Online estimation of Equivalent Model for cluster of induction generators: A MVMO-based approach

Rueda, J.L.; González-Longatt, Francisco; Erlich, I.

doi:10.1109/isap.2015.7325559

Cited by 2 publications

(1 citation statement)

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“…If appropriate measurement data of the system's input and outputs are available, the system identification process is straightforward. In this case, the system identification is performed considering the structure of the dynamic model is known: the synchronous generator, the governor, and the steam turbine model [1], [16], [17]. The identification can be easily formulated as an optimisation problem where the target is minimising the error between the measured output (Ymeas) and the output obtained from simulations (Ysim):…”

Section: Prepare System Identificationmentioning

confidence: 99%

System Parameter Identification of Thermal Generation Unit in the Mongolian Electrical Grid: Real-Life Frequency Response Test

Adiyabazar¹,

González-Longatt

Acosta

et al. 2021

2021 IEEE PES Innovative Smart Grid Technologies Conference - Latin America (ISGT Latin America)

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Mongolian power grid (MPG) is becoming more eco-friendly as the power system is continuously integrating renewable energy, which reached 20% of the total installed capacity of Mongolia in 2020. With such growth of renewable energy in the system, the daily operation and the safety of the MPG has become a challenge. Therefore, the dynamic behaviour of conventional power plants (CPPs) must be demonstrated to fulfil the requirements of integrating more renewable energy in the MPG, especially for frequency stability. This paper illustrates the results of the system parameter identification of an actual steam turbine and a governor system with PID controller by using a real-life test performed on Generator 1 (G1) of the biggest thermal power plant (TPP-4) in Mongolia on 6 th March 2020. The main contribution of this paper is to clear uncertainties about the PID controller's parameters installed in the steam turbine of G1 in early 2019, as a consequence, giving the system operator an accurate dynamic model of the generation unit. The steam turbine and governor are modelled in DIgSILENT® PowerFactory, and the Particle Swarm Optimization (PSO) method is used for identifying the parameters of the PID controller of the G1 at TPP-4. Simulation results from the PowerFactory software matched firmly (error <0.3%) with the measured frequency from the Phasor Measurement Unit (PMU).

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Section: Prepare System Identificationmentioning

confidence: 99%