A Feedback Linearization Scheme for the Control of Synchronous Generators

Abstract

This paper proposes an advanced nonlinear control algorithm to manage active power and voltage provided by a synchronous generator. The algorithm is based on the so-called FeedBack Linearization (FBL) theory, which relies on the central concept to algebraically transform nonlinear systems dynamics into fully or partly linear ones, so that linear control techniques can be applied. Starting from the basic (electrical, magnetic and mechanical) machine equations, a suitable state transformation is introduced in order to apply the FBL block to the generator model. A regulation scheme is then derived, which receives as input the measure and the reference signals of both the electric power and the voltage at the generator side and produces as outputs the physical inputs of the machine, i.e. the mechanical torque and the field voltage. Particular attention is devoted both to the linearization process, where internal dynamics and stability studies play an important role, and to the design of the two (Power and Voltage) decoupled regulators. Several simulations are finally performed in order to verify the effectiveness of the proposed approach and to highlight its main advantages and drawbacks with respect to the traditional P-V synchronous generator control strategy

Inertial frequency response provided by battery energy storage systems: Probabilistic assessment

“…It consists of two synchronous generators (P n = 400 MVW, H = 5.0 sec) connected to an equivalent transmission system, where a 50 MW BESS in connected. The synchronous generator is equipped with GAST governor and IEEE Type I AVR [20]. The full model of the BESS has been developed using DigSILENT Simulation Language (DSL) consider the previous section models, and the BESS has been enabled to provide system frequency response using an inertia frequency response controller.…”

Tuning and Feasibility Analysis of Classical First-Order MIMO Non-Linear Sliding Mode Control Design for Industrial Applications

“…where x di is the ith state desired trajectory. The control problem can be solved by choosing the command laws as [34]: (14) in which: (16) and:…”

“…This fact, combined with the current more and more pressing issue of increased efficiency in each industrial field (e.g., in power generation [1][2][3][4], the transport sector [5][6][7], energy utilization [8,9], renewable energy [10][11][12], and so on), strongly favors the development and implementation of more sophisticated control theories, such as model-based ones. Among model-based control techniques experiencing wide popularity, model predictive control (MPC) [13][14][15], feedback linearization (FBL) [16,17], and sliding mode (SM) control [18] stand out. In particular, the SM control theory has been receiving growing interest since the early 1970s [19] and has found application in numerous industrial applications; to name a few, it was employed in References [20,21] for photovoltaic systems, in References [22,23] for gas turbines, in Reference [24], and Reference [25] for hybrid electric vehicles, and the list goes on.…”

Implementation of primary frequency regulation on fully rated wind turbine generators

“…The proposed WT employs a full-rated power converter (FRPC) configuration. The structure modelled for this paper is characterized with the data available in [16][17][18], but escalated to represent an equivalent 3 MW WT. Instead, Figure 4 displays a block scheme of the controller suited to a VSWT with a DD (direct drive) synchronous generator interfaced to the main grid by mean of a FRPC.…”