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A feedforward controller for the automatic regulation of chemical composition of molten steel in the tundish of a continuous casting machine is proposed in this work. The flow of molten steel inside the tundish is modeled as a distributed parameter system, and the resulting partial differential equation is transformed into a set of ordinary differential equations by means of the finite differences technique. From the above set and using a proper boundary condition, a feedforward control law is synthesized. No experimental tests are reported, however, the dynamic performance of the controller is illustrated by means of numerical simulations.
This paper presents the modeling, simulation and practical implementation of an inverter-based diesel generator emulator. The main purpose of this emulator is for the study of frequency variations in diesel-based autonomous power systems in a laboratory environment where the operation of a real diesel generator is not possible. The emulator basically consists in a voltage source inverter with a second order output filter which voltage references are given by the model of the diesel generator. The control of the emulator is based on the digital signal processor TMS320F2812, where the mathematical models of the diesel generator and the control of the inverter are computed in real-time. Parameters for the model were obtained from commercially available components. Experimental results for different values of speed droop showed that the emulator achieves a satisfactory performance in the transient and stationary response. For the stationary response, the measured frequency deviates from theoretical values with a mean absolute error of: 0.06 Hz for 0% droop, 0.037 Hz for 3% droop, and 0.087 Hz for 5% droop. For the transient response, the measured frequency nadir deviates from simulations in: 0.05 Hz for 0% droop, 0.02 Hz for 3% droop, and 0.1 Hz for 5% droop.
Ideally, diesel hybrid autonomous power systems would operate with
high penetration of renewable energy sources such as wind and photovoltaic to
minimize fuel consumption. However, since these are inherently intermittent and
fluctuating, the grid-forming diesel engine generator sets are usually required
to operate with larger amounts of spinning reserve, often at low loading
conditions what tends to increases operating and maintenance costs. Frequency
stability is of great concern in “small” systems, such as mini-grids, where any
individual generator in-feed represents a substantial portion of the total
demand. There, the initial rate of change of frequency is typically larger and
a lower value of frequency can be reached in a shorter time than in
conventional systems with all generation supplied by rotating machines,
possibly resulting in under-frequency load shedding and tripping of renewable
energy generators. The first part of this paper, discusses some general
concepts regarding frequency stability in a diesel hybrid mini-grid and how
energy storage systems can be used to enhance system performance. Then, a
particular technique based on a virtual synchronous generator is presented and
its effectiveness is demonstrated with simulation results.
This paper addresses the problem of dynamic frequency control in a diesel-based mini-grid. It is shown that a virtual synchronous machine (VSM) can support dynamic frequency control by adding virtual inertia and damping to the system. However, it is found that the typical formulation of damping power does not work properly when the grid forming gen-set operates in droop mode because of the unknown stabilization value of the grid frequency. As a solution to this problem, an estimator for the stabilization frequency that works in conjunction with the damping function of the VSM is proposed. Theoretical and experimental results provide evidence of a satisfactory performance of the proposed VSM with estimator for different values of the gen-set droop factor. The estimated stabilization frequency converges in approximately 2 s and the maximum frequency deviation during the transient is reduced in 34%, on average.