Development of Frequency Weighted Model Reduction Algorithm with Error Bound: Application to Doubly Fed Induction Generator Based Wind Turbines for Power System

The state-space representations grant a convenient, compact, and elegant way to examine the induction and synchronous generator-based wind turbines, with facts readily available for stability, controllability, and observability analysis. The state-space models are used to look into the functionality of different wind turbine technologies to fulfill grid code requirements. This paper deals with the model order reduction of the Variable-Speed Wind Turbines model with the aid of improved stability preserving a balanced realization algorithm based on frequency weighting. The algorithm, which is in view of balanced realization based on frequency weighting, can be utilized for reducing the order of the system. Balanced realization based model design uses a full frequency spectrum to perform the model reduction. However, it is not possible practically to use the full frequency spectrum. The Variable-Speed Wind Turbines model utilized in this paper is stable and includes various input-output states. This brings a complicated state of affairs for analysis, control, and design of the full-scale system. The proposed work produces steady and precise outcomes such as in contrast to conventional reduction methods which shows the efficacy of the proposed algorithm.

Design for Ease of Control and Estimation

Traditionally, a dynamic system is first designed then its controller is designed in a sequential process, which offers many organizational and computational advantages. However, this sequential design approach may not lead to system optimality compared to the combined design, or co-design, of the dynamic system and its controller. It has been proposed that a control proxy function (CPF) be used in the first step of this sequential design process to achieve, or approach, system-optimality. This paper considers the use of a CPF based on controllability and observability Gramians and a balanced realization to ensure the design of the dynamic system for both ease of control and estimation. The proposed approach is illustrated using an example of linear quadratic design for combined passive and active vibration control.