Simulation of dfig based wind turbine using mmc converter in MATLAB

Simulation of dfig based wind turbine using mmc converter in MATLAB

MATLABSolutions demonstrate how to Implementation of The application of the MMC is a system that connects wind power to a grid through high-voltage direct current (HVDC) in the form of back-to-back connected MMCs, whereas a HILS is a system used to test or develop hardware or a software algorithm with real time.

A real-time operation model of the MMC is required to conduct a HILS experiment. Although some studies have introduced the HILS model of MMCs for grid connection using PSCAD/EMTDC, it is difficult to find a study in the literature on the model using Matlab/Simulink, which is widely used for power electronic simulation

Abstract

In this study, we propose a wind power generation system model for operating modular multilevel converter (MMC) in a hardware-in-the-loop simulation (HILS) application. The application of the MMC is a system that connects wind power to a grid through high-voltage direct current (HVDC) in the form of back-to-back connected MMCs, whereas a HILS is a system used to test or develop hardware or a software algorithm with real time. A real-time operation model of the MMC is required to conduct a HILS experiment. Although some studies have introduced the HILS model of MMCs for grid connection using PSCAD/EMTDC, it is difficult to find a study in the literature on the model using Matlab/Simulink, which is widely used for power electronic simulation. Hence, in this paper, we propose a real-time implementation model employing a detailed equivalent model (DEM) using MATLAB/Simulink. The equivalent model of both wind power generation system and MMC are presented in this paper. In addition, we describe how to implement components such as a variable resistor that is not provided in the Simulink's library. The feasibility of the proposed model is demonstrated with real-time operation of a wind power generation system.

Introduction

Power converters are characterized by a variable structure behavior. The development of new conversion systems leads always to new modeling approaches or methodologies. One of the most important issue related to the MMC is concerning its modeling for different reasons: very huge number of state variables (large mathematical dimension), strong coupling of these variables and large set of dynamics behavior. This chapter is dedicated to the MMC modeling aspects. After a state of the art base on recent bibliography references, thesis contributions in the field of MMC general modeling are explained and developed. To finish, the proposed models are implemented, assessed and validated.

Model categories

A model is always a simplified representation of a given real process, system or object. The ideal and perfect model must be accurate, fast, and easy to build and to implement. However, this perfect model is not existing, it is always a compromise between all these requirements. The modeling step is essential to understand, to control, to design and/or optimize, to assess, to observe and to predict the behavior of a system.

• Understanding: In power system, models can be used to explain and predict the behavior of real equipment or process.
• Observing, predicting: For the benefit of power system operation, there is a need to perform various measurements at different nodes of the network with the most possible accurate values. However, it is not possible economically to have measurement devices at any node in the grid. Hence, it is necessary to develop component models using state estimation method to get a good estimated value of the given variables.
• Sizing/ optimizing: A model is also required in order to design a component. In the same aim as above, the use of model allows the determination of the constraints applied to the component. Moreover, it allows engineers to reach a given objective by choosing an adapted set of decision variables.
• Controlling: The control design needs specific models. Depending on the control law type, these models can be linear or nonlinear; time domain or frequency domain, continuous or discrete. They can be obtained from the system knowledge or from experiment tests.

According to how the model is interpreted and for which purpose it will be dedicated, the representation of a model may be different from one to another goal. For example, a model which is used for control purposes can be different to the ones used for circuit design or load flow calculation. Consequently, the users must narrow the type of models by identifying the requirements that must be fulfilled. To simplify, only the elements that are thought to play an important role and to reproduce the investigated phenomena must be considered.