Power boiler control loops optimal tuning

Kulessky, R.; Nudelman, G.

doi:10.1109/melcon.1998.692473

Cited by 10 publications

(2 citation statements)

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“…Thus paper presents a new approach of TFI for SISO models including the model order reduction as a part of its own identification procedure. Here we applied the principles of the approach previously of discussed in [15], [16]. 0885-8950/00$10.00 © 2000 IEEE The behavior of LFCUM described in this paper represents the significant dynamics of a 140 MW unit at the Haifa Power Station operating in the main regimes of its load-frequency control.…”

Section: B Identification Problemsmentioning

confidence: 99%

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Identification-based power unit model for load-frequency control purposes

Hain

Kulessky

Nudelman

2000

IEEE Trans. Power Syst.

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This paper presents a new method for process transfer function identification (TFI) and a new approach for the development of a power unit's dynamic model based on new applications for presented TFI method. This method uses a two-stage procedure which indirectly reduces both noise effects and the order of the transfer function. The first stage is the frequency response identification of a process, while the second one is the transfer function computation using frequency response obtained in the first stage. The power unit dynamic model which is identified using three relatively simple experiments is applied to load-frequency control. This dynamic model developed for the vicinity of the steady-state operation mode can be used for Automatic Generation Control purposes, to tune load-frequency control systems, as well as to build and set up a real-time simulator for dispatcher training. The modeling of 140 MW power units of the IEC (Israel) is fulfilled through implementation of this model and by its identification method yielding sufficiently good results.Index Terms-Boiler-turbine models, power system modeling, transfer function identification.

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Section: B Identification Problemsmentioning

confidence: 99%

“…Informative properties of a test signal are important in this case. The theorem in [16] applies to this problem.…”

Section: E the Problem Of Data Acquisition Needed For Identificationmentioning

confidence: 99%