The impact of Customer Baseline Load (CBL) calculation methods on Peak Time Rebate program offered to residential customers

• An investigation into CBL methods’ performance for residential customers.
• Performing an error analysis of CBL methods.
• A financial analysis to evaluate the overall performance of CBL methods.
• A proposed solution to improve the accuracy and bias of CBL methods.

This paper investigates the impact of CBL's performance on PTR programs offered to the residential customers. For the purpose of analysis, HighXofY (NYISO), exponential moving average (ISONE), regression methods and their adjusted forms are first introduced and then employed to calculate the CBL. Irish Commission for Energy Regulation (CER) smart metering trial dataset is used for this analysis. Furthermore, the metrics of accuracy, bias and Overall Performance Index (OPI) are introduced and then applied to carry out error analysis. Residential customers as opposed to industrial customers show a high degree of unpredictability due to multitudes of non-correlated personal and household activities. Therefore, an approach is also proposed in this paper to harness the randomness of individual customers’ consumption. Also, it is necessary to examine how the metrics affect DR programs financially for the sake of reaching a valid conclusion about the overall performance of CBL methods. Consequently, a PTR program for a case of 260 customers is investigated as a case study. Results from this case study as well as their discussion are provided at the end.