The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Distributed Optimal Energy Management for Energy Internet
Abstract
In this paper, a novel energy management framework for energy Internet with many energy bodies is presented, which features multicoupling of different energy forms, diversified energy roles, and peer-to-peer energy supply/demand, etc. The energy body as an integrated energy unit, which may have various functionalities and play multiple roles at the same time, is formulated for the system model development. Forecasting errors, confidence intervals, and penalty factor are also taken into account to model renewable energy resources to provide tradeoff between optimality and possibility. Furthermore, a novel distributed-consensus alternating direction method of multipliers (ADMM) algorithm, which contains a dynamic average consensus algorithm and distributed ADMM algorithm, is presented to solve the optimal energy management problem of energy Internet. The proposed algorithm can effectively handle the problems of power-heat-gas-coupling, global constraint limits, and nonlinear objective function. With this effort, not only the optimal energy market clearing price but also the optimal energy outputs/demands can be obtained through only local communication and computation. Simulation results are presented to illustrate the effectiveness of the proposed distributed algorithm.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
The Future Renewable Electric Energy Delivery and Management (FREEDM) System: The Energy Internet
Huang, A. Q., Crow, M. L., Heydt, G. T., Zheng, J. P., & Dale, S. J. (2011) · Proceedings of the IEEE · doi:10.1109/jproc.2010.2081330 · Cited by 1,463
Consensus Based Approach for Economic Dispatch Problem in a Smart Grid
Yang, S., Tan, S., & Xu, J.-X. (2013) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2271640 · Cited by 759
Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine
Wan, C., Xu, Z., Pinson, P., Dong, Z. Y., & Wong, K. P. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2287871 · Cited by 753
Distributed Consensus-Based Economic Dispatch With Transmission Losses
Binetti, G., Davoudi, A., Lewis, F. L., Naso, D., & Turchiano, B. (2014) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2014.2299436 · Cited by 477
Multi-Agent Distributed Optimization via Inexact Consensus ADMM
Chang, T.-H., Hong, M., & Wang, X. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2014.2367458 · Cited by 444
Sun, Q., Han, R., Zhang, H., Zhou, J., & Guerrero, J. M. (2015) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2015.2412779 · Cited by 401
Self-citationOptimal Power Dispatch of Multi-Microgrids at Future Smart Distribution Grids
Nikmehr, N., & Najafi Ravadanegh, S. (2015) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2015.2396992 · Cited by 377
Rahbari-Asr, N., Ojha, U., Zhang, Z., & Chow, M.-Y. (2014) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2014.2346511 · Cited by 309
Distributed Optimal Resource Management Based on the Consensus Algorithm in a Microgrid
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Cited by
Li, X., Ma, R., Gan, W., & Yan, S. (2022) · Journal of Modern Power Systems and Clean Energy · doi:10.35833/mpce.2020.000183 · Cited by 115
Metadata
- Authors
- Zhang, H., Li, Y., Gao, D. W., & Zhou, J.
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2017-12
- Volume
- 13
- Issue
- 6
- Pages
- 3081-3097
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W2622287519
- Cited by
- 284
- References
- 28
- FWCI
- 13.31
- Type
- journal article
- Language
- en
- Open access
- closed
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