Multi-objective home energy management with battery energy storage systems
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The presented method is more inclusive than other DSM examples in the literature, which only allow users with storage systems, smart appliances, EVs, or similar to participate.
“Moreover, the presented method is more inclusive than other DSM examples from the literature, where only users with storage systems [14], smart appliances [15], EVs [16] or similar can participate.”
From Congestion mitigation in unbalanced residential networks with OPF-based demand management (2022) · cites this paper as [14]
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References 33 · Cited by 170
- Authors
- Lokeshgupta, B., & Sivasubramani, S.
- Affiliations
- Indian Institute of Technology Patna (IN)
- Corresponding author
- Sivasubramani, S.
- Venue
- Sustainable Cities and Society
- Publisher
- Elsevier BV
- Published
- 2019-05
- Volume
- 47
- Pages
- 101458
- ISSN
- 2210-6707 (ISSN-L)
- OpenAlex
- W2914046382
- Cited by
- 170
- References
- 33
- Citations by year
- 2026: 9 · 2025: 12 · 2024: 25 · 2023: 28 · 2022: 29 · 2021: 31 · 2020: 31 · 2019: 5
- FWCI
- 8.63
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Sustainable Cities and Society (publishedVersion)
- 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 › IoT-based Smart Home Systems
- Keywords
- home energy management systems, battery energy storage, demand-side management, multi-objective optimization, mixed-integer linear programming, peak shaving, electricity cost reduction, load uncertainty, smart grid, residential customers
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