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Dual-Kalman-Filter-Based Identification and Real-Time Optimization of PV Systems
- Source :
- IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Electronics, Institute of Electrical and Electronics Engineers, 2015, 62 (11), pp.7266-7275. ⟨10.1109/TIE.2015.2475240⟩
- Publication Year :
- 2015
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2015.
-
Abstract
- In this paper, the use of the Dual Kalman Filter for the identification of photovoltaic system parameters is presented. The system includes the photovoltaic source, the dc/dc converter and the battery/dc bus and both its states and parameters in the actual operating conditions are identified. In particular, the proposed approach gives the confidence interval for the system settling time, which is used for the real-time optimization of the perturbative maximum power point tracking algorithm. The proposed technique is implemented by using a Field-Programmable Gate Array and it is validated by means of both simulation and experimental results.
- Subjects :
- Optimization
field programmable gate array
Engineering
dual Kalman filter
optimisation
Covariance matrices
Settling time
power system parameter estimation
DC-DC converter
battery-DC bus
dual-Kalman filter-based identification
7. Clean energy
photovoltaic system parameter identification
[SPI]Engineering Sciences [physics]
Extended Kalman filter
Mathematical model
Control theory
Gate array
Electronic engineering
PV system real-time optimization
Electrical and Electronic Engineering
real-time optimization
Real-time systems
ComputingMilieux_MISCELLANEOUS
field programmable gate arrays
DC/DCconverters
system identification
photovoltaic power systems
real-timeoptimization
business.industry
Photovoltaic system
System identification
maximum power point trackers
Computer Science Applications1707 Computer Vision and Pattern Recognition
Kalman filter
DC-BUS
Power optimizer
photovoltaic system
Kalman filters
perturbative maximum power point tracking algorithm
Estimation
Noise
photovoltaic systems
Control and Systems Engineering
business
Subjects
Details
- ISSN :
- 15579948 and 02780046
- Volume :
- 62
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Industrial Electronics
- Accession number :
- edsair.doi.dedup.....2c5cdc91f17917a30f89a0393a03dcd1