The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Self-Organizing Hierarchical Particle Swarm Optimization for Nonconvex Economic Dispatch
Abstract
The economic dispatch has the objective of generation allocation to the power generators in such a manner that the total fuel cost is minimized while all operating constraints are satisfied. Conventional optimization methods assume generator cost curves to be continuous and monotonically increasing, but modern generators have a variety of nonlinearities in their cost curves making this assumption inaccurate, and the resulting approximate dispatches cause a lot of revenue loss. Evolutionary methods like particle swarm optimization perform better for such problems as no convexity assumptions are imposed, but these methods converge to sub-optimum solutions prematurely, particularly for multimodal problems. To handle the problem of premature convergence, this paper proposes to apply a novel self-organizing hierarchical particle swarm optimization (SOH_PSO) for the nonconvex economic dispatch (NCED). The performance further improves when time-varying acceleration coefficients are included. The results show that the proposed approach outperforms previous methods for NCED.
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Cites
Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192
Power Generation, Operation, and Control
Wood, A. J., & Wollenberg, B. F. (1984) · Cited by 8,303
Empirical study of particle swarm optimization
Shi, Y., & Eberhart, R. C. (2003) · Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406) · doi:10.1109/cec.1999.785511 · Cited by 3,945
Self-Organizing Hierarchical Particle Swarm Optimizer With Time-Varying Acceleration Coefficients
Ratnaweera, A., Halgamuge, S. K., & Watson, H. C. (2004) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2004.826071 · Cited by 3,034
Comparing inertia weights and constriction factors in particle swarm optimization
Eberhart, R. C., & Shi, Y. (2002) · Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512) · doi:10.1109/cec.2000.870279 · Cited by 2,966
Particle swarm optimization to solving the economic dispatch considering the generator constraints
Gaing, Z.-L. (2003) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2003.814889 · Cited by 1,715
Evolutionary programming techniques for economic load dispatch
Sinha, N., Chakrabarti, R., & Chattopadhyay, P. K. (2003) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2002.806788 · Cited by 1,270
Fuzzy adaptive particle swarm optimization
Shi, Y., & Eberhart, R. C. (2002) · Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546) · doi:10.1109/cec.2001.934377 · Cited by 1,071
A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems
Selvakumar, A. I., & Thanushkodi, K. (2007) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2006.889132 · Cited by 829
Optimal design of power-system stabilizers using particle swarm optimization
Abido, M. A. (2002) · IEEE Transactions on Energy Conversion · doi:10.1109/tec.2002.801992 · Cited by 714
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Wang, D., Tan, D., & Liu, L. (2018) · Soft Computing · doi:10.1007/s00500-016-2474-6 · Cited by 3,343
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
Differential evolution with multi-population based ensemble of mutation strategies
Wu, G., Mallipeddi, R., Suganthan, P. N., Wang, R., & Chen, H. (2016) · Information Sciences · doi:10.1016/j.ins.2015.09.009 · Cited by 569
Zhang, Y., Gong, D.-W., & Ding, Z. (2012) · Information Sciences · doi:10.1016/j.ins.2011.06.004 · Cited by 288
Metadata
- Authors
- Chaturvedi, K. T., Pandit, M., & Srivastava, L.
- Venue
- IEEE Transactions on Power Systems
- Published
- 2008-08
- Volume
- 23
- Issue
- 3
- Pages
- 1079-1087
- ISSN
- 0885-8950 (ISSN-L)
- 1558-0679
- OpenAlex
- W2131680865
- Cited by
- 485
- References
- 15
- FWCI
- 22.41
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chaturvedi, K. T., Pandit, M., & Srivastava, L. (2008). Self-Organizing Hierarchical Particle Swarm Optimization for Nonconvex Economic Dispatch. IEEE Transactions on Power Systems. https://doi.org/10.1109/tpwrs.2008.926455
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