Evaluating Demand Response Potential of Air Conditioners in Residential Sector: A Data-Driven Approach Estimating Room Temperature

With the rapid spread of renewable energy, the utilizing residential air conditioners (AC) for demand response (DR) is gaining importance. As resource aggregators seek to manage the flexibility offered by a large number of AC units, accurately estimating the DR potential of ACs is essential for successful bidding in the balancing market. This study introduced a data-driven method that leverages measured electricity data from residential ACs to evaluate the DR potential and estimate the room temperature without the complex model of thermal conduction. The proposed method comprises three components: estimating the AC turn-on/off states, calculating time-dependent parameters for room temperature estimation, and determining the room temperature and AC electricity consumption after DR implementation. A case study was conducted using data from 479 dwellings in Osaka, Japan, to assess the downward DR potential during the cooling season. Results indicate a median DR potential ranging from 9.2% to 18.7% of total AC electricity consumption. This study provides valuable insights into leveraging residential ACs as flexible resources for demand response, empowering resource aggregators to make informed decisions in a balanced market.