The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Demand Response Management via Real-Time Electricity Price Control in Smart Grids
Abstract
This paper proposes a real-time pricing scheme that reduces the peak-to-average load ratio through demand response management in smart grid systems. The proposed scheme solves a two-stage optimization problem. On one hand, each user reacts to prices announced by the retailer and maximizes its payoff, which is the difference between its quality-of-usage and the payment to the retailer. On the other hand, the retailer designs the real-time prices in response to the forecasted user reactions to maximize its profit. In particular, each user computes its optimal energy consumption either in closed forms or through an efficient iterative algorithm as a function of the prices. At the retailer side, we develop a Simulated-Annealing-based Price Control (SAPC) algorithm to solve the non-convex price optimization problem. In terms of practical implementation, the users and the retailer interact with each other via a limited number of message exchanges to find the optimal prices. By doing so, the retailer can overcome the uncertainty of users' responses, and users can determine their energy usage based on the actual prices to be used. Our simulation results show that the proposed real-time pricing scheme can effectively shave the energy usage peaks, reduce the retailer's cost, and improve the payoffs of the users.
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Cites
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Cited by
Load forecasting, dynamic pricing and DSM in smart grid: A review
Khan, A. R., Mahmood, A., Safdar, A., Khan, Z. A., & Khan, N. A. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.10.117 · Cited by 469
Local flexibility markets: Literature review on concepts, models and clearing methods
Jin, X., Wu, Q., & Jia, H. (2020) · Applied Energy · doi:10.1016/j.apenergy.2019.114387 · Cited by 373
Dynamic Pricing and Energy Consumption Scheduling With Reinforcement Learning
Kim, B.-G., Zhang, Y., van der Schaar, M., & Lee, J.-W. (2016) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2015.2495145 · Cited by 299
Self-citationEsther, B. P., & Kumar, K. S. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.12.282 · Cited by 264
Anees, A., & Chen, Y.-P. P. (2016) · Applied Energy · doi:10.1016/j.apenergy.2015.12.103 · Cited by 70
Metadata
- Authors
- Qian, L. P., Zhang, Y. J. A., Huang, J., & Wu, Y.
- Venue
- IEEE Journal on Selected Areas in Communications
- Published
- 2013-07
- Volume
- 31
- Issue
- 7
- Pages
- 1268-1280
- ISSN
- 0733-8716 (ISSN-L)
- OpenAlex
- W2148910210
- Cited by
- 287
- References
- 23
- FWCI
- 17.37
- Type
- journal article
- Language
- en
- Open access
- closed
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- Qian, L. P., Zhang, Y. J. A., Huang, J., & Wu, Y. (2013). Demand Response Management via Real-Time Electricity Price Control in Smart Grids. IEEE Journal on Selected Areas in Communications. https://doi.org/10.1109/jsac.2013.130710
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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