Building a Better Baseline for Residential Demand Response Programs: Mitigating the Effects of Customer Heterogeneity and Random Variations

Peter Schwarz,Valentina Cecchi,Saeed Mohajeryami

doi:10.3390/electronics9040570

Peter Schwarz, Valentina Cecchi + Show 1 more

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https://doi.org/10.3390/electronics9040570

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Abstract

Peak-time rebates offer an opportunity to introduce demand response in electricity markets. To implement peak-time rebates, utilities must accurately determine the consumption level if the program were not in effect. Reliable calculations of customer baseline load elude utilities and independent system operators, due to factors that include heterogeneous demands and random variations. Prevailing research is limited for residential markets, which are growing rapidly with the presence of load aggregators and the availability of smart grid systems. Our research pioneers a novel method that clusters customers according to the size and predictability of their demands, substantially improving existing customer baseline calculations and other clustering methods.

Highlights

Smart grid systems provide real-time capability for managing and monitoring electric usage.With smart grid technology, demand response (DR) offers a cost-effective alternative to increasing electricity supply, when dealing with a small number of capacity-constrained hours
We are unable to consider gaming, as the customers we study are not yet subject to an actual DR program
We find that our clustering method performs considerably better than non-clustering methods currently used by load-serving entities (LSEs), and improves upon previous methods of clustering, based on standard metrics of accuracy and bias commonly used to measure customer baseline load (CBL) performance

Summary

Introduction

Smart grid systems provide real-time capability for managing and monitoring electric usage. Demand response (DR) offers a cost-effective alternative to increasing electricity supply, when dealing with a small number of capacity-constrained hours. For purposes of this article, DR refers to programs where customers are paid “to reduce their consumption relative to an administratively set baseline level of consumption.” [1]. While economists have long endorsed dynamic prices such as real-time pricing (RTP) that vary continuously to improve electric system efficiency, regulators have hesitated to implement these programs, for residential customers. To gain greater customer participation, electricity load-serving entities (LSEs) have introduced DR offerings, such as peak-time rebate (PTR), that credit customers for reducing their use during event hours rather than charging a premium during high demand hours

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