Prediction and assessment of demand response potential with coupon incentives in highly renewable power systems

Abstract

Demand 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.

Market Transaction Model Design Applicable for Both Plan and Market Environment of China’s Renewable Energy

“…For medium-and long-term market-oriented transactions, on the basis of standardizing annual and monthly regular market operation, the power transaction with the curve is carried out based on available transfer capability (ATC) and other constraints, gradually shortening transaction cycles, rolling out short-term power transactions in a month, realizing continuous market operation within a month, allowing market entities to adjust the transaction contract curve continuously through multiple transactions, and promoting market transactions to be as close to actual operation as possible, connecting with spot transactions well (Ming et al, 2020;Cong et al, 2020). For special power generation types such as renewable energy, the curve can be determined by itself or agreed in advance before market closing according to transaction contracts and submitted to dispatching organizations.…”

Prediction of Survival Time of Patients With Esophageal Squamous Cell Carcinoma Based on Univariate Analysis and ASSA-BP Neural Network

“…The processed data with the real data is compared. If the difference does not meet the set precision requirement, then enters the back propagation [33], [34]. At this time, the weights and thresholds of neurons in each layer will be changed, and the weights and thresholds will be changed continuously through the above process cycle, until the minimum difference set or the preset training times are met [33], [34].…”

Design of Incentive Mechanisms Using Prospect Theory to Promote Better Sell-back Behavior among Prosumers

“…We proposed a lottery based mechanism and analyzed the mechanism using the prospect theory. [20] implements a coupon based system for demand response program. In contrast, we provide a theoretical understanding of the lottery based mechanism using prospect theory, and compute the optimal sell-back amount for a given lottery scheme.…”