Prediction and assessment of demand response potential with coupon incentives in highly renewable power systems Academic Article uri icon

abstract

  • AbstractDemand Response (DR) provides both operational and financial benefits to a variety of stakeholders in the power system. For example, in the deregulated market operated by the Electric Reliability Council of Texas (ERCOT), load serving entities (LSEs) usually purchase electricity from the wholesale market (either in day-ahead or real-time market) and sign fixed retail price contracts with their end-consumers. Therefore, incentivizing end-consumers’ load shift from peak to off-peak hours could benefit the LSE in terms of reducing its purchase of electricity under high prices from the real-time market. As the first-of-its-kind implementation of Coupon Incentive-based Demand Response (CIDR), the EnergyCoupon project provides end-consumers with dynamic time-of-use DR event announcements, individualized load reduction targets with EnergyCoupons as the incentive for meeting these targets, as well as periodic lotteries using these coupons as lottery tickets for winning dollar-value gifts. A number of methodologies are developed for this special type of DR program including price/baseline prediction, individualized target setting and a lottery mechanism. This paper summarizes the methodologies, design, critical findings, as well as the potential generalization of such an experiment. Comparison of the EnergyCoupon with a conventional Time-of-Use (TOU) price-based DR program is also conducted. Experimental results in the year 2017 show that by combining dynamic coupon offers with periodic lotteries, the effective cost for demand response providers in EnergyCoupon can be substantially reduced, while achieving a similar level of demand reduction as conventional DR programs.

author list (cited authors)

  • Ming, H., Xia, B., Lee, K., Adepoju, A., Shakkottai, S., & Xie, L. e.

complete list of authors

  • Ming, Hao||Xia, Bainan||Lee, Ki-Yeob||Adepoju, Adekunle||Shakkottai, Srinivas||Xie, Le

publication date

  • April 2020