The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
A Distributed Economic Dispatch Strategy for Power–Water Networks
Abstract
A power–water network consists of power plants, water plants, and coproduction plants, which supply power and water collectively. Heterogeneous plants generally have different costs when they produce water and power; thus, an optimization method should be employed to allocate the production tasks of the plants to reduce the total cost of the power–water network. This study investigates a continuous-time distributed algorithm for the economic dispatch problem of the power–water network. A conceptual model is first presented to illustrate the logical relationships within the power–water network, and then, a constrained nonlinear programming model is developed to describe the economic dispatch problem of the power–water network. The model not only includes the generation capacity constraints and supply–demand constraints but also considers the constraints on the power–water production ratios of the coproduction plants. A novel distributed algorithm is developed for the economic dispatch problem, which can guarantee a plug-and-play operation and preserve the privacy information of the plants in the power–water network. Some numerical results are given to demonstrate the performance and effectiveness of the proposed algorithm.
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Cites
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Cited by
Power System Monitoring for Electrical Disturbances in Wide Network Using Machine Learning
Wei, J., Chammam, A., Feng, J., Alshammari, A., Tehranian, K., Innab, N., Deebani, W., & Shutaywi, M. (2024) · Sustainable Computing: Informatics and Systems · doi:10.1016/j.suscom.2024.100959 · Cited by 25
Metadata
- Authors
- Li, P., Hu, J., Qiu, L., Zhao, Y., & Ghosh, B. K.
- Venue
- IEEE Transactions on Control of Network Systems
- Published
- 2022-03
- Volume
- 9
- Issue
- 1
- Pages
- 356-366
- ISSN
- 2325-5870 (ISSN-L)
- 2372-2533
- OpenAlex
- W4245409830
- Cited by
- 267
- References
- 26
- FWCI
- 15.12
- Type
- journal article
- Language
- en
- Open access
- closed
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