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Dynamic pricing

About: Dynamic pricing is a research topic. Over the lifetime, 4144 publications have been published within this topic receiving 91390 citations. The topic is also known as: surge pricing & demand pricing.


Papers
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Journal ArticleDOI
TL;DR: A vision and related implementation of the services needed by the end user to enable the smart grid in a smart home and an economic analysis to assess the cost of energy produced by small renewable-based installations are presented.
Abstract: The smart grid promises to change the way people manage their energy needs, to facilitate the inclusion of small-scale renewable sources, and to open the energy market to all. One of the enabling instruments is the real-time pricing of energy at the retail level: dynamic and flexible tariffs will vary through the day to reflect the actual availability of energy and the congestion conditions of the power grid, in turn, helping the power grid to stay in balance. Current pilots and research efforts consider how such dynamic tariffs can be formed and how these will affect energy distribution and usage, although currently there are no instances of them deployed. To experiment with dynamic pricing, we present a vision and related implementation of the services needed by the end user to enable the smart grid in a smart home. Our system realistically simulates the dynamic prices and services of the smart grid, using data coming from wholesale energy markets and renewable installations. In addition, we perform an economic analysis to assess the cost of energy produced by small renewable-based installations. The aim is to offer a testing tool to easily realize large simulations, testbeds, and pilot projects for future energy distribution scenarios. We have tested the proposed services and dynamic pricing solution in an existing living laboratory, showing the feasibility of the approach and effectiveness of the tool.

40 citations

Journal ArticleDOI
Zhan Pang1
TL;DR: This paper studies the optimal dynamic pricing and inventory control policies in a periodic-review inventory system with fixed ordering cost and additive demand and identifies two sufficient conditions under which (s,S,p) policies are optimal.

40 citations

Journal ArticleDOI
TL;DR: This paper proposes an average cost Markov decision process model to reduce the expected total system travel time of the logit route choice model using dynamic pricing and develops approximation schemes for handling a large number of users.
Abstract: The traffic assignment problem is primarily concerned with the study of user equilibrium and system optimum and it is often assumed that travelers are perfectly rational and have a complete knowledge of network conditions. However, from an empirical standpoint, when a large number of selfish users travel in a network, the chances of reaching an equilibrium are slim. User behavior in such settings can be modeled using probabilistic route choice models which define when and how travelers switch paths. This approach results in stochastic processes with steady state distributions containing multiple states in their support. In this paper, we propose an average cost Markov decision process model to reduce the expected total system travel time of the logit route choice model using dynamic pricing. Existing dynamic pricing methods in day-to-day network models are formulated in continuous time. However, the solutions from these methods cannot be used to set tolls on different days in the network. We hence study dynamic tolling in a discrete time setting in which the system manager collects tolls based on the state of the system on previous day(s). In order to make this framework practical, approximation schemes for handling a large number of users are developed. A simple example to illustrate the application of the exact and approximate methods is also presented.

40 citations

Journal ArticleDOI
TL;DR: In this paper, the authors consider how governments and firms and nonprofits strategically interact in the design and implementation of these systems and assess with regard to the uniqueness of bidding in government four principles on the role of credible commitments, rational collusion, the setting of reserve prices, and heterogeneity among bidders.
Abstract: Governments continue to embrace the market-like mechanisms of auctions and bidding. This essay considers how governments (as bid-takers) and firms and nonprofits (as bidders) strategically interact in the design and implementation of these systems. I assess with regard to the uniqueness of bidding in government four principles on the role of: credible commitments, rational collusion, the setting of reserve prices, and heterogeneity among bidders. I also address recent calls for expanding the use of dynamic pricing in government.

40 citations

Proceedings ArticleDOI
01 Oct 2013
TL;DR: It is shown that the accumulative regret of the proposed algorithm grows with the learning horizon T at the order of O(log T) and the achieved growth rate cannot be reduced by any piecewise linear policy.
Abstract: The problem of dynamically pricing of electricity by a retailer for customers in a demand response program is considered. It is assumed that the retailer obtains electricity in a two-settlement wholesale market consisting of a day ahead market and a real-time market. Under a day ahead dynamic pricing mechanism, the retailer aims to learn the aggregated demand function of its customers while maximizing its retail profit. A piecewise linear stochastic approximation algorithm is proposed. It is shown that the accumulative regret of the proposed algorithm grows with the learning horizon T at the order of O(log T). It is also shown that the achieved growth rate cannot be reduced by any piecewise linear policy.

40 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023140
2022262
2021307
2020324
2019346
2018314