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An Intelligent Auction Scheme for Smart Grid Market Using a Hybrid Immune Algorithm
Abstract
Smart Grid technology is recognized as a key component of the solution to challenges such as the increasing electric demand, an aging utility infrastructure and workforce, and the environmental impact of greenhouse gases produced during electric generation. This paper presents the application of a hybrid optimization algorithm for distributed energy resource (DER) management in Smart Grid operation. The approach emphasizes the advantages of using multiagent systems for profitable operation of a Smart Grid in the energy market. The trading strategy adopted for the auction process is a profit-maximizing adaptive bidding strategy based on risk and competitive equilibrium price prediction. The auctioneer manages the usage of DERs by receiving bids from buyers and asks from sellers. A hybrid-immune-system-based particle swarm optimization is used to minimize the fuel cost for generation assuming realistic market prices for power, distributed generator bids reflecting realistic operational costs, and load bids customized according to the consumers' priorities. The simulation results clearly indicate that the agent-based management is effective in coordinating the various DERs economically and profitably.
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Cites
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
Cited by
Smart Grid — The New and Improved Power Grid: A Survey
Fang, X., Misra, S., Xue, G., & Yang, D. (2012) · IEEE Communications Surveys & Tutorials · doi:10.1109/surv.2011.101911.00087 · Cited by 3,405
A Survey on the Edge Computing for the Internet of Things
Yu, W., Liang, F., He, X., Hatcher, W. G., Lu, C., Lin, J., & Yang, X. (2018) · IEEE Access · doi:10.1109/access.2017.2778504 · Cited by 1,520
A literature review of microgrids: A functional layer based classification
Martin-Martínez, F., Sánchez-Miralles, A., & Rivier, M. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2016.05.025 · Cited by 239
Eren, Y., Küçükdemiral, İ. B., & Üstoğlu, İ. (2017) · Optimization in Renewable Energy Systems · doi:10.1016/b978-0-08-101041-9.00002-8 · Cited by 67
Metadata
- Authors
- Ramachandran, B., Srivastava, S. K., Edrington, C. S., & Cartes, D. A.
- Venue
- IEEE Transactions on Industrial Electronics
- Published
- 2011-10
- Volume
- 58
- Issue
- 10
- Pages
- 4603-4612
- ISSN
- 0278-0046 (ISSN-L)
- 1557-9948
- OpenAlex
- W2168991848
- Cited by
- 193
- References
- 1
- FWCI
- 9.22
- Type
- journal article
- Language
- en
- Open access
- closed
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- Ramachandran, B., Srivastava, S. K., Edrington, C. S., & Cartes, D. A. (2011). An Intelligent Auction Scheme for Smart Grid Market Using a Hybrid Immune Algorithm. IEEE Transactions on Industrial Electronics. https://doi.org/10.1109/tie.2010.2102319
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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.
