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Energy Storage System Control Algorithm by Operating Target Power to Improve Energy Sustainability of Smart Home

Author

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  • Byeongkwan Kang

    (School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Korea)

  • Kyuhee Jang

    (School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Korea)

  • Sounghoan Park

    (School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Korea)

  • Myeong-in Choi

    (School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Korea)

  • Sehyun Park

    (School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Korea)

Abstract

As energy issues are emerging around the world, a variety of smart home technologies aimed at realizing zero energy houses are being introduced. Energy storage system (ESS) for smart home energy independence is increasingly gaining interest. However, limitations exist in that most of them are controlled according to time schedules or used in conjunction with photovoltaic (PV) generation systems. In consideration of load usage patterns and PV generation of smart home, this study proposes an ESS control algorithm that uses constant energy of energy network while making maximum use of ESS. Constant energy means that the load consumes a certain amount of power under all conditions, which translates to low variability. The proposed algorithm makes a smart home a load of energy network with low uncertainty and complexity. The simulation results show that the optimal ESS operating target power not only makes the smart home use power constantly from the energy network, but also maximizes utilization of the ESS. In addition, since the smart home is a load that uses constant energy, it has the advantage of being able to operate an efficient energy network from the viewpoint of energy providers.

Suggested Citation

  • Byeongkwan Kang & Kyuhee Jang & Sounghoan Park & Myeong-in Choi & Sehyun Park, 2018. "Energy Storage System Control Algorithm by Operating Target Power to Improve Energy Sustainability of Smart Home," Sustainability, MDPI, vol. 10(1), pages 1-16, January.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:1:p:236-:d:127441
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    References listed on IDEAS

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    1. Zhou, Bin & Li, Wentao & Chan, Ka Wing & Cao, Yijia & Kuang, Yonghong & Liu, Xi & Wang, Xiong, 2016. "Smart home energy management systems: Concept, configurations, and scheduling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 30-40.
    2. Yohwan Choi & Hongseok Kim, 2016. "Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost," Energies, MDPI, vol. 9(6), pages 1-19, June.
    3. Brian C. Murray & Peter T. Maniloff & Evan M. Murray, 2015. "Why Have Greenhouse Emissions in RGGI States Declined? An Econometric Attribution to Economic, Energy Market and Policy Factors (Payne Institute Policy Brief)," Payne Institute Policy Briefs 2014-04, Colorado School of Mines, Division of Economics and Business.
    4. M. Hasanuzzaman & Ummu Salamah Zubir & Nur Iqtiyani Ilham & Hang Seng Che, 2017. "Global electricity demand, generation, grid system, and renewable energy polices: a review," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 6(3), May.
    5. Gabriele Lobaccaro & Salvatore Carlucci & Erica Löfström, 2016. "A Review of Systems and Technologies for Smart Homes and Smart Grids," Energies, MDPI, vol. 9(5), pages 1-33, May.
    6. Erdinc, Ozan, 2014. "Economic impacts of small-scale own generating and storage units, and electric vehicles under different demand response strategies for smart households," Applied Energy, Elsevier, vol. 126(C), pages 142-150.
    7. Telaretti, E. & Graditi, G. & Ippolito, M.G. & Zizzo, G., 2016. "Economic feasibility of stationary electrochemical storages for electric bill management applications: The Italian scenario," Energy Policy, Elsevier, vol. 94(C), pages 126-137.
    8. Murray, Brian C. & Maniloff, Peter T., 2015. "Why have greenhouse emissions in RGGI states declined? An econometric attribution to economic, energy market, and policy factors," Energy Economics, Elsevier, vol. 51(C), pages 581-589.
    9. Fischer, Carolyn & Newell, Richard G., 2008. "Environmental and technology policies for climate mitigation," Journal of Environmental Economics and Management, Elsevier, vol. 55(2), pages 142-162, March.
    10. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    11. Brian L. Thomas & Diane J. Cook, 2016. "Activity-Aware Energy-Efficient Automation of Smart Buildings," Energies, MDPI, vol. 9(8), pages 1-17, August.
    12. Li, Ke & Lin, Boqiang, 2015. "Impacts of urbanization and industrialization on energy consumption/CO2 emissions: Does the level of development matter?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1107-1122.
    13. Wade, N.S. & Taylor, P.C. & Lang, P.D. & Jones, P.R., 2010. "Evaluating the benefits of an electrical energy storage system in a future smart grid," Energy Policy, Elsevier, vol. 38(11), pages 7180-7188, November.
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    Cited by:

    1. Zheng Li & Ruoyao Tang & Hanbin Qiu & Linwei Ma, 2023. "Smart Energy Urban Agglomerations in China: The Driving Mechanism, Basic Concepts, and Indicator Evaluation," Sustainability, MDPI, vol. 15(15), pages 1-23, August.
    2. Federica Cucchiella & Idiano D’Adamo & Massimo Gastaldi & Vincenzo Stornelli, 2018. "Solar Photovoltaic Panels Combined with Energy Storage in a Residential Building: An Economic Analysis," Sustainability, MDPI, vol. 10(9), pages 1-29, August.

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