyutlandırılmasını bulmak için HOMER ve MATLAB yazılımı kullanılarak sonuçlar elde edilir. Genetik Algoritma (GA), simülasyon sürecinde daha iyi performans göstererek hızlı ve güvenilir sonuçlar sunar. GA'yı en iyi sistem konfigürasyonunda kullanmak, sırasıyla 3.407975x103 kW PV, 50 kW WT ve 951.5493 kW Batarya, 3.9808$ x105 yıllık sistem maliyeti (ACS), 6.4580$ x106 net mevcut maliyet (NPC) ve 0.1998$/kWh. Güneş panelleri tüm sistemi kaplar ve Yenilenebilir Enerji Fraksiyonu (REF) %100'dür. Sonuçlar, bu çalışmada önerilen şemanın, aynı optimal konfigürasyonu kullanarak düzgün bir güç akışı sağlayabileceğini açıkça göstermektedir.

Anahtar Kelimeler

Enerji yönetimi, Algoritmalar, Optimal planlama, Güneş enerjisi, Hızlı boyutlandırma.

Energy Management and Optimization of a Hybrid Energy System by Particle Swarm Optimizing Algorithm-Genetic Algorithm and Gray Wolf Optimizing Algorithm Technique: A case study for Yalova University

Öz

This article presents a detailed feasibility investigation of a Hybrid Renewable Energy System (HRES) designed to meet the energy needs of a university campus. The HRES includes Wind Turbine (WT), Photovoltaic (PV), Diesel Generator, Battery, and inverter components. Based on the constraint of power balance, different optimization techniques are applied to reduce the Annual Cost of the System and determine the optimum WT power, PV panel power, and number of batteries. An energy management strategy is presented in a way to minimize the Levelized Cost of Energy and Total Net Present Cost, and it is thought that the Loss of Power Supply Probability validates the reliability of the operation. To find the optimum sizing of the components, results are obtained using the HOMER and MATLAB software. The Genetic Algorithm (GA) outperforms during the simulation process, delivering quick and dependable results. Using GA in the best system configuration, 3.407975x103 kW PV, 50 kW WT and 951.5493 kW Battery, $3.9808 x105 annual system cost (ACS), $6.4580 x106 net present cost (NPC), and $0.1998/kWh, respectively. Solar panels cover the entire system, and the Renewable Energy Fraction (REF) is 100%. The results clearly show that the scheme that is proposed in this study can achieve a smooth flow of power using the identical optimal configuration.

Anahtar Kelimeler

Energy management, Algorithms, Optimal planning, Solar energy, Fast sizing.

Kaynakça

• Ahmadi, S., Abdi, S., (2016). Application of the Hybrid Big Bang-Big Crunch Algorithm for Optimal Sizing of a Stand-Alone Hybrid PV/Wind/Battery System. Solar Energy, 134: 366–374.
• Alturki, F.A., Al-Shamma’a, A.A., Farh, H.M.H., AlSharabi, K., (2021). Optimal Sizing of Autonomous Hybrid Energy System Using Supply-Demand-Based Optimization Algorithm. International Journal of Energy Research, 45(1): 605–625.
• Bala, B.K., Siddique., S.A., (2009). Optimal Design of a PV-Diesel Hybrid System for Electrification of an Isolated Island-Sandwip in Bangladesh Using Genetic Algorithm. Energy for Sustainable Development, 13(3):137–142.
• Bukar, A.L., Tan, C.W., Lau, K.Y., (2019). Optimal Sizing of an Autonomous Photovoltaic/Wind/Battery /Diesel Generator Microgrid Using Grasshopper Optimization Algorithm. Solar Energy, 188: 685–696.
• Chen, L., Wang, S., Yousefi, N., (2021). An optimal arrangement for photovoltaic/diesel/battery management system applying Crow Search Algorithm: a case of Namib Desert. Int. J. Ambient Energy.
• Chen, Y., Wang, R., Ming, M., Cheng, S., Bao, Y., Zhang, W., Zhang, D., (2021). Constraint Multi-Objective Optimal Design of Hybrid Renewable Energy System Considering Load Characteristics. Complex & Intelligent Systems, 8: 803-817.
• Eriksson, E.L.V., Gray, E.M., (2019). Optimization of Renewable Hybrid Energy Systems–A Multi-Objective Approach. Renewable Energy, 133:971–999.
• Fathy, A., Kaaniche, K., Alanazi, T.M., (2020). 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.
• Geleta, D.K., Manshahia, M.S., (2020). Gravitational Search Algorithm-Based Optimization of Hybrid Wind and Solar Renewable Energy System. Computational Intelligence, 38: 1106–1132.
• Geleta, D.K., Manshahia, M.S., Vasant, P., Banik, A., (2020). Grey Wolf Optimizer for Optimal Sizing of Hybrid Wind and Solar Renewable Energy System. Computational Intelligence, 38: 1133-1162.
• Ghenai, C., Salameh, T., Merabet, A., (2020). Technico-Economic Analysis of off Grid Solar PV/Fuel Cell Energy System for Residential Community in Desert Region. International Journal of Hydrogen Energy, 45(20): 11460–11470.
• He, L., Zhang, S., Chen, Y., Ren, L., Li, J., (2018). Techno-Economic Potential of a Renewable Energy-Based Microgrid System for a Sustainable Large-Scale Residential Community in Beijing, China. Renewable and Sustainable Energy Reviews, 93: 631–641.
• Hermann, D.T., Talla Konchou, F.A., René, T., Donatien, N., (2022). Consideration of some optimization techniques to design a hybrid energy system for a building in Cameroon. Energy and Built Environment, 3(2): 233-249.
• Kaabeche, A., Belhamel, M., Ibtiouen, R., (2011). Techno-Economic Valuation and Optimization of Integrated Photovoltaic/Wind Energy Conversion System. Solar Energy, 85(10): 2407–2420.
• Mahesh, A., and Kanwarjit, S.S., (2019). Optimal Sizing of a Grid-Connected PV/Wind/Battery System Using Particle Swarm Optimization. Iranian Journal of Science and Technology - Transactions of Electrical Engineering, 43(1): 107–121.
• Mirjalili, S., Mirjalili, S.M., Lewis, A., (2014). Grey Wolf Optimizer. Advances in Engineering Software, 69:46–61.
• Mohammed, O.H., Amirat, Y., Benbouzid, M., (2019). Particle Swarm Optimization Of a Hybrid Wind/Tidal/PV/Battery Energy System. Application To a Remote Area In Bretagne, France. Energy Procedia, 162:87–96.
• Mokhtara, C., Negrou, B., Settou, N., Settou, B., Samy, M.M., (2021). 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: 1-18.
• Parrado, C., Girard, A., Simon, F., Fuentealba, E., (2016). 2050 LCOE (Levelized Cost of Energy) Projection for a Hybrid PV (Photovoltaic)-CSP (Concentrated Solar Power) Plant in the Atacama Desert, Chile. Energy, 94: 422–430.
• Ramli, M.A.M., Bouchekara, H.R.E.H., Alghamdi, A.S., (2018). Optimal Sizing of PV/Wind/Diesel Hybrid Microgrid System Using Multi-Objective Self-Adaptive Differential Evolution Algorithm. Renewable Energy, 121: 400–411.
• Roslan, M.F., Hannan, M.A., Ker, P.J., Begum, R.A., Indra Mahlia, T.M., Dong, Z.Y., (2021). Scheduling Controller for Microgrids Energy Management System Using Optimization Algorithm in Achieving Cost Saving and Emission Reduction. Applied Energy, 292: 1-16.
• Saheb-Koussa, D., Koussa, M., (2016). GHGs (Greenhouse Gases) Emission and Economic Analysis of a GCRES (Grid-Connected Renewable Energy System) in the Arid Region, Algeria. Energy, 102: 216–230.
• Shivaie, M., Mokhayeri, M., Kiani-Moghaddam, M., Ashouri-Zadeh, A., (2019). A Reliability-Constrained Cost-Effective Model for Optimal Sizing of an Autonomous Hybrid Solar/Wind/Diesel/Battery Energy System by a Modified Discrete Bat Search Algorithm. Solar Energy, 189: 344–356.
• Singh, P., Pandit M., Srivastava L., (2020). Comparison of Traditional and Swarm Intelligence Based Techniques for Optimization of Hybrid Renewable Energy System. Renewable Energy Focus, 35: 1–9.
• Talla Konchou, F.A., Temene, H.D., Tchinda R., Njomo D., (2021). Techno-Economic and Environmental Design of an Optimal Hybrid Energy System for a Community Multimedia Centre in Cameroon. SN Applied Sciences, 3(1): 1-12.
• Voloshin, R.A., Rodionova, M.V., Zharmukhamedov, S.K., Veziroglu, T.N., Allakhverdiev, S.I., (2016). Review: Biofuel Production from Plant and Algal Biomass. International Journal of Hydrogen Energy, 41(39): 17257–17273.
• Zhu, W., Guo, J., Zhao, G., (2021). Multi-objective sizing optimization of hybrid renewable energy microgrid in a stand-alone marine context. Electronics, 10:1–24.