2021/11/22 by Kamalanathan Ganesan, Ganesan, Kamalanathan, Jo ao Tom'e Saraiva +4
Engineering · #FOS: Computer and information sciences #FOS: Economics and business #FOS: Electrical engineering #General Economics (econ.GN) #Machine Learning (cs.LG) #Smart Grid Energy Management #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2111.11875
openalex publication_date 2021/11/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
One of the major barriers for the retailers is to understand the consumption\nelasticity they can expect from their contracted demand response (DR) clients.\nThe current trend of DR products provided by retailers are not\nconsumer-specific, which poses additional barriers for the active engagement of\nconsumers in these programs. The elasticity of consumers demand behavior varies\nfrom individual to individual. The utility will benefit from knowing more\naccurately how changes in its prices will modify the consumption pattern of its\nclients. This work proposes a functional model for the consumption elasticity\nof the DR contracted consumers. The model aims to determine the load adjustment\nthe DR consumers can provide to the retailers or utilities for different price\nlevels. The proposed model uses a Bayesian probabilistic approach to identify\nthe actual load adjustment an individual contracted client can provide for\ndifferent price levels it can experience. The developed framework provides the\nretailers or utilities with a tool to obtain crucial information on how an\nindividual consumer will respond to different price levels. This approach is\nable to quantify the likelihood with which the consumer reacts to a DR signal\nand identify the actual load adjustment an individual contracted DR client\nprovides for different price levels they can experience. This information can\nbe used to maximize the control and reliability of the services the retailer or\nutility can offer to the System Operators.\n