OPTIMAL OPERATION MODEL OF HYBRID POWER SYSTEMS FOR HVAC LOADS AND DEMAND RESPONSE APPLICATIONS FOR HVAC LOADS OF AN HOSPITAL

Öz

In this study, optimal power management strategy to make optimal operation of the alternative sources has been considered to meet the load demand of heating, ventilations and air conditioning (HVAC) units for public institutions, hospitals, schools, etc. A hybrid power system consisting of wind türbine (WT), photovoltaics (PV) and battery has been proposed. The system is modelled to be used in an optimal demand response application. Moreover, the grid has been added to the hybrid power system due to the intermittent generation characteristics of alternative power sources. The objectives defined by the optimization problem are the operation of the alternative power sources at maximum rate and primarily meeting the HVAC load demand by the relevant sources. The resulting mixed-integer linear programming model is tested in GAMS v.24.1.3 platform using the solver CPLEX v.12.

Anahtar Kelimeler

• Hybrid Power System
• Demand Response
• Optimization
• WT/PV
• HVAC Loads

HİBRİT GÜÇ SİSTEMİ İLE İKLİMLENDİRME YÜKLERİNİN OPTİMAL İŞLETİM MODELİ VE HASTANE İKLİMLENDİRME YÜKLERİ İÇİN TALEP CEVABI UYGULAMASI

Öz

Bu çalışmada, kamu kuruluşları, hastane, okul vb. gibi kurumların iklimlendirme cihazlarının yük talebinin karşılanmasında alternatif enerji kaynaklarından optimal olarak yararlanma stratejisi ele alınmıştır. İklimlendirme yüklerinin karşılanmasında rüzgar türbini (RT), güneş pili (GP) ve batarya (Bat) ile teşkil edilen hibrit güç sistemi önerilmiştir. Hibrit güç sistemi optimal talep cevabı uygulamasında kullanılmasına imkan verecek şekilde modellenmiştir. Ayrıca, hibrit kaynakların kesintili üretim karakteristikleri gereği hibrit güç sistemine şebeke gücü de ilave edilmiştir. Optimizasyon probleminde alternatif enerji kaynaklarının maksimum kapasitede kullanımı ve ilgili kaynakların öncelikli olarak iklimlendirme yüklerinin talebine cevap verecek şekilde kullanımı amaç olarak belirlenmiştir. Elde edilen karışık tamsayı lineer programlama modeli GAMS v.24.1.3 ortamında CPLEX v.12 çözücüsü ile test edilmiştir. Kış ve yaz koşulları dikkate alınarak optimal işletim modelinin benzetim çalışmaları yapılmıştır ve ilgili sonuçlar sunulmuştur.

Anahtar Kelimeler

• Hibrit Güç Sistemi
• Talep Cevabı
• Optimizasyon
• RT/GP
• İklimlendirme Yükleri.

Kaynakça

1. Arabul, F.K., Arabul, A.Y., Kumru, C.F. ve Boynuegri, A.R. Providing energy management of a fuel cell–battery–wind turbine–solar panel hybrid off grid smart home system. International Journal of Hydrogen Energy 42 (2017): 26906-26913.
2. Binalarda Enerji Performansı Yönetmeliği, 2008 Türkiye Cumhuriyeti Çevre ve Şehircilik Bakanlığı, Resmi Gazete, Sayı: 27075.
3. CPLEX 12 Solver Description. İnternet Erişim Adresi: http://www.gams.com/dd/docs/solvers/cplex.pdfg. (Ziyaret Tarihi: 10.07.2021)
4. Erdinc, O. Economic impacts of small-scale own generating and storage units, and electric vehicles under different demand response strategies for smart households. Applied Energy 126 (2014): 142-150.
5. Erdinc, O., Taşçıkaraoğlu, A., Paterakis, N.G., Eren Y. ve Catalao, J.P.S., 2017. End-User Comfort Oriented Day-Ahead Planning for Responsive Residential HVAC Demand Aggregation Considering Weather Forecasts, IEEE Transaction on Smart Grid, 8:362-372.
6. General Algebraic Modeling System. GAMS İnternet Erişim Adresi: http://www.gams.com. (Ziyaret Tarihi:10.07.2021)
7. Goddard, G., Klose J. ve Backhaus, S., 2014. Model Development and Identification for Fast Demand Response in Commercial HVAC Systems. IEEE Transactions on Smart Grid, 5(4), 2084-2092.
8. Hao, H., Lin,Y., Kowli, A.S., Barooah, P. ve Meyn S., 2014. Ancillary Service to the Grid through Control of Fans in Commercial Building HVAC Systems. IEEE Transactions on smart grid, 5(4), 2066-2074.

9. Ioan, B., Horia, B. ve Susana, O.P.T., 2015. Determination of the power generated by a wind turbine in constant wind and variable wind. 9th International Symposium on Advanced Topics in Electrical Engineering (ATEE), doi: 10.1109/ATEE.2015.7133919.
10. Mizuno, Y., Baba, T., Tanaka, Y., Kurokawa, F., Tanaka, M., Colak, İ., Matsui, N., 2018. A New Load Prediction Method and Management of Distributed Power System in Island Mode of a Large Hospital," 7th International Conference on Renewable Energy Research and Applications (ICRERA).
11. Photovoltaic Calculator. PVC İnternet Erişim Adresi: https://photovoltaic-software.com/principle-ressources/how-calculate-solar-energy-power-pv-systems. (Ziyaret Tarihi:01.06.2021)
12. Photovoltaic Geographical Information System European Union Science Hub. PVGIS İnternet Erişim Adresi: https://re.jrc.ec.europa.eu/pvg_tools/en/. (Ziyaret Tarihi:01.06.2021)
13. Prudenzi A., Caracciolo V. ve Silvestri A., 2008. Identification of electrical load typical patterns in hospital for supporting energy management strategies, IFHE.
14. Prudenzi A., Caracciolo V. ve Silvestri A., 2009. Electrical load analysis in a hospital complex. IEEE Bucharest PowerTech, 2009, doi: 10.1109/PTC.2009.5281797.
15. Shen, C., Zhao, K., Ge, J., ve Zhou, Q., 2019. Analysis of Building Energy Consumption in a Hospital in the Hot Summer and Cold Winter Area. Energy Procedia, 158, 3735-3740.
16. Sun, B., Luh, P. B., Jia, Q., Jiang, Z., Wang F., ve Song, C. 2013. Building Energy Management: Integrated Control of Active and Passive Heating, Cooling, Lighting, Shading, and Ventilation Systems, IEEE Transactions on Automation Science and Engineering, 10(3), 588-602.
17. Tahboub, R., Ibrik, I., Tamimi, M., 2011. The Potential and Feasibility of Solar and Wind Energy Applications in Al-Ahli Hospital, International Energy Conference in Palestine.
18. Talebi, A., Hatami, A., 2020. Online fuzzy control of HVAC systems considering demand response and users’ comfort. Energy Sources, Part B: Economics, Planning, and Policy 15(7), 403-422.
19. Tanwar, M.P., Agarwal, A. ve Mishra, A., 2018. Power Output Enhancement of Solar Panels by Field Area Optimization, International Conference on Computing, Power and Communication Technologies (GUCON), doi: 10.1109/GUCON.2018.8674954.
20. Tizgui, I., Bouzahir, H., Guezar F.E., ve Benaid, B., 2017. Wind Speed Extrapolation and Wind Power Assessment at Different Heights, International Conference on Electrical and Information Technologies (ICEIT), doi: 10.1109/EITech.2017.8255215.
21. Xu, Z., Jia, Q. ve Guan, X., 2015. Supply Demand Coordination for Building Energy Saving: Explore the Soft Comfort, IEEE Transactions on Automation Science and Engineering, 12(2), 656-665.
22. Yuan, J., Xiao, Z., Chen, X., Lu, Z. ve Gang, W., 2021. A Temperature & Humidity Setback Demand Response Strategy for HVAC Systems. Sustainable Cities and Society, 75 (2021): 103393.