Rize İli için Bilgisayar Kontrollü Güneş Evi Modelinin Enerji Yönetimi ve Ölçümü

Year 2020, Volume: 10 Issue: 2, 404 - 414, 15.04.2020

Mustafa Ergin Şahin

https://doi.org/10.17714/gumusfenbil.544087

Abstract

Türkiye'nin Rize şehri, Doğu Karadeniz bölgesinde bulunmakta ve ormanlarla ve yüksek dağlarla kaplıdır. Engebeli arazi, elektriğin uzak yerlere dağıtımını önler. Bu nedenle plato yaşam ve turizm hizmetleri bazı alanlarla sınırlıdır. Buna bağlı olarak, bazı dağlık alanlar bölgede hala elektrik kullanamamaktadır ve yenilenebilir enerji kaynaklarının gereksinimleri her geçen gün artmaktadır. Bu çalışmada güneş paneli içeren bir güneş evi modeli tasarlanmış ve bilgisayar kontrolü ile desteklenmiştir. İlave olarak sistemin gerçek bir evde kullanılması için gerekli hesaplamalar yapılmıştır. Bölgesel meteorolojik verilerde bu hesaplama için dikkate alınmıştır. Yine güneş panelinden ve aküye depolanan enerji hesaplanmıştır. Visual Basic programı LPT paralel portu ile güneş evi modeli arasındaki haberleşmeyi sağlamak ve temel ve özel uygulamalar için kullanılır. Yazılım enerjiyi daha verimli kullanmak için akıllı bir denetim algoritması sağlar. Ölçüm sonuçları Rize ilinin enerji potansiyelinin sistem verimi, uygulanabilirliği ve tekrarlanabilirliği yönünden uygun olduğunu göstermiştir.

Keywords

Paralel Port ile Bilgisayar Kontrolü, Enerji Depolama, Enerji Ölçümü ve Yönetimi, Fotovoltaik Güneş Evi Modeli

Energy Management and Measurement of Computer Controlled Solar House Model for Rize City

Abstract

The Rize city of Turkey is located in the East Black Sea region and covered with forests and high mountains. The hilly terrain prevents the distribution of electricity to remote locations. Therefore, plateau living and tourism services are restricted to certain areas. Depend on, some mountain places still could not use electricity in the region and the requirements of renewable energy sources are increasing every past day. In this study, a solar house model that contains a solar cell panel was designed and supported with computer control. Also, necessary calculations were performed for the system enlarged to use in residential. Regional meteorological data were taken into account for these calculations. Also, the energy obtained from the photovoltaic panel and stored in the battery was measured. Visual Basic software was used to provide communication between the line printer (parallel port) and the solar house model device control unit for basic and special applications. The software supplies a management algorithm to use energy more efficiently.  Measurements showed that the solar energy potential of Rize city is competitive in terms of system efficiency, applicability, and repeatability.

Keywords

Computer Control with a Parallel Port, Energy Storage, Energy Management and Measurement, Photovoltaic Solar House Model

References

• Ahmad, G. E., 2002. Photovoltaic-Powered Rural Zone Family House in Egypt. Renewable Energy, 26(3) 379-390.
• Aksungur, K. M., Kurban, M., and Filik, Ü.B., 2013. Türkiye’nin Farklı Bölgelerindeki Güneş Işınım Verilerinin Analizi ve Değerlendirilmesi. Energy Efficiency and Quality Symposium, Turkey.
• Altaş, I. H., 1999. Photovoltaic solar cells: Practices. 3E (Energy, Electric, Electro-mechanics) Magazine Journal, 60, 26-29.
• Axelson, J., 2000. Parallel Port Complete, Bileşim Publishing, İstanbul.
• Baldauf, A., 2015, May. A Smart Home Demand-Side Management System Considering Solar Photovoltaic Generation. In 2015 5th International Youth Conference on Energy (IYCE) (pp. 1-5).
• Bingöl, E., 2012. Device Control with Computer, Graduate Project, RTE University.
• Bojic, M., Parvedy, A. P., Miranville, F., Bigot, D., Cvetković, D., Djordjević, S., & Nikolić, D., 2013, Photovoltaic Electricity Production in A Residential House On Réunion. Journal of Energy in Southern Africa, 24(2), 50-56.
• Bradley, J.C., and Anita, C. M., 2003. Programming in Visual Basic, Net. Boston, McGraw-Hill.
• Ceylan, M., 2012. Elektrik Enerji Sanatralleri ve Elektrik Enerjisi İletimi ve Dağıtımı, Seçkin Yayıncılık, Ankara, 145-147.
• Chekired, F., Mahrane, A., Samara, Z., Chikh, M., Guenounou, A., & Meflah, A. 2017. Fuzzy Logic Energy Manage-ment for A Photovoltaic Solar Home. Energy Procedia, 134, 723-730.
• Chen, Z., and Shong-Iee, I.S., 2016. The Joint Bargaining Coordination in A Photovoltaic Supply Chain. Journal of Renewable and Sustainable Energy, 8(3), 035904.
• Ciabattoni, L., Ferracuti, F., Grisostomi, M., Ippoliti, G., & Longhi, S., 2015. Fuzzy Logic Based Economical Analysis of Photovoltaic Energy Management. Neurocomputing, 170, 296-305.
• Cucchiella, F., D’adamo, I., Gastaldi, M., & Koh, S. L., 2012. Renewable Energy Options for Buildings: Performance Evaluations of Integrated Photovoltaic Systems. Energy and Buildings, 55, 208-217.
• Cora, A., Özkop, E., 2008. Test ve Ölçüm Cihazlarının Bilgisayar İle Haberleşmesini Sağlayan İletişim Bağlantıları. 3E (Energy, Electric, Electro-mechanics) Magazine Journal, 165.
• Eroğlu, Ş., 2012. Analog Digital Converter Design, Graduate Project, RTE University.
• Fıratoğlu, Z. A, Yeşilata, B., 2009. Dinamik Çevre Koşullarının Fotovoltaik Destekli Su Pompası Sistemi Üzerindeki Etkilerinin Araştırılması. Engineer and Machinery Journal, 46/544.
• Firdaus, M-S. et al., 2011. An Evaluation of the Installation of Solar Photovoltaic in Residential Houses in Malaysia: Past, Present, And Future. Energy Policy, 39(12), 7975-7987. Güçlü, T., 2007. Paralell Port, Elektronik Hobi, Alfa Publishing, İstanbul.
• Guo, X-Q., 2011. Real-Time Measurement Method of Dc Injection for Transformerless PV Systems. Measure-ment, 44.6, 1136-1142.
• Iga, A., Yamaguchi, M., Yokoyama, S., Sueda, O., Yoshii, K., & Kaneko, T., 2004. Study of The Merit of Battery Combined Photovoltaic Generation System for Residential House (2). IEEJ Transactions on Power and Energy, 124, 1224-1230.
• Iwafune, Y., Ikegami, T., da Silva Fonseca Jr, J. G., Oozeki, T., & Ogimoto, K., 2015. Cooperative Home Energy Man-agement Using Batteries for A Photovoltaic System Considering the Diversity of Households. Energy conversion and management, 96, 322-329.
• Kamalapur, G. D., & Udaykumar, R. Y., 2011. Rural Electrification in India and Feasibility of Photovoltaic Solar Home Systems. International Journal of Electrical Power & Energy Systems, 33(3), 594-599.
• Kanamori, R., Takayuki, I., and Nobuyasu, M., 2011. Agent-Based Electrical Power Management Model for Houses Equipped with A Storage Battery and Photovoltaic Unit, 2011 IEEE International Conference on Service-Oriented Computing and Applications (SOCA).
• Kevin, J., 2000. PC Interfacing and Data Acquisition: Techniques for Measurement, Instrumentation, And Control, Oxford Press, Boston, 256.
• Kuwano, Y., 1998. Progress of A Photovoltaic System for Houses and Buildings in Japan. Renewable Energy. 15(1), 535-540.
• Lazzaroni, M. et. al., 2015. Models for Solar Radiation Prediction Based On Different Measurement Sites. Measure-ment, 63, 346-363.
• Official Statistics, 2018. General Directorate of Meteorology Republic of Turkey, URL-2: https://www.mgm.gov.tr/veridegerlendirme/il-ve-ilceler-istatistik.aspx?k=A&m=RIZE
• Ordóñez, J., Jadraque, E., Alegre, J., & Martínez, G., 2010, Analysis of The Photovoltaic Solar Energy Capacity of Residential Rooftops in Andalusia (Spain). Renewable and Sustainable Energy Reviews, 14(7), 2122-2130.
• Ozden, T., Kesler, S., & Okumus, H. I., 2018. A Fuzzy Logic Embedded Energy Management Software with A Multi-Agent System for A Stand-Alone PV Power Plant. International Journal of Environmental Science and Technol-ogy, 1-8.
• Öztürk, A. et. al., 2016. Experimental Performance Comparison of A 2-Axis Sun Tracking System with The Fixed Sys-tem Under the Climatic Conditions of Düzce, Turkey. Turkish Journal of Electrical Engineering & Computer Sci-ences, 24(5), 4383-4390.
• Philips Semiconductors, 2018. 74HC4052; 74HCT4052 Dual 4-Channel Analog Multiplexer. Demultiplexer, Data Sheet, URL_4: http://www.komponenten.es.aau.dk/fileadmin/komponenten/Data_Sheet/MOS-TTL/hc/74HC4052.pdf.pdf Sahin, M. E., and Nevruzov, V., 2010. Computer Controlled Solar House for Measurement Rize City Solar Energy Potential, NuRER Conference.
• Sahin, M. E., and Okumuş, H. İ., 2016. Physical Structure, Electrical Design, Mathematical Modeling and Simulation of Solar Cells and Modules. Turkish Journal of Electromechanics and Energy, 1(1), 8-12.
• Şahin, M. E., Okumuş, H. I., 2017. The Design Steps of Hybrid Energy System. Acta Physica Polonica A, 132, 1160-1164.
• Senpinar, A., 2018. Internet-/Arduino-Controlled PV Automatic Irrigation System for A Clean Environment. Interna-tional Journal of Environmental Science and Technology, 1-12.
• Shakeri, M., Shayestegan, M., Reza, S. S., Yahya, I., Bais, B., Akhtaruzzaman, M., ... & Amin, N. (2018). Implementa-tion of A Novel Home Energy Management System (HEMS) Architecture with Solar Photovoltaic System as Supplementary Source. Renewable energy, 125, 108-120.
• Sharaf, A. M., and Şahin, M. E., 2017. A Flexible PV-Powered Battery-Charging Scheme for Electric Vehicles. IETE Technical Review 34(2), 133-143.
• SMA Solar Technology, 2016. Planning Guidelines SMA Smart Home, Version 4.4, Germany, 10-11, URL_5: http://files.sma.de/dl/1353/SI-HoMan-PL-en-51.pdf
• Solar Energy Potential Map of Rize City (GEPA), 2018. Renewable Energy Directorate General of the Republic of Turkey, URL-1, http://www.yegm.gov.tr/MyCalculator/pages/53.aspx. Soulayman, S., Hammoud, M., 2016. Optimum Tilt Angle of Solar Collectors for Building Applications in The Mid-Latitude Zone. Energy Conversion Management, 124, 20-28.
• Sun, C., Sun, F., & Moura, S. J., 2016. Nonlinear Predictive Energy Management of Residential Buildings with Photo-voltaics & Batteries. Journal of Power Sources, 325, 723-731.
• Taylor, B. W., et al., 1998. Computer-Controlled Lighting System with Distributed Control Resources. U.S. Patent No.5, 769-727.
• Texas Instrument, 2018. ADC080x 8-Bit, µP-Compatible, Analog-to-Digital Converters. Data Sheet, URL_3: http://www.ti.com/lit/ds/symlink/adc0804-n.pdf
• Thanaa, F., Mona, N.E., and Mohsen T. E-H., 2006. Energy Flow and Management of a Hybrid Wind/PV/Fuel Cell Generation System. Energy Conversion and Management, 47(9), 1264-1280.
• Tohănean, D., 2018. Innovation Management and Artificial Intelligence: The Impact of Digitalization on Management Processes. Review, 81.
• Villa, G. G., 2018. The Influence of Different Innovation Enablers On the Adoption of Industry 4.0 By Smes and Large Companies: A Comparative Case Study.
• Wu, X., Hu, X., Moura, S., Yin, X., & Pickert, V., 2016. Stochastic Control of Smart Home Energy Management With Plug-In Electric Vehicle Battery Energy Storage And Photovoltaic Array. Journal of Power Sources, 333, 203-212.