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Appliance level data analysis of summer demand reduction potential from residential air conditioner control

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  • Malik, Anam
  • Haghdadi, Navid
  • MacGill, Iain
  • Ravishankar, Jayashri

Abstract

Residential air-conditioner loads are known to be a key driver of summer demand peaks for some electricity industries. Such demand peaks occur infrequently but have potentially severe implications for network and peaking generation plant investment, and hence electricity prices for end users. Detailed assessments of air-conditioner peak demand have, however, been hampered by limited residential consumption data, and even when interval meter data is available, the complexities of other household loads and behavior. This study utilizes data from a significant appliance level consumption monitoring project in Sydney, Australia, to analyze the actual contribution of air-conditioners to regional summer demand peaks. K-means clustering is used to characterize air-conditioner load profiles across a large number of households at times of these overall demand peaks. These clustered air-conditioning load profiles, combined with a number of possible load control strategies, are then used to estimate possible peak load reductions from air-conditioner demand response across the Australian State of New South Wales. Our findings suggest that residential air-conditioning presents a significant demand response opportunity, approaching perhaps 9% of total peak demand in some circumstances.

Suggested Citation

  • Malik, Anam & Haghdadi, Navid & MacGill, Iain & Ravishankar, Jayashri, 2019. "Appliance level data analysis of summer demand reduction potential from residential air conditioner control," Applied Energy, Elsevier, vol. 235(C), pages 776-785.
    • Handle: RePEc:eee:appene:v:235:y:2019:i:c:p:776-785
    DOI: 10.1016/j.apenergy.2018.11.010
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    6. Rama Curiel, José Adrián & Thakur, Jagruti, 2022. "A novel approach for Direct Load Control of residential air conditioners for Demand Side Management in developing regions," Energy, Elsevier, vol. 258(C).
    7. Zhu, Mengshu & Huang, Ying & Wang, Si-Nuo & Zheng, Xinye & Wei, Chu, 2023. "Characteristics and patterns of residential energy consumption for space cooling in China: Evidence from appliance-level data," Energy, Elsevier, vol. 265(C).
    8. Miranda, Nicole D. & Renaldi, Renaldi & Khosla, Radhika & McCulloch, Malcolm D., 2021. "Bibliometric analysis and landscape of actors in passive cooling research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    9. Afzalan, Milad & Jazizadeh, Farrokh, 2019. "Residential loads flexibility potential for demand response using energy consumption patterns and user segments," Applied Energy, Elsevier, vol. 254(C).
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