The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Consensus + Innovations Approach for Distributed Multiagent Coordination in a Microgrid
Open accessAbstract
Distributed energy resources and demand-side management are expected to become more prevalent in the future electric power system. Coordinating the increased number of grid participants in an efficient and reliable way is going to be a major challenge. A potential solution is the employment of a distributed energy management approach, which uses intelligence distributed over the grid to balance supply and demand. In this paper, we specifically consider the situation in which distributed resources and loads form microgrids within the bulk power system in which the load is supplied by local generation. A distributed energy management approach based on the consensus + innovations method is presented and used to coordinate local generation, flexible load, and storage devices within the microgrid. The approach takes advantage of the fact that, at the optimal allocation settings, the marginal costs given as a function of the power output/consumption need to be equal for all nonbinding network resources. Solutions for single time step, as well as multitime step optimization including intertemporal constraints, are presented.
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Cites
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
Consensus and Cooperation in Networked Multi-Agent Systems
Olfati-Saber, R., Fax, J. A., & Murray, R. M. (2007) · Proceedings of the IEEE · doi:10.1109/jproc.2006.887293 · Cited by 10,522 · cited 1×
“Historically, this version of the restricted agreement problem is referred to as the average consensus problem or simply the agreement problem and has been studied extensively over the last few years (see [22], [23]).”
Background
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A survey of distributed optimization
Yang, T., Yi, X., Wu, J., Yuan, Y., Wu, D., Meng, Z., Hong, Y., Wang, H., Lin, Z., & Johansson, K. H. (2019) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2019.05.006 · Cited by 913
Bilateral Contract Networks for Peer-to-Peer Energy Trading
Morstyn, T., Teytelboym, A., & Mcculloch, M. D. (2019) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2017.2786668 · Cited by 543
Multiclass Energy Management for Peer-to-Peer Energy Trading Driven by Prosumer Preferences
Morstyn, T., & McCulloch, M. D. (2019) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2018.2834472 · Cited by 533
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Metadata
- Authors
- Hug, G., Kar, S., & Wu, C.
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2015-07
- Volume
- 6
- Issue
- 4
- Pages
- 1893-1903
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W2042225379
- Cited by
- 352
- References
- 2
- FWCI
- 26.60
- Type
- journal article
- Language
- en
- Open access
- green
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