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A new demand response algorithm for solar PV intermittency management

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  • Sivaneasan, Balakrishnan
  • Kandasamy, Nandha Kumar
  • Lim, May Lin
  • Goh, Kwang Ping

Abstract

This paper presents a new algorithm for managing solar PV intermittency in green buildings using demand response management (DRM) technique. The proposed DRM algorithm utilizes the building air conditioning and mechanical ventilation (ACMV) system to dynamically compensate for the deficit of power generated by solar PV system from its rated capacity. For example, the developed solution will reduce the load demand of the ACMV system equal to the drop of solar generation by controlling the speed of the fan. This will ensure that the amount of power supplied by the grid to the building will remain the same (as before the drop of solar generation) and thus no impact on the grid stability. However, since ACMV system is directly linked to building occupant comfort/health, the proposed solution will also include energy storage management and priority-based load shedding programs to provide support when room temperature (air conditioning) or CO level (ventilation) is above regulatory limit. A thermal model for building temperature variation is developed to test and analyze the proposed algorithm to dynamically manage solar PV fluctuation.

Suggested Citation

  • Sivaneasan, Balakrishnan & Kandasamy, Nandha Kumar & Lim, May Lin & Goh, Kwang Ping, 2018. "A new demand response algorithm for solar PV intermittency management," Applied Energy, Elsevier, vol. 218(C), pages 36-45.
    • Handle: RePEc:eee:appene:v:218:y:2018:i:c:p:36-45
    DOI: 10.1016/j.apenergy.2018.02.147
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    2. Thiaux, Yaël & Dang, Thu Thuy & Schmerber, Louis & Multon, Bernard & Ben Ahmed, Hamid & Bacha, Seddik & Tran, Quoc Tuan, 2019. "Demand-side management strategy in stand-alone hybrid photovoltaic systems with real-time simulation of stochastic electricity consumption behavior," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
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    5. Ana García-Garre & Antonio Gabaldón & Carlos Álvarez-Bel & María Del Carmen Ruiz-Abellón & Antonio Guillamón, 2018. "Integration of Demand Response and Photovoltaic Resources in Residential Segments," Sustainability, MDPI, vol. 10(9), pages 1-31, August.
    6. Xie, Kang & Hui, Hongxun & Ding, Yi & Song, Yonghua & Ye, Chengjin & Zheng, Wandong & Ye, Shuiquan, 2022. "Modeling and control of central air conditionings for providing regulation services for power systems," Applied Energy, Elsevier, vol. 315(C).
    7. Nousdilis, Angelos I. & Christoforidis, Georgios C. & Papagiannis, Grigoris K., 2018. "Active power management in low voltage networks with high photovoltaics penetration based on prosumers’ self-consumption," Applied Energy, Elsevier, vol. 229(C), pages 614-624.
    8. Susanto, Julius & Shahnia, Farhad & Ludwig, David, 2018. "A framework to technically evaluate integration of utility-scale photovoltaic plants to weak power distribution systems," Applied Energy, Elsevier, vol. 231(C), pages 207-221.
    9. Alex Ximenes Naves & Laureano Jiménez Esteller & Assed Naked Haddad & Dieter Boer, 2021. "Targeting Energy Efficiency through Air Conditioning Operational Modes for Residential Buildings in Tropical Climates, Assisted by Solar Energy and Thermal Energy Storage. Case Study Brazil," Sustainability, MDPI, vol. 13(22), pages 1-29, November.
    10. Temitayo O. Olowu & Aditya Sundararajan & Masood Moghaddami & Arif I. Sarwat, 2018. "Future Challenges and Mitigation Methods for High Photovoltaic Penetration: A Survey," Energies, MDPI, vol. 11(7), pages 1-32, July.
    11. Ren, Haoshan & Ma, Zhenjun & Fai Norman Tse, Chung & Sun, Yongjun, 2022. "Optimal control of solar-powered electric bus networks with improved renewable energy on-site consumption and reduced grid dependence," Applied Energy, Elsevier, vol. 323(C).

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