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Look-Ahead Energy Management of a Grid-Connected Residential PV System with Energy Storage under Time-Based Rate Programs

Author

Listed:
  • Jaeyeong Yoo

    (School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea)

  • Byungsung Park

    (School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea)

  • Kyungsung An

    (School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea)

  • Essam A. Al-Ammar

    (Saudi Aramco Chair in Electrical Power, Department of Electrical Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Yasin Khan

    (Saudi Aramco Chair in Electrical Power, Department of Electrical Engineering, King Saud University, Riyadh 11421, Saudi Arabia)

  • Kyeon Hur

    (School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea)

  • Jong Hyun Kim

    (Department of Nuclear & Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon 305-701, South Korea)

Abstract

This paper presents look-ahead energy management system for a grid-connected residential photovoltaic (PV) system with battery under critical peak pricing for electricity, enabling effective and proactive participation of consumers in the Smart Grid’s demand response. In the proposed system, the PV is the primary energy source with the battery for storing (or retrieving) excessive (or stored) energy to pursue the lowest possible electricity bill but it is grid-tied to secure electric power delivery. Premise energy management scheme with an accurate yet practical load forecasting capability based on a Kalman filter is designed to increase the predictability in controlling the power flows among these power system components and the controllable electric appliances in the premise. The case studies with various operating scenarios demonstrate the validity of the proposed system and significant cost savings through operating the energy management scheme.

Suggested Citation

  • Jaeyeong Yoo & Byungsung Park & Kyungsung An & Essam A. Al-Ammar & Yasin Khan & Kyeon Hur & Jong Hyun Kim, 2012. "Look-Ahead Energy Management of a Grid-Connected Residential PV System with Energy Storage under Time-Based Rate Programs," Energies, MDPI, vol. 5(4), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:5:y:2012:i:4:p:1116-1134:d:17292
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    References listed on IDEAS

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    1. Iqbal, M.T., 2003. "Modeling and control of a wind fuel cell hybrid energy system," Renewable Energy, Elsevier, vol. 28(2), pages 223-237.
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    Cited by:

    1. Sheng-Yu Tseng & Hung-Yuan Wang, 2013. "A Photovoltaic Power System Using a High Step-up Converter for DC Load Applications," Energies, MDPI, vol. 6(2), pages 1-33, February.
    2. Muhammad Majid Hussain & Rizwan Akram & Zulfiqar Ali Memon & Mian Hammad Nazir & Waqas Javed & Muhammad Siddique, 2021. "Demand Side Management Techniques for Home Energy Management Systems for Smart Cities," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    3. David Toquica & Kodjo Agbossou & Roland Malhamé & Nilson Henao & Sousso Kelouwani & Alben Cardenas, 2020. "Adaptive Machine Learning for Automated Modeling of Residential Prosumer Agents," Energies, MDPI, vol. 13(9), pages 1-19, May.
    4. Arslan Ahmad Bashir & Mahdi Pourakbari Kasmaei & Amir Safdarian & Matti Lehtonen, 2018. "Matching of Local Load with On-Site PV Production in a Grid-Connected Residential Building," Energies, MDPI, vol. 11(9), pages 1-16, September.
    5. Yoon, Yourim & Kim, Yong-Hyuk, 2016. "Effective scheduling of residential energy storage systems under dynamic pricing," Renewable Energy, Elsevier, vol. 87(P2), pages 936-945.
    6. Sani Hassan, Abubakar & Cipcigan, Liana & Jenkins, Nick, 2017. "Optimal battery storage operation for PV systems with tariff incentives," Applied Energy, Elsevier, vol. 203(C), pages 422-441.
    7. Seog-Chan Oh & Alfred J. Hildreth, 2013. "Decisions on Energy Demand Response Option Contracts in Smart Grids Based on Activity-Based Costing and Stochastic Programming," Energies, MDPI, vol. 6(1), pages 1-19, January.
    8. Luis Hernández-Callejo, 2019. "A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids," Energies, MDPI, vol. 12(9), pages 1-50, April.
    9. Adnan Ahmad & Asif Khan & Nadeem Javaid & Hafiz Majid Hussain & Wadood Abdul & Ahmad Almogren & Atif Alamri & Iftikhar Azim Niaz, 2017. "An Optimized Home Energy Management System with Integrated Renewable Energy and Storage Resources," Energies, MDPI, vol. 10(4), pages 1-35, April.
    10. Lupangu, C. & Bansal, R.C., 2017. "A review of technical issues on the development of solar photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 950-965.
    11. Chapaloglou, Spyridon & Nesiadis, Athanasios & Iliadis, Petros & Atsonios, Konstantinos & Nikolopoulos, Nikos & Grammelis, Panagiotis & Yiakopoulos, Christos & Antoniadis, Ioannis & Kakaras, Emmanuel, 2019. "Smart energy management algorithm for load smoothing and peak shaving based on load forecasting of an island’s power system," Applied Energy, Elsevier, vol. 238(C), pages 627-642.
    12. Zafar Iqbal & Nadeem Javaid & Saleem Iqbal & Sheraz Aslam & Zahoor Ali Khan & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2018. "A Domestic Microgrid with Optimized Home Energy Management System," Energies, MDPI, vol. 11(4), pages 1-39, April.
    13. Daniele Gallo & Carmine Landi & Mario Luiso & Rosario Morello, 2013. "Optimization of Experimental Model Parameter Identification for Energy Storage Systems," Energies, MDPI, vol. 6(9), pages 1-19, September.

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