The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Neural-Network-Based MPPT Control of a Stand-Alone Hybrid Power Generation System
Abstract
A stand-alone hybrid power system is proposed in this paper. The system consists of solar power, wind power, diesel engine, and an intelligent power controller. MATLAB/Simulink was used to build the dynamic model and simulate the system. To achieve a fast and stable response for the real power control, the intelligent controller consists of a radial basis function network (RBFN) and an improved Elman neural network (ENN) for maximum power point tracking (MPPT). The pitch angle of wind turbine is controlled by the ENN, and the solar system uses RBFN, where the output signal is used to control the dc/dc boost converters to achieve the MPPT.
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Elman, J. L. (1990) · Cognitive Science · doi:10.1207/s15516709cog1402_1 · Cited by 11,212
Optimization of Perturb and Observe Maximum Power Point Tracking Method
Femia, N., Petrone, G., Spagnuolo, G., & Vitelli, M. (2005) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2005.850975 · Cited by 3,002
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Kellogg, W., Nehrir, M. H., Venkataramanan, G., & Gerez, V. (1998) · IEEE Transactions on Energy Conversion · doi:10.1109/60.658206 · Cited by 627
Output feedback control of nonlinear systems using RBF neural networks
Seshagiri, S., & Khalil, H. K. (2000) · IEEE Transactions on Neural Networks · doi:10.1109/72.822511 · Cited by 558
Wang, Q., & Chang, L. (2004) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2004.833459 · Cited by 555
Sensorless Output Maximization Control for Variable-Speed Wind Generation System Using IPMSG
Morimoto, S., Nakayama, H., Sanada, M., & Takeda, Y. (2005) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2004.841159 · Cited by 391
A decision support technique for the design of hybrid solar-wind power systems
Chedid, R. B., Akiki, H. B., & Rahman, S. (1998) · IEEE Transactions on Energy Conversion · doi:10.1109/60.658207 · Cited by 385
Dynamic multiphysics model for solar array
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Brunton, S. L., Rowley, C. W., Kulkarni, S. R., & Clarkson, C. (2010) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2010.2049747 · Cited by 328
Cited by
Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems
Verma, D., Nema, S., Shandilya, A. M., & Dash, S. K. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.10.068 · Cited by 420
Photovoltaic Model Identification Using Particle Swarm Optimization With Inverse Barrier Constraint
Soon, J. J., & Low, K.-S. (2012) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2012.2188818 · Cited by 276
Das, H. S., Salem, M., Zainuri, M. A. A. M., Dobi, A. M., Li, S., & Ullah, M. H. (2022) · Energy Reports · doi:10.1016/j.egyr.2022.10.407 · Cited by 32
Metadata
- Authors
- Lin, W.-M., Hong, C.-M., & Chen, C.-H.
- Venue
- IEEE Transactions on Power Electronics
- Published
- 2011-12
- Volume
- 26
- Issue
- 12
- Pages
- 3571-3581
- ISSN
- 0885-8993 (ISSN-L)
- 1941-0107
- OpenAlex
- W1978551974
- Cited by
- 347
- References
- 16
- FWCI
- 9.06
- Type
- journal article
- Language
- en
- Open access
- closed
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