Averaging methods determine baselines by averaging the consumption on past days that are similar (ex: in temperature or workday) to the event day. There are many variants such as weighted averaging and using an adjustment factor to account for variations between the event day and prior similar days. A detailed comparison of different averaging methods in offered in [8] [9] [10]. While averaging methods are attractive because of their simplicity, they suffer from estimation biases that can be substantial [10] [11]. Also, these methods require significant **data** access, especially for residential DR programs [12].