2019 IEEE International Conference on Big Data (Big Data) 2019
DOI: 10.1109/bigdata47090.2019.9005456
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Power Demand Response Incentive Pricing Model

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Cited by 3 publications
(3 citation statements)
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“…To motivate power users to participate in the interruptible load management, the authors in [127] proposed a multiattribute sealed auction game to simulate the interaction between the power company and the power users, with the aim of maximizing the power company's revenue and finally decide the list of participating users. The auction model consists of two main phases, i.e., user bidding and user selection.…”
Section: B Incentive Mechanisms Based On Reverse Auctionsmentioning
confidence: 99%
“…To motivate power users to participate in the interruptible load management, the authors in [127] proposed a multiattribute sealed auction game to simulate the interaction between the power company and the power users, with the aim of maximizing the power company's revenue and finally decide the list of participating users. The auction model consists of two main phases, i.e., user bidding and user selection.…”
Section: B Incentive Mechanisms Based On Reverse Auctionsmentioning
confidence: 99%
“…• From the perspective of reward methods, most articles motivate participants by money, and the only article [75] motivate participants by non-monetary means, through reward points to increase the probability of being selected, and further encourage more small and medium-sized users to participate. Participants aim to obtain monetary rewards, which is easy to cause fraud.…”
Section: Rq4: What Are the Incentive Mechanisms To Improve The Data Q...mentioning
confidence: 99%
“…The images collected by the car camera classification and labeling [64] Air quality assessment [65,66] Energy demand prediction for electric vehicle network [67,68] Traffic sign recognition [69] Traffic flow prediction [70] Vehicle scheduling [71], routing [72] Indoor localization [73] Security monitoring [74] Power demand response [75] Physical Information System…”
Section: Computing and Smart Citymentioning
confidence: 99%