Optimal coordination and scheduling of demand response via monetary incentives
Abstract
Without demand-side management, an increase in the number of electric vehicles (EVs) could result in overloads on distribution feeders. Aggregators could optimally manage the charging/discharging of the EVs, to not only maximize the consumers' welfare in response to real-time prices and accommodate their needs for transportation, but also to keep the distribution network within its operating limits. This paper proposes a decentralized framework in which the aggregator seeks to maximize its profits while the consumers minimize their costs in response to time-varying prices, and additional incentives provided to mitigate potential overloads in the distribution system. Test results show that a large penetration of EV penetration can then be managed without violating the capacity of the distribution network.
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
References [11] and [28] rely on balanced power flow equations, whereas the distribution system is unbalanced.
“References [11], [28] rely on balanced power flow equations, whereas the distribution system is unbalanced”
From Congestion mitigation in unbalanced residential networks with OPF-based demand management (2022) · cites this paper as [11]
Reference [11] does not provide feasibility considerations of its MILP approximations.
“and [11] does not provide feasibility considerations of their MILP approximations.”
From Congestion mitigation in unbalanced residential networks with OPF-based demand management (2022) · cites this paper as [11]
The MILP formulation used is three-phase unbalanced, which gives a better distribution system representation than balanced models while remaining computationally tractable.
“The MILP formulation used is three-phase unbalanced, which gives a better distribution system representation than balanced models (like [11], [28]), while it is still”
From Congestion mitigation in unbalanced residential networks with OPF-based demand management (2022) · cites this paper as [11]
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References 36 · Cited by 203
- Authors
- Sarker, M. R., Ortega-Vazquez, M. A., & Kirschen, D. S.
- Affiliations
- University of Washington (US)
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2015-05
- Volume
- 6
- Issue
- 3
- Pages
- 1341-1352
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W2009668565
- Cited by
- 203
- References
- 36
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 5 · 2023: 16 · 2022: 22 · 2021: 25 · 2020: 25 · 2019: 31 · 2018: 20 · 2017: 24 · 2016: 16 · 2015: 5
- FWCI
- 7.96
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Smart Grid (publishedVersion)
- Funders
- National Science Foundation (1239408)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- demand response, electric vehicle charging, demand-side management, distribution network capacity, distributed coordination, aggregators, financial incentives, time-varying prices, consumer welfare, EV penetration
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