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Kampüs Binaları için Enerji Planlama ve Optimizasyon Modeli: Erciyes Üniversitesi Örneği

Year 2024, Volume: 9 Issue: 2, 1095 - 1116, 26.12.2024
https://doi.org/10.30785/mbud.1559401

Abstract

Bu çalışma, üniversite kampüs binalarında artan enerji tüketimi ve iklim değişikliği gibi önemli sorunları, Erciyes Üniversitesi örneğinde ele almıştır. Üniversitelerin küçük şehirler gibi işlev gördüğü kabul edilerek, araştırmada, kampüs genelindeki tesislerde enerji verimliliğini artırmayı amaçlayan çok hedefli bir optimizasyon modeli geliştirilmiştir. GAMS yazılım paketi ve NEOS Server analiz hizmeti kullanılarak, çeşitli enerji tasarrufu sağlama önlemleri ve bu önlemlerin yatırım maliyetleri değerlendirilmektedir. Araştırmanın temel bulguları, enerji verimliliğine yapılacak stratejik yatırımların genel enerji performansında önemli iyileştirmelere yol açabileceğini göstermektedir. Örneğin, bina kabuğuna yapılacak yalıtım önlemleri, ısıtma enerji tüketimini %35 oranında azaltabilirken, verimli sıcak su sistemlerinin ve enerji tasarrufu sağlayan teknolojilerin kurulumu, potansiyel tasarrufları %75,5’e kadar çıkarabilmektedir. Modelin hesaplamaları, SCIP ve LINDO çözücüleri ile yapılmış ve sonuçlar yalnızca %0,2’lik bir hata payı ile yüksek doğruluk göstermektedir. Bu, modelin optimal çözümler üretme konusunda güvenilirliğini doğrulamaktadır. Araştırmadan elde edilen bulgular, üniversite karar vericileri için bir rehber sunarak, önemli birincil enerji tasarrufları sağlanabilecek önlemleri vurgulamaktadır.

References

  • Abdou, N., El Mghouchi, Y., Hamdaoui, S., El Asri, N. & Mouqallid, M. (2021). Multi-objective optimization of passive energy efficiency measures for net-zero energy building in Morocco. Building and Environment, 204, 108-141. https://doi.org/10.1016/j.buildenv.2021.108141
  • Ascione, F., Bianco, N., De Masi, R. F., Mauro, G. M. & Vanoli, G. P. (2017). Energy retrofit of educational buildings: Transient energy simulations, model calibration and multi-objective optimization towards nearly zero-energy performance. Energy and Buildings, 144, 303-319. https://doi.org/10.1016/j.enbuild.2017.03.056
  • Bayata, Ö. & Temiz, I. (2017). Developing a model and software for energy efficiency optimization in the building design process: A case study in Turkey. Turkish Journal of Electrical Engineering & Computer Sciences, 25, 4172-4186. https://doi.org/10.3906/elk-1612-13
  • Bellia, L., Borrelli, M., Ruggiero, S. & Vanoli, G. (2018). University building: energy diagnosis and refurbishment design with Cost-Optimal approach. Discussion about the effect of numerical modelling assumptions. Journal of Building Engineering, 18. https://doi.org/10.1016/j.jobe.2018.02.017
  • Benaddi, F. Z., Boukhattem, L., Ait Nouh, F., Cesar Tabares-Velasco, P. & Benhamou, B. (2023). Energy-saving potential assessment of a classroom building envelope through sensitivity analysis and multi- objective optimization under different climate types. Building Services Engineering Research and Technology, 44(3), 309-332. https://doi.org/10.1177/01436244231161944
  • Czyzyk, J., Mesnier, M. P. & More, J. J. (1998). The NEOS Server. IEEE Computational Science and Engineering, 5(3), 68-75. https://doi.org/10.1109/99.714603
  • Diakaki, C. & Grigoroudis, E. (2021). Improving energy efficiency in buildings using an interactive mathematical programming approach. Sustainability, 13(8).
  • Diakaki, C., Grigoroudis, E., Kabelis, N., Kolokotsa, D., Kalaitzakis, K. & Stavrakakis, G. (2010). A multi-objective decision model for the improvement of energy efficiency in buildings. Energy, 35(12), 5483- 5496. https://doi.org/10.1016/j.energy.2010.05.012
  • Google Earth. (2024). R&D Park Building of Erciyes University, Kayseri. Access Address (10.10.2024): https://earth.google.com/
  • Guerrieri, M., La Gennusa, M., Peri, G., Rizzo, G. & Scaccianoce, G. (2019). University campuses as small-scale models of cities: Quantitative assessment of a low carbon transition path. Renewable and Sustainable Energy Reviews, 113, 109263. https://doi.org/10.1016/j.rser.2019.109263
  • Gültekin, Y. S., Gültekin, P., Başaran, N. & Yılmaz Kaya, M. (2024). Measuring universities’ sustainability performance with using UI GreenMetric World Ranking: A case study of Düzce University [Üniversitelerin sürdürülebilirlik performansının UI GreenMetric Dünya Sıralaması kullanılarak ölçülmesi: Düzce Üniversitesi örneği]. Journal of Architectural Sciences and Applications, 9(1), 145-164. https://doi.org/10.30785/mbud.1403115
  • Han, Y., Zhou, X. & Luo, R. (2015). Analysis on campus energy consumption and energy saving measures in cold region of China. Procedia Engineering, 121, 801-808. https://doi.org/10.1016/j.proeng.2015.09.033
  • Hashempour, N., Taherkhani, R. & Mahdikhani, M. (2020). Energy performance optimization of existing buildings: A literature review. Sustainable Cities and Society, 54, 101967. https://doi.org/10.1016/j.scs.2019.101967
  • Karmellos, M., Kiprakis, A. & Mavrotas, G. (2015). A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies. Applied Energy, 139, 131- 150. https://doi.org/10.1016/j.apenergy.2014.11.023
  • Penna, P., Prada, A., Cappelletti, F. & Gasparella, A. (2015). Multi- objectives optimization of energy efficiency measures in existing buildings. Energy and Buildings, 95, 57-69. https://doi.org/10.1016/j.enbuild.2014.11.003
  • Rüşen, S. E., Topçu, M. A., Karanfil Celep, G., Çeltek, S. A. & Rüşen, A. (2018). Üniversite kampüs binaları için enerji etüdü: Örnek çalışma [Energy audit for campus buildings of university: A case study]. Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 33(2), 83- 92. https://doi.org/10.21605/cukurovaummfd.508904
  • Shi, Y. & Chen, P. (2024). Energy retrofitting of hospital buildings considering climate change: An approach integrating automated machine learning with NSGA-III for multi-objective optimization. Energy and Buildings, 319, 114571. https://doi.org/10.1016/j.enbuild.2024.114571
  • Vardopoulos, I., Santamouris, M., Zorpas, A. A., Barone, G., Italos, C. & Vassiliades, C. (2024). A comparative study on discrepancies in residential building energy performance certification in a mediterranean context. Buildings, 14(4), 1009. https://www.mdpi.com/2075-5309/14/4/1009
  • YÖK. (2024). Number of universities in Türkiye. Access Address (10.10.2024): https://istatistik.yok.gov.tr/

Energy Planning and Optimization Model for Campus Buildings: A Case Study of Erciyes University

Year 2024, Volume: 9 Issue: 2, 1095 - 1116, 26.12.2024
https://doi.org/10.30785/mbud.1559401

Abstract

This study addresses energy consumption and climate change challenges in university campus buildings, focusing on Erciyes University. The research develops a multi-objective optimization model using GAMS software and NEOS Server to enhance campus energy efficiency. The model evaluates various energy-saving measures and their investment costs. Findings indicate that building envelope insulation can reduce heating energy consumption by 35%, while efficient hot water systems and energy-saving technologies can achieve savings up to 75.5%. Model calculations using SCIP and LINDO solvers demonstrate high accuracy, with results differing by only 0.2%. This research provides valuable guidance for university decision-makers in implementing targeted interventions for significant primary energy savings.

Thanks

The article complies with national and international research and publication ethics. Ethics Committee approval was not required for the study. This study is a part of a doctoral thesis titled 'Energy Planning and Optimization Model for Campus Buildings and Transportation: A Case Study of Erciyes University' by Atabek Movlanov, a PhD student in the Department of Energy Systems Engineering at Erciyes University.

References

  • Abdou, N., El Mghouchi, Y., Hamdaoui, S., El Asri, N. & Mouqallid, M. (2021). Multi-objective optimization of passive energy efficiency measures for net-zero energy building in Morocco. Building and Environment, 204, 108-141. https://doi.org/10.1016/j.buildenv.2021.108141
  • Ascione, F., Bianco, N., De Masi, R. F., Mauro, G. M. & Vanoli, G. P. (2017). Energy retrofit of educational buildings: Transient energy simulations, model calibration and multi-objective optimization towards nearly zero-energy performance. Energy and Buildings, 144, 303-319. https://doi.org/10.1016/j.enbuild.2017.03.056
  • Bayata, Ö. & Temiz, I. (2017). Developing a model and software for energy efficiency optimization in the building design process: A case study in Turkey. Turkish Journal of Electrical Engineering & Computer Sciences, 25, 4172-4186. https://doi.org/10.3906/elk-1612-13
  • Bellia, L., Borrelli, M., Ruggiero, S. & Vanoli, G. (2018). University building: energy diagnosis and refurbishment design with Cost-Optimal approach. Discussion about the effect of numerical modelling assumptions. Journal of Building Engineering, 18. https://doi.org/10.1016/j.jobe.2018.02.017
  • Benaddi, F. Z., Boukhattem, L., Ait Nouh, F., Cesar Tabares-Velasco, P. & Benhamou, B. (2023). Energy-saving potential assessment of a classroom building envelope through sensitivity analysis and multi- objective optimization under different climate types. Building Services Engineering Research and Technology, 44(3), 309-332. https://doi.org/10.1177/01436244231161944
  • Czyzyk, J., Mesnier, M. P. & More, J. J. (1998). The NEOS Server. IEEE Computational Science and Engineering, 5(3), 68-75. https://doi.org/10.1109/99.714603
  • Diakaki, C. & Grigoroudis, E. (2021). Improving energy efficiency in buildings using an interactive mathematical programming approach. Sustainability, 13(8).
  • Diakaki, C., Grigoroudis, E., Kabelis, N., Kolokotsa, D., Kalaitzakis, K. & Stavrakakis, G. (2010). A multi-objective decision model for the improvement of energy efficiency in buildings. Energy, 35(12), 5483- 5496. https://doi.org/10.1016/j.energy.2010.05.012
  • Google Earth. (2024). R&D Park Building of Erciyes University, Kayseri. Access Address (10.10.2024): https://earth.google.com/
  • Guerrieri, M., La Gennusa, M., Peri, G., Rizzo, G. & Scaccianoce, G. (2019). University campuses as small-scale models of cities: Quantitative assessment of a low carbon transition path. Renewable and Sustainable Energy Reviews, 113, 109263. https://doi.org/10.1016/j.rser.2019.109263
  • Gültekin, Y. S., Gültekin, P., Başaran, N. & Yılmaz Kaya, M. (2024). Measuring universities’ sustainability performance with using UI GreenMetric World Ranking: A case study of Düzce University [Üniversitelerin sürdürülebilirlik performansının UI GreenMetric Dünya Sıralaması kullanılarak ölçülmesi: Düzce Üniversitesi örneği]. Journal of Architectural Sciences and Applications, 9(1), 145-164. https://doi.org/10.30785/mbud.1403115
  • Han, Y., Zhou, X. & Luo, R. (2015). Analysis on campus energy consumption and energy saving measures in cold region of China. Procedia Engineering, 121, 801-808. https://doi.org/10.1016/j.proeng.2015.09.033
  • Hashempour, N., Taherkhani, R. & Mahdikhani, M. (2020). Energy performance optimization of existing buildings: A literature review. Sustainable Cities and Society, 54, 101967. https://doi.org/10.1016/j.scs.2019.101967
  • Karmellos, M., Kiprakis, A. & Mavrotas, G. (2015). A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies. Applied Energy, 139, 131- 150. https://doi.org/10.1016/j.apenergy.2014.11.023
  • Penna, P., Prada, A., Cappelletti, F. & Gasparella, A. (2015). Multi- objectives optimization of energy efficiency measures in existing buildings. Energy and Buildings, 95, 57-69. https://doi.org/10.1016/j.enbuild.2014.11.003
  • Rüşen, S. E., Topçu, M. A., Karanfil Celep, G., Çeltek, S. A. & Rüşen, A. (2018). Üniversite kampüs binaları için enerji etüdü: Örnek çalışma [Energy audit for campus buildings of university: A case study]. Çukurova Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 33(2), 83- 92. https://doi.org/10.21605/cukurovaummfd.508904
  • Shi, Y. & Chen, P. (2024). Energy retrofitting of hospital buildings considering climate change: An approach integrating automated machine learning with NSGA-III for multi-objective optimization. Energy and Buildings, 319, 114571. https://doi.org/10.1016/j.enbuild.2024.114571
  • Vardopoulos, I., Santamouris, M., Zorpas, A. A., Barone, G., Italos, C. & Vassiliades, C. (2024). A comparative study on discrepancies in residential building energy performance certification in a mediterranean context. Buildings, 14(4), 1009. https://www.mdpi.com/2075-5309/14/4/1009
  • YÖK. (2024). Number of universities in Türkiye. Access Address (10.10.2024): https://istatistik.yok.gov.tr/
There are 19 citations in total.

Details

Primary Language English
Subjects Ecology, Sustainability and Energy
Journal Section Research Articles
Authors

Atabek Movlyanov 0000-0001-6676-5231

Beyza Akyol 0000-0002-5933-5724

Saltuk Buğra Selçuklu 0000-0002-9295-3866

Publication Date December 26, 2024
Submission Date October 1, 2024
Acceptance Date December 15, 2024
Published in Issue Year 2024 Volume: 9 Issue: 2

Cite

APA Movlyanov, A., Akyol, B., & Selçuklu, S. B. (2024). Energy Planning and Optimization Model for Campus Buildings: A Case Study of Erciyes University. Journal of Architectural Sciences and Applications, 9(2), 1095-1116. https://doi.org/10.30785/mbud.1559401