Research Article
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Year 2023, Volume: 8 Issue: 1, 12 - 24, 29.12.2023
https://doi.org/10.55088/ijesg.1335769

Abstract

References

  • D. Burillo, M. Chester, and B. Ruddell, “Electric Grid Vulnerabilities to Rising Air Temperatures in Arizona,” Procedia Engineering, vol. 145, pp. 1346–1353, 2016 doi:10.1016/j.proeng.2016.04.173.
  • J. Farfan and C. Breyer, “Aging of European power plant infrastructure as an opportunity to evolve towards sustainability,” International Journal of Hydrogen Energy, vol. 42, no. 28, pp. 18081–18091, Jul. 2017, doi: 10.1016/j.ijhydene.2016.12.138.
  • O. Majeed Butt, M. Zulqarnain, and T. Majeed Butt, “Recent advancement in smart grid technology: Future prospects in the electrical power network,” Ain Shams Engineering Journal. Vol. 12(1), pp.687-695, Jul. 07, 2020, doi: 10.1016/j.asej.2020.05.004.
  • “Global Electricity Review 2020 - Ember.” https://ember-climate.org/project/global-power-2020/ (accessed Sep. 25, 2020).
  • P. Carvalho, “Smart metering deployment in Brazil,” Energy Procedia, vol. 83, pp. 360–369, Dec. 2015, doi: 10.1016/j.egypro.2015.12.211.
  • S. Alpanda and A. Peralta-Alva, “Oil crisis, energy-saving technological change and the stock market crash of 1973-74,” Review of Economic Dynamics, vol. 13, no. 4, pp. 824–842, Oct. 2010, doi: 10.1016/j.red.2010.04.003.
  • S. Rajamand, “Effect of demand response program of loads in cost optimization of microgrid considering uncertain parameters in PV/WT, market price and load demand,” Energy, vol. 194, p. 116917, Mar. 2020, doi: 10.1016/j.energy.2020.116917.
  • “Electricity Information 2019 – Analysis - IEA.” https://www.iea.org/reports/electricity-information-overview (accessed Sep. 25, 2020).
  • C. Camarasa, C. Nägeli, Y. Ostermeyer, M. Klippel, and S. Botzler, “Diffusion of energy efficiency technologies in European residential buildings: A bibliometric analysis,” Energy and Buildings, vol. 202. Elsevier Ltd, p. 109339, Nov. 01, 2019, doi: 10.1016/j.enbuild.2019.109339.
  • E. lo Cascio, Z. Ma, D. Borelli, and C. Schenone, “Residential Building Retrofit through Numerical Simulation: A Case Study,” Energy Procedia, vol. 111, pp. 91–100, Mar. 2017, doi: 10.1016/j.egypro.2017.03.011.
  • A. Synnefa et al., “Transformation through Renovation: An Energy Efficient Retrofit of an Apartment Building in Athens,” Procedia Engineering, vol. 180, pp. 1003–1014, Jan. 2017, doi: 10.1016/j.proeng.2017.04.260.
  • S. N. J. Al-Saadi, J. Al-Hajri, and M. A. Sayari, “Energy-Efficient Retrofitting Strategies for Residential Buildings in hot climate of Oman,” Energy Procediavol. 142, pp. 2009–2014, Dec. 2017, doi: 10.1016/j.egypro.2017.12.403.
  • S. M. Hosseini, R. Carli, and M. Dotoli, “Model Predictive Control for Real-Time Residential Energy Scheduling under Uncertainties,” in Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, pp. 1386–1391, Jan. 2019, doi:10.1109/SMC.2018.00242.
  • R. Halvgaard, L. Vandenberghe, N. K. Poulsen, H. Madsen, and J. B. Jørgensen, “Distributed Model Predictive Control for Smart Energy Systems,” IEEE Transactions on Smart Grid, vol. 7, no. 3, pp. 1675–1682, May 2016, doi: 10.1109/TSG.2016.2526077.
  • D. Dongol, T. Feldmann, and E. Bollin, “A model predictive control based peak shaving application for a grid connected household with photovoltaic and battery storage,” in SMARTGREENS 2018 - Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems, vol. 2018-March, pp. 54–63, 2018 doi: 10.5220/0006685300540063.
  • S. Seal, B. Boulet, and V. R. Dehkordi, “Centralized model predictive control strategy for thermal comfort and residential energy management,” Energy, vol. 212, p. 118456, Dec. 2020, doi: 10.1016/j.energy.2020.118456.
  • R. Halvgaard, L. Vandenberghe, N. K. Poulsen, H. Madsen, and J. B. Jørgensen, “Distributed Model Predictive Control for Smart Energy Systems,” IEEE Transactions on Smart Grid, vol. 7, no. 3, pp. 1675–1682, May 2016, doi: 10.1109/TSG.2016.2526077.
  • H. M. Ruzbahani, A. Rahimnejad, and H. Karimipour, “Smart Households Demand Response Management with Micro Grid,” 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2019, pp. 1-5, doi:10.1109/ISGT.2019.8791595.
  • M. J. M. al Essa, “Home energy management of thermostatically controlled loads and photovoltaic-battery systems,” Energy, vol. 176, pp. 742–752, Jun. 2019, doi: 10.1016/j.energy.2019.04.041.
  • M. Shakeri et al., “An intelligent system architecture in home energy management systems (HEMS) for efficient demand response in smart grid,” Energy and Buildings, vol. 138, pp. 154–164, Mar. 2017, doi: 10.1016/j.enbuild.2016.12.026.
  • A. Parsa, T. A. Najafabadi, and F. R. Salmasi, “Implementation of smart optimal and automatic control of electrical home appliances (IoT),” in IEEE Proceedings 2017 Smart Grid Conference, SGC 2017, Mar. 2018, pp. 1–6, doi: 10.1109/SGC.2017.8308861.
  • H. M. Ruzbahani, A. Rahimnejad and H. Karimipour, "Smart Households Demand Response Management with Micro Grid," 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2019, pp. 1-5, doi: 10.1109/ISGT.2019.8791595.
  • K. Ma, G. Hu, and C. J. Spanos, “A cooperative demand response scheme using punishment mechanism and application to industrial refrigerated warehouses,” IEEE Transactions on Industrial Informatics, vol. 11, no. 6, pp. 1520–1531, Dec. 2015, doi: 10.1109/TII.2015.2431219.
  • A. Mahmood, A. R. Butt, U. Mussadiq, R. Nawaz, R. Zafar, and S. Razzaq, “Energy sharing and management for prosumers in smart grid with integration of storage system,” in ICSG 2017 - 5th International Istanbul Smart Grids and Cities Congress and Fair, Istanbul, Turkey, Jun. 2017, pp. 153–156, doi: 10.1109/SGCF.2017.7947623.
  • H. Turker and I. Colak, “Multiobjective optimization of Grid- Photovoltaic- Electric Vehicle Hybrid system in Smart Building with Vehicle-to-Grid (V2G) concept,” in 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018, pp. 1477–1482, doi: 10.1109/ICRERA.2018.8567002.
  • “HOME - www.soda-pro.com.” http://www.soda-pro.com/ (accessed Sep. 25, 2020).
  • “Photovoltaic Geographical Information System (PVGIS) | EU Science Hub.” https://ec.europa.eu/jrc/en/pvgis (accessed Sep. 25, 2020).
  • “Global Solar Atlas.” . [Online]. Available: https://globalsolaratlas.info/map?c=11.523088,8.4375,3 (accessed Sep. 25, 2020).
  • “Solar Panels | Tesla.” . [Online]. Available: https://www.tesla.com/solarpanels (accessed Sep. 25, 2020).
  • “Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States - Datasets - OpenEI DOE Open Data.” . [Online]. Available: https://openei.org/doe-opendata/dataset/commercial-and-residential-hourly-load-profiles-for-all-tmy3-locations-in-the-united-states (accessed Sep. 25, 2020).
  • “Electricity storage and renewables: Costs and markets to 2030,” /publications/2017/Oct/Electricity-storage-and-renewables-costs-and-markets, Accessed: Sep. 25, 2020. [Online]. Available: /publications/2017/Oct/Electricity-storage-and-renewables-costs-and-markets.
  • “Time of Use, TOU, Pricing Plans, TOU Pricing Plans | San Diego Gas & Electric.” . [Online]. Available: https://www.sdge.com/whenmatters (accessed Sep. 25, 2020).
  • X. Wu, X. Hu, Y. Teng, S. Qian, and R. Cheng, “Optimal integration of a hybrid solar-battery power source into smart home nanogrid with plug-in electric vehicle,” Journal of Power Sources, vol. 363, pp. 277–283, Sep. 2017, doi: 10.1016/j.jpowsour.2017.07.086.

Power Bill Optimization for Grid-tie Solar PV-Battery House

Year 2023, Volume: 8 Issue: 1, 12 - 24, 29.12.2023
https://doi.org/10.55088/ijesg.1335769

Abstract

This study focuses on the optimization of power bills for a house equipped with a grid-tie solar PV-battery system. Rather than adhering to conventional load scheduling practices or minimizing grid power usage at each time interval, a novel approach is adopted wherein the optimization is performed for the entire 24-hour period simultaneously. By directly incorporating time-of-use rates into the cost function, an absolute optimal solution is attained. The findings indicate that compared to single time step optimization, the proposed method results in a reduction of the power bill ranging from 6% to 10%, depending on load-generation variations. Furthermore, if the utility or government enforces the summer tariff consistently throughout the year, the savings escalate to a range of 15% to 22%. Introducing a more intelligent tariff structure can thus serve as an effective means to expedite the transition towards renewable energy by incentivizing individual investments in solar PV, battery systems, and smart home energy management.

References

  • D. Burillo, M. Chester, and B. Ruddell, “Electric Grid Vulnerabilities to Rising Air Temperatures in Arizona,” Procedia Engineering, vol. 145, pp. 1346–1353, 2016 doi:10.1016/j.proeng.2016.04.173.
  • J. Farfan and C. Breyer, “Aging of European power plant infrastructure as an opportunity to evolve towards sustainability,” International Journal of Hydrogen Energy, vol. 42, no. 28, pp. 18081–18091, Jul. 2017, doi: 10.1016/j.ijhydene.2016.12.138.
  • O. Majeed Butt, M. Zulqarnain, and T. Majeed Butt, “Recent advancement in smart grid technology: Future prospects in the electrical power network,” Ain Shams Engineering Journal. Vol. 12(1), pp.687-695, Jul. 07, 2020, doi: 10.1016/j.asej.2020.05.004.
  • “Global Electricity Review 2020 - Ember.” https://ember-climate.org/project/global-power-2020/ (accessed Sep. 25, 2020).
  • P. Carvalho, “Smart metering deployment in Brazil,” Energy Procedia, vol. 83, pp. 360–369, Dec. 2015, doi: 10.1016/j.egypro.2015.12.211.
  • S. Alpanda and A. Peralta-Alva, “Oil crisis, energy-saving technological change and the stock market crash of 1973-74,” Review of Economic Dynamics, vol. 13, no. 4, pp. 824–842, Oct. 2010, doi: 10.1016/j.red.2010.04.003.
  • S. Rajamand, “Effect of demand response program of loads in cost optimization of microgrid considering uncertain parameters in PV/WT, market price and load demand,” Energy, vol. 194, p. 116917, Mar. 2020, doi: 10.1016/j.energy.2020.116917.
  • “Electricity Information 2019 – Analysis - IEA.” https://www.iea.org/reports/electricity-information-overview (accessed Sep. 25, 2020).
  • C. Camarasa, C. Nägeli, Y. Ostermeyer, M. Klippel, and S. Botzler, “Diffusion of energy efficiency technologies in European residential buildings: A bibliometric analysis,” Energy and Buildings, vol. 202. Elsevier Ltd, p. 109339, Nov. 01, 2019, doi: 10.1016/j.enbuild.2019.109339.
  • E. lo Cascio, Z. Ma, D. Borelli, and C. Schenone, “Residential Building Retrofit through Numerical Simulation: A Case Study,” Energy Procedia, vol. 111, pp. 91–100, Mar. 2017, doi: 10.1016/j.egypro.2017.03.011.
  • A. Synnefa et al., “Transformation through Renovation: An Energy Efficient Retrofit of an Apartment Building in Athens,” Procedia Engineering, vol. 180, pp. 1003–1014, Jan. 2017, doi: 10.1016/j.proeng.2017.04.260.
  • S. N. J. Al-Saadi, J. Al-Hajri, and M. A. Sayari, “Energy-Efficient Retrofitting Strategies for Residential Buildings in hot climate of Oman,” Energy Procediavol. 142, pp. 2009–2014, Dec. 2017, doi: 10.1016/j.egypro.2017.12.403.
  • S. M. Hosseini, R. Carli, and M. Dotoli, “Model Predictive Control for Real-Time Residential Energy Scheduling under Uncertainties,” in Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, pp. 1386–1391, Jan. 2019, doi:10.1109/SMC.2018.00242.
  • R. Halvgaard, L. Vandenberghe, N. K. Poulsen, H. Madsen, and J. B. Jørgensen, “Distributed Model Predictive Control for Smart Energy Systems,” IEEE Transactions on Smart Grid, vol. 7, no. 3, pp. 1675–1682, May 2016, doi: 10.1109/TSG.2016.2526077.
  • D. Dongol, T. Feldmann, and E. Bollin, “A model predictive control based peak shaving application for a grid connected household with photovoltaic and battery storage,” in SMARTGREENS 2018 - Proceedings of the 7th International Conference on Smart Cities and Green ICT Systems, vol. 2018-March, pp. 54–63, 2018 doi: 10.5220/0006685300540063.
  • S. Seal, B. Boulet, and V. R. Dehkordi, “Centralized model predictive control strategy for thermal comfort and residential energy management,” Energy, vol. 212, p. 118456, Dec. 2020, doi: 10.1016/j.energy.2020.118456.
  • R. Halvgaard, L. Vandenberghe, N. K. Poulsen, H. Madsen, and J. B. Jørgensen, “Distributed Model Predictive Control for Smart Energy Systems,” IEEE Transactions on Smart Grid, vol. 7, no. 3, pp. 1675–1682, May 2016, doi: 10.1109/TSG.2016.2526077.
  • H. M. Ruzbahani, A. Rahimnejad, and H. Karimipour, “Smart Households Demand Response Management with Micro Grid,” 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2019, pp. 1-5, doi:10.1109/ISGT.2019.8791595.
  • M. J. M. al Essa, “Home energy management of thermostatically controlled loads and photovoltaic-battery systems,” Energy, vol. 176, pp. 742–752, Jun. 2019, doi: 10.1016/j.energy.2019.04.041.
  • M. Shakeri et al., “An intelligent system architecture in home energy management systems (HEMS) for efficient demand response in smart grid,” Energy and Buildings, vol. 138, pp. 154–164, Mar. 2017, doi: 10.1016/j.enbuild.2016.12.026.
  • A. Parsa, T. A. Najafabadi, and F. R. Salmasi, “Implementation of smart optimal and automatic control of electrical home appliances (IoT),” in IEEE Proceedings 2017 Smart Grid Conference, SGC 2017, Mar. 2018, pp. 1–6, doi: 10.1109/SGC.2017.8308861.
  • H. M. Ruzbahani, A. Rahimnejad and H. Karimipour, "Smart Households Demand Response Management with Micro Grid," 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2019, pp. 1-5, doi: 10.1109/ISGT.2019.8791595.
  • K. Ma, G. Hu, and C. J. Spanos, “A cooperative demand response scheme using punishment mechanism and application to industrial refrigerated warehouses,” IEEE Transactions on Industrial Informatics, vol. 11, no. 6, pp. 1520–1531, Dec. 2015, doi: 10.1109/TII.2015.2431219.
  • A. Mahmood, A. R. Butt, U. Mussadiq, R. Nawaz, R. Zafar, and S. Razzaq, “Energy sharing and management for prosumers in smart grid with integration of storage system,” in ICSG 2017 - 5th International Istanbul Smart Grids and Cities Congress and Fair, Istanbul, Turkey, Jun. 2017, pp. 153–156, doi: 10.1109/SGCF.2017.7947623.
  • H. Turker and I. Colak, “Multiobjective optimization of Grid- Photovoltaic- Electric Vehicle Hybrid system in Smart Building with Vehicle-to-Grid (V2G) concept,” in 7th International IEEE Conference on Renewable Energy Research and Applications, ICRERA 2018, pp. 1477–1482, doi: 10.1109/ICRERA.2018.8567002.
  • “HOME - www.soda-pro.com.” http://www.soda-pro.com/ (accessed Sep. 25, 2020).
  • “Photovoltaic Geographical Information System (PVGIS) | EU Science Hub.” https://ec.europa.eu/jrc/en/pvgis (accessed Sep. 25, 2020).
  • “Global Solar Atlas.” . [Online]. Available: https://globalsolaratlas.info/map?c=11.523088,8.4375,3 (accessed Sep. 25, 2020).
  • “Solar Panels | Tesla.” . [Online]. Available: https://www.tesla.com/solarpanels (accessed Sep. 25, 2020).
  • “Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States - Datasets - OpenEI DOE Open Data.” . [Online]. Available: https://openei.org/doe-opendata/dataset/commercial-and-residential-hourly-load-profiles-for-all-tmy3-locations-in-the-united-states (accessed Sep. 25, 2020).
  • “Electricity storage and renewables: Costs and markets to 2030,” /publications/2017/Oct/Electricity-storage-and-renewables-costs-and-markets, Accessed: Sep. 25, 2020. [Online]. Available: /publications/2017/Oct/Electricity-storage-and-renewables-costs-and-markets.
  • “Time of Use, TOU, Pricing Plans, TOU Pricing Plans | San Diego Gas & Electric.” . [Online]. Available: https://www.sdge.com/whenmatters (accessed Sep. 25, 2020).
  • X. Wu, X. Hu, Y. Teng, S. Qian, and R. Cheng, “Optimal integration of a hybrid solar-battery power source into smart home nanogrid with plug-in electric vehicle,” Journal of Power Sources, vol. 363, pp. 277–283, Sep. 2017, doi: 10.1016/j.jpowsour.2017.07.086.
There are 33 citations in total.

Details

Primary Language English
Subjects Electrical Engineering (Other)
Journal Section Research Article
Authors

Kiswendsida Elias Ouedraogo 0000-0002-1615-1693

Pınar Oğuz Ekim 0000-0003-1860-4526

Erhan Demirok 0000-0002-0266-0366

Early Pub Date December 22, 2023
Publication Date December 29, 2023
Published in Issue Year 2023 Volume: 8 Issue: 1

Cite

IEEE K. E. Ouedraogo, P. O. Ekim, and E. Demirok, “Power Bill Optimization for Grid-tie Solar PV-Battery House”, IJESG, vol. 8, no. 1, pp. 12–24, 2023, doi: 10.55088/ijesg.1335769.

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