Research Article
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Determination of Fair Usage Rate and Optimization for a Site Houses Photovoltaic-Battery Energy Source

Year 2022, Volume: 5 Issue: 1, 34 - 46, 30.06.2022

Abstract

With this study, a study had been carried out to meet part of the total electricity need in a site consisting of 4 houses by the photovoltaic-battery (PV-BT) system. Partial energy to be covered by the PV-BT system was aimed to be distributed equally among these 4 houses. Standard deviation method was used for fair distribution. Standard deviation calculations were made with the conditional flow algorithm (CFA), random algorithm (RA) and excel solver (ES). Optimization studies were carried out according to this standard deviation value. CFA and particle swarm optimization (PSO) algorithms were used for optimization. At the end of the study, the minimum standard deviation value was calculated as 0.219779. Fair usage percentages were calculated as 1.1061%, 9.1814%, 32.3474% and 57.3650% for the minimum standard deviation for each house, respectively. According to the minimum standard deviation value, the optimum result was obtained with CFA.

References

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  • Hemeida, A.M., El-Ahmar, M.H., El-Sayed, A.M., Hasanien, H.M., Alkhalaf, S., Esmail, M.F.C. and Senjyu, T. (2020). Optimum design of hybrid wind/PV energy system for remote area. Ain Shams Engineering Journal, 11:1, 11-23.
  • Jamshidi, M. and Askarzadeh, A. (2019). 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.
  • Junior, F.E.F. and Yen, G.G. (2019). Particle Swarm Optimization of Deep Neural Networks Architectures for Image Classification. Swarm and Evolutionary Computation, 49, 62-74.
  • Kaabeche, A. and Bakelli, Y. (2019). Renewable hybrid system size optimization considering various electrochemical energy storage Technologies. Energy Conversion and Management, 193, 162-175.
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  • Mohamed, M.A., Eltamaly, A.M. and Alolah,A.I. (2017). Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems. Renewable and Sustainable Energy Reviews, 77, 515-524.
  • Photovoltaic panel price, Retrieved from: https://www.terasolarsatis.com/200w-polikristal-fotovoltaik-panel, (Accessed Date: 12 April 2020).
  • Population of Malatya province, Retrieved from: https://biruni.tuik.gov.tr/medas/?kn=95&locale=tr, 2020, (Accessed Date:10 March 2020)
  • Precon, Pakistan Residential Electricity Consumption Dataset, Retrieved from: https://opendata.com.pk/dataset/precon-pakistan-residential-electricity-consumption-dataset, (Accessed Date: 30 March 2020).
  • Shamshirband, S., Mosavi, A. and Rabczuk, T. (2020). Particle swarm optimization model to predict scour depth around a bridge pier. Frontiers of Structural and Civil Engineering, 1-12.
  • Sobek, W. (2018). Building as renewable power plants: Active houses for the electric City, Urban Energy Transition (Second Edition). Renewable Strategies for Cities and Regions, 131-138.
  • Standard Deviation, Retrieved from: https://acikders.ankara.edu.tr/pluginfile.php/1379/mod_resource/content/2/B6_Merkezden%20Da%C4%9F%C4%B1lma%20%C3%96l%C3%A7%C3%BCleri.pdf, (Accessed Date: 16 May 2020).
  • Turkish State, Meteorological Service, Solar radiation data of Malatya. Retrieved from: www.mgm.gov.tr, (Accessed Date: 30 June 2012).
  • Yang, H., Zhou, W., Lu, L. and Fang, Z. (2008). Optimal sizing method for stand-alone hybrid solar–wind system with LPSP technology by using genetic algorithm. Solar Energy, 82, 354–367.
  • Yi, L. (2020). Energy optimization potential for interconnected buildings in a new urban development project. Master of Science Thesis TRITA-ITM-EX 2020:4, KTH Industrial Engineering and Management, Sustainable Energy Engineering.
  • Zhang, W., Maleki, A., Rosen, M.A. and Liu, J. (2019). Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm. Energy Conversion and Management, 180, 609-621.
  • Zhang, W., Maleki, A., Rosen, M.A. and Liu, J. (2018). Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage. Energy, 163, 191-207.
Year 2022, Volume: 5 Issue: 1, 34 - 46, 30.06.2022

Abstract

References

  • Al-falahi, M.D.A., Jayasinghe, S.D.G. and Enshaei, H. (2017). A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system. Energy Conversion and Management, 143, 252-274.
  • Al-Ghussain, L., Samu, R., Taylan, O. and Fahrioglu, M. (2020). Sizing renewable energy systems with energy storage systems in microgrids for maximum cost-efficient utilization of renewable energy resources. Sustainable Cities and Society, 55, 102059.
  • Astaneh, M., Roshandel, R., Dufo-López, R. and Bernal-Agustín, J.L. (2018). A novel framework for optimization of size and control strategy of lithium-ion battery based off-grid renewable energy systems. Energy Conversion and Management, 175, 99-111.
  • Baran, B. (2012). Cost optimization of solar - wind hybrid systems, Inonu University Electrical and Electronic Engineering Department. Master of Science Thesis.
  • Battery price, Retrieved from: https://www.epttavm.com/item/62578015_12v-100-ah-mutlu-solar-energy-aku-2019-yeni-urun, 2020, (Accessed Date: 12 April 2020)
  • Bukar, A.L. and Tan, C.W. (2019). A review on stand-alone photovoltaic-wind energy system with fuel cell: System optimization and energy management strategy. Journal of Cleaner Production., 221, 73-88.
  • Bukar, A.L., Tan, C.W. and Lau, K.Y. (2019). Optimal sizing of an autonomous photovoltaic/wind/battery/diesel generator microgrid using grasshopper optimization algorithm. Solar Energy, 188, 685-696.
  • Chauhan, A. and Saini, R.P. (2017). Size optimization and demand response of a stand-alone integrated renewable energy system. Energy, 124, 59-73.
  • Engin, M. (2010). Solar-Wind Hybrid Energy Generation System Design for Bornova (Bornova İçin Güneş-Rüzgar Hibrid Enerji Üretim Sistemi Tasarımı). Soma Vocational School Technical Sciences Journal, 2:13, 11-20.
  • Excel Solver, Retrieved from: https://support.microsoft.com/tr-tr/office/%C3%A7%C3%B6z%C3%BCc%C3%BC-y%C3%BC-kullanarak-bir-sorunu-tan%C4%B1mlama-ve-%C3%A7%C3%B6zme-5d1a388f-079d-43ac-a7eb-f63e45925040, (Accessed Date: 22 May 2020).
  • Fetanat, A. and Khorasaninejad, E. (2015). Size optimization for hybrid photovoltaic–wind energy system using ant colony optimization for continuous domains based integer programming. Applied Soft Computing, 31, 196-209.
  • Garson, S. What is a Load Profile and why is it Important?. Retrieved from: http://bettercostcontrol.com/what-is-a-load-profile-andwhy-is-it-important, (Accessed Date: 27 July 2020).
  • Ghaffari, A. (2020). Design optimization of a hybrid system subject to reliability level and renewable energy penetration. Energy, 193, 116754.
  • Hemeida, A.M., El-Ahmar, M.H., El-Sayed, A.M., Hasanien, H.M., Alkhalaf, S., Esmail, M.F.C. and Senjyu, T. (2020). Optimum design of hybrid wind/PV energy system for remote area. Ain Shams Engineering Journal, 11:1, 11-23.
  • Jamshidi, M. and Askarzadeh, A. (2019). 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.
  • Junior, F.E.F. and Yen, G.G. (2019). Particle Swarm Optimization of Deep Neural Networks Architectures for Image Classification. Swarm and Evolutionary Computation, 49, 62-74.
  • Kaabeche, A. and Bakelli, Y. (2019). Renewable hybrid system size optimization considering various electrochemical energy storage Technologies. Energy Conversion and Management, 193, 162-175.
  • Kennedy, J. and Eberhart, R.C. (2001). Swarm Intelligence. Academic Press, San Diego, CA.
  • Kerdphol, T., Fuji, K., Mitani, Y., Watanabe, M. and Qudaih, Y. (2016). Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids. International Journal of Electrical Power&Energy Systems, 81, October, 32-39.
  • Mahmoud, T.S., Ahmed, B.S. and Hassan, M.Y. (2019). The role of intelligent generation control algorithms in optimizing battery energy storage systems size in microgrids: A case study from Western Australia. Energy Conversion and Management, 196, 1335-1352.
  • Makhdoomi, S. and Askarzadeh, A. (2020). Optimizing operation of a photovoltaic/diesel generator hybrid energy system with pumped hydro storage by a modified crow search algorithm. Journal of Energy Storage, 27, 101040.
  • Mehrabankhomartash, M., Rayati, M., Sheikhi, A. and Ranjbar, A.M. (2017). Practical battery size optimization of a PV system by considering individual customer damage function. Renewable and Sustainable Energy Reviews, 67, 36-50.
  • Mohamed, M.A., Eltamaly, A.M. and Alolah,A.I. (2017). Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems. Renewable and Sustainable Energy Reviews, 77, 515-524.
  • Photovoltaic panel price, Retrieved from: https://www.terasolarsatis.com/200w-polikristal-fotovoltaik-panel, (Accessed Date: 12 April 2020).
  • Population of Malatya province, Retrieved from: https://biruni.tuik.gov.tr/medas/?kn=95&locale=tr, 2020, (Accessed Date:10 March 2020)
  • Precon, Pakistan Residential Electricity Consumption Dataset, Retrieved from: https://opendata.com.pk/dataset/precon-pakistan-residential-electricity-consumption-dataset, (Accessed Date: 30 March 2020).
  • Shamshirband, S., Mosavi, A. and Rabczuk, T. (2020). Particle swarm optimization model to predict scour depth around a bridge pier. Frontiers of Structural and Civil Engineering, 1-12.
  • Sobek, W. (2018). Building as renewable power plants: Active houses for the electric City, Urban Energy Transition (Second Edition). Renewable Strategies for Cities and Regions, 131-138.
  • Standard Deviation, Retrieved from: https://acikders.ankara.edu.tr/pluginfile.php/1379/mod_resource/content/2/B6_Merkezden%20Da%C4%9F%C4%B1lma%20%C3%96l%C3%A7%C3%BCleri.pdf, (Accessed Date: 16 May 2020).
  • Turkish State, Meteorological Service, Solar radiation data of Malatya. Retrieved from: www.mgm.gov.tr, (Accessed Date: 30 June 2012).
  • Yang, H., Zhou, W., Lu, L. and Fang, Z. (2008). Optimal sizing method for stand-alone hybrid solar–wind system with LPSP technology by using genetic algorithm. Solar Energy, 82, 354–367.
  • Yi, L. (2020). Energy optimization potential for interconnected buildings in a new urban development project. Master of Science Thesis TRITA-ITM-EX 2020:4, KTH Industrial Engineering and Management, Sustainable Energy Engineering.
  • Zhang, W., Maleki, A., Rosen, M.A. and Liu, J. (2019). Sizing a stand-alone solar-wind-hydrogen energy system using weather forecasting and a hybrid search optimization algorithm. Energy Conversion and Management, 180, 609-621.
  • Zhang, W., Maleki, A., Rosen, M.A. and Liu, J. (2018). Optimization with a simulated annealing algorithm of a hybrid system for renewable energy including battery and hydrogen storage. Energy, 163, 191-207.
There are 34 citations in total.

Details

Primary Language English
Journal Section Research Papers
Authors

Burhan Baran 0000-0001-6394-412X

Publication Date June 30, 2022
Submission Date December 30, 2021
Acceptance Date March 12, 2022
Published in Issue Year 2022 Volume: 5 Issue: 1

Cite

APA Baran, B. (2022). Determination of Fair Usage Rate and Optimization for a Site Houses Photovoltaic-Battery Energy Source. Journal of Investigations on Engineering and Technology, 5(1), 34-46.