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Demand Side Management in Smart Grid Using Heuristic Optimization
Open accessAbstract
Demand side management (DSM) is one of the important functions in a smart grid that allows customers to make informed decisions regarding their energy consumption, and helps the energy providers reduce the peak load demand and reshape the load profile. This results in increased sustainability of the smart grid, as well as reduced overall operational cost and carbon emission levels. Most of the existing demand side management strategies used in traditional energy management systems employ system specific techniques and algorithms. In addition, the existing strategies handle only a limited number of controllable loads of limited types. This paper presents a demand side management strategy based on load shifting technique for demand side management of future smart grids with a large number of devices of several types. The day-ahead load shifting technique proposed in this paper is mathematically formulated as a minimization problem. A heuristic-based Evolutionary Algorithm (EA) that easily adapts heuristics in the problem was developed for solving this minimization problem. Simulations were carried out on a smart grid which contains a variety of loads in three service areas, one with residential customers, another with commercial customers, and the third one with industrial customers. The simulation results show that the proposed demand side management strategy achieves substantial savings, while reducing the peak load demand of the smart grid.
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“All these works neglect grid constraints, and therefore there is no strict control of congestion events and voltage issues along the feeders.”
From Congestion mitigation in unbalanced residential networks with OPF-based demand management (2022) · cites this paper as [13]
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Metadata
- Authors
- Logenthiran, T., Srinivasan, D., & Shun, T. Z.
- Affiliations
- National University of Singapore (SG)
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2012-09
- Volume
- 3
- Issue
- 3
- Pages
- 1244-1252
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W2055134499
- Cited by
- 1,229
- References
- 21
- Citations by year
- 2026: 35 · 2025: 40 · 2024: 49 · 2023: 75 · 2022: 103 · 2021: 110 · 2020: 106 · 2019: 129 · 2018: 146 · 2017: 142 · 2016: 107 · 2015: 89 · 2014: 59 · 2013: 35 · 2012: 4
- FWCI
- 38.24
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- IEEE Transactions on Smart Grid (publishedVersion)
- National University of Singapore (submittedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid and Power Systems
- Keywords
- demand-side management, smart grid, load shifting, day-ahead scheduling, peak shaving, flexible loads, evolutionary algorithms, heuristic optimization, energy cost reduction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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