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Energy management system for smart grid: An overview and key issues
Abstract
Energy crisis and the global impetus to “go green” have encouraged the integration of renewable energy resources, plug-in electric vehicles, and energy storage systems to the grid. The presence of more than one energy source in the grid necessitates the need for an efficient energy management system to guide the flow of energy. Moreover, the variability and volatile nature of renewable energy sources, uncertainties associated with plug-in electric vehicles, the electricity price, and the time-varying load bring new challenges to the power engineers to achieve demand-supply balance for stable operation of the power system. The energy management system can effectively coordinate the energy sharing/trading among all available energy resources, and supply loads economically in all the conditions for the reliable, secure, and efficient operation of the power system. This paper reviews the framework, objectives, architecture, benefits, and challenges of the energy management system with a comprehensive analysis of different stakeholders and participants involved in it. The review paper gives a critical analysis of the distributed energy resources behavior and different programs such as demand response, demand-side management, and power quality management implemented in the energy management system. Different uncertainty quantification methods are also summarized. This review paper also presents a comparative and critical analysis of the main optimization techniques used to achieve different energy management system objectives while satisfying multiple constraints. Thus, the review offers numerous recommendations for research and development of the cutting-edge optimized energy management system applicable for homes, buildings, industries, electric vehicles, and the whole community.
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Metadata
- Authors
- Rathor, S. K., & Saxena, D.
- Venue
- International Journal of Energy Research
- Publisher
- Wiley
- Published
- 2020-05
- Volume
- 44
- Issue
- 6
- Pages
- 4067-4109
- ISSN
- 0363-907X (ISSN-L)
- 1099-114X
- OpenAlex
- W3003943177
- Cited by
- 494
- References
- 153
- FWCI
- 14.26
- Type
- journal article
- Language
- en
- Open access
- closed
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.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
