**1. Introduction**

Wind energy emerged as the most promising renewable energy source (RES) in the world over the past few years. Since 2014, annual wind power installations have surpassed 50 GW each year on a global scale, bringing the total cumulative capacity up to 591 GW at the end of 2018 [1]. China is leading the global market with 206 GW of installed capacity, followed by the US (127 GW) and several EU countries. With a total installed capacity of 179 GW in the EU at the end of 2018, wind power had installed more capacity than any other type of electricity generation in the EU in that year [2], positioning itself as the second largest type of power generation capacity in the region.

In addition to the installed capacity, wind power plays a key role in electricity demand coverage. In the EU, wind power met 14% of the electricity demand in 2018 [2], which is 2% higher than in 2017. Denmark presents the highest share of wind energy in its electricity demand (41%) in the EU. Ireland, Portugal, Germany and Spain also exhibited a considerable contribution of wind power to demand coverage in 2018: 28%, 24%, 21% and 19%, respectively.

Network operators, either transmission system operators (TSOs) or distribution system operators (DSOs), perform transient stability analysis to correctly integrate the increasing penetration of wind power into the energy mix of current power systems. Dynamic wind turbine (WT) simulation models are required for this purpose [3]. However, in contrast to traditional synchronous generators, most WT models are not standardized or validated [4]. In this sense, the models developed by WT manufacturers are able to reproduce the behavior of their WTs with the greatest accuracy [5]. Nevertheless, the use of WT vendor models for transient stability analysis presents the following challenges: (i) they require specific simulation software [6], (ii) each vendor model is commonly subject to a non-disclosure agreemen<sup>t</sup> [7], (iii) each WT has specific controls depending on the manufacturer [8], (iv) increased accuracy is provided at the expense of increased complexity and number of parameters and, as a consequence, high computation time [9].

In light of the above considerations, the International Electrotechnical Commission published the Standard International Electronic Commission (IEC) 61400-27-1 in February 2015 [10]. IEC 61400-27-1 defined four generic WT models to conduct dynamic simulations of power system disturbances such as short-circuits. These generic models, also known as standard or simplified models, involve several assumptions and have several key properties, as follows:


Under this framework, the present paper performs the validation of six generic WT models based on the guidelines imposed by IEC 61400-27-1. For the first time in the literature, field campaigns conducted by three WT manufacturers, Siemens–Gamesa, Senvion and ENERCON, are used for the validation of three different WT technologies. Specifically, the variable-speed WT topologies, i.e., the doubly-fed induction generator (DFIG) and the full-scale converter, which represent the largest market share in current power systems, were submitted to voltage dips of different magnitude and duration. The validation methodology defined by the IEC 61400-27-1 was implemented to evaluate the accuracy of the generic WT models.

Following this introduction, the rest of the paper is structured as follows: Section 2 provides an overview of the current state of the art regarding variable-speed WTs, where the lack of field validation works is highlighted. Section 3 describes the methodology and testing procedure implemented in the present work, the results of which are provided in Section 4. Finally, Section 5 summarizes the main conclusions of the paper.

#### **2. Overview of Generic Variable-Speed WTs and Previous Field Validation Works**

MW-range WTs may be operated in two different ways: either fixed-speed or variable-speed operation. Fixed rotor speed is the oldest WT technology [15], while variable-speed is the most advanced technology and hence the current choice for every WT manufacturer [16]. Two different WT topologies are identified as variable-speed operation, Figure 1: the DFIG, also known as type 3 (Figure 1a), and the full-scale converter, also known as type 4 (Figure 1b).

**Figure 1.** Diagrams of the variable-speed wind turbines (WTs).

As shown in Figure 1, both of these variable-speed WT technologies include a bi-directional AC-DC/DC-AC converter. The main difference between them is the converter rated power: the converter is rated to 25–30% of the WT rated power for type 3 [17]; while the converter evacuates all the energy produced by the generator (either an induction generator, IG, or a synchronous generator, SG) in type 4. Hence, the type 4 generator is completely decoupled from the grid by the converter [18]. The power converter is composed of a machine (or rotor) side converter (MSC), a grid side converter (GSC) and the dc-link. Depending on the fault-ride trough (FRT) capability of the WT, the generic type 3 WT model is divided into two subtypes [10]: type 3A for WTs where the MSC and the chopper are sufficiently dimensioned for FRT without disconnecting the converter; and the type 3B, which is equipped with a crowbar device connected to the MSC in order to short-circuit the rotor when over-currents and over-voltages voltages are detected [19]. In fact, the type 3B WT is transformed into an induction generator with a rotor-connected resistance during crowbar activation [20]. In a similar way, two subtypes are also defined for the generic type 4 WT model: type 4A, which omits the aerodynamic and mechanical components due to the addition of a chopper in the dc-link; and type 4B, where choppers are not included and hence post-fault power oscillations are present.

Due to the complex behavior of variable-speed WTs, and taking into account the particular features of the generic IEC WT models listed in Section 1, there is little previous literature on the validation of these models. Two of the first contributions are found in [20,21], where both generic type 3 models, type 3B and type 3A, respectively, were validated with a 2 MW based WT operating at full-load conditions against one voltage dip test case. A generic type 4B model was validated against one voltage dip in [22], where the post-fault power oscillations were clearly observed. Generic type 3B and type 4A models, both from the same vendor, were validated in [5,8,12] based on the field results obtained from several test cases. It should be noted that the authors of the present work collaborated in most of the previously cited contributions, as well as being members of Working Group 27 of the IEC Technical Committee 88 in charge of the development of IEC 61400-27.

Under this framework, it can be clearly observed that the field validation of generic WT models is a current topic of interest in the wind power industry. Nevertheless, the number of contributions found in the literature is limited. Furthermore, there is a lack of contributions with the involvement of several WT manufacturers and this is the gap the present paper aims to fill. Since each WT vendor has specific controls, the FRT response of each actual WT is different. Hence, the validation of several WT topologies provided by different manufacturers is the key contribution of the present paper.

#### **3. Description of the Validation Methodology and Testing Procedure**

Validating a model consists of comparing the emulated response with the measured data from field tests, both referring to the same wind turbine terminals (WTT). According to IEC 61400-27-1 [10], the measured and simulated data should be represented in per unit (pu) values based on the nominal

active power and the nominal voltage at the WTT. The results of the validation procedure will include the following parameters:


$$\mathbf{x}\_E(n) = \mathbf{x}\_{field}(n) - \mathbf{x}\_{sim}(n) \tag{1}$$

• Three key validation errors are estimated for the previous error time series: mean error (*xME*), Equation (2), mean absolute error (*xMAE*), Equation (3) and maximum absolute error (*xMXE*), Equation (4).

$$\mathbf{x}\_{ME} = \frac{\sum\_{n=1}^{N} \mathbf{x}\_E(n)}{N} \tag{2}$$

$$\mathbf{x}\_{MAE} = \frac{\sum\_{n=1}^{N} |\mathbf{x}\_{E}(n)|}{N} \tag{3}$$

$$\|\mathbf{x}\_{MXE} = \max\left( |\mathbf{x}\_E(1)|, |\mathbf{x}\_E(2)|, \dots, |\mathbf{x}\_E(N)| \right) \tag{4}$$

Three different fault windows (*W*) are considered for the estimation of each key validation error, as represented with different colors in Figure 2: (i) a pre-fault window lasting 1000 ms before the fault occurs at *tf ault* (this is the first time the voltage dip occurs in one of the phases); (ii) a fault-window that covers a time period from *tf ault* to the fault clearance, *tclear*; (iii) a post-fault window lasting 5000 ms after *tclear*. As observed in Figure 2, two quasi-steady state (QS) sub-windows were defined during both fault and post-fault periods. These QS sub-windows are used to avoid a misunderstanding of the validation errors due to electromagnetic transients that could appear in the field but are outside the scope of root mean square (RMS) simulations. The calculation of the final validation errors at each window is summarized in Table 1.

**Figure 2.** Voltage dip validation windows.

**Table 1.** Windows used for the estimation of the validation errors.


Furthermore, the validation methodology defined by IEC 61400-27-1 includes two different approaches to represent the grid model. On the one hand, the full system simulation approach considers the modeling of the whole system composed of the equivalent grid, the interface between the grid and the WT and the generic WT model [23]. On the other hand, the play-back approach involves only the WT being modeled and the measured voltage being directly played-back into the generic WT model. Therefore, the play-back validation methodology is recommended for assessing the accuracy of the generic WT model as the uncertainties related to grid and test equipment models are reduced.

FRT mobile test units were used to perform the field tests and measurements of the actual WTs. Figure 3 shows several photos of the different field campaigns carried out by the manufacturers involved in the present work: Siemens–Gamesa (Figure 3a), Senvion (Figure 3b) and ENERCON (Figure 3c), to perform the field tests used for the validation of the generic IEC WT models.

(**a**) Siemens–Gamesa.

(**b**) Senvion.

(**c**) ENERCONc .

**Figure 3.** Photos of the field campaigns carried out by the WT manufacturers.

The validation methodology previously described, as well as the FRT mobile units, were used to perform six different field tests for the validation of the generic WT models, as shown in Table 2. Three different WT topologies (Type 3A, Type 3B and Type 4A) from three WT manufacturers were considered. Siemens–Gamesa implemented the play-back validation methodology, while Senvion and ENERCON deployed the full system simulation approach. A wide range of voltage dip characteristics (residual voltage and dip duration) were also considered. It should be noted that the residual voltage shown in Table 2 is based on the measurement guidelines defined by IEC 61400-21-1 [24]. This means that the field test is defined by a voltage dip without a WT and, subsequently, when the WT is connected and the test is performed, the final residual voltage may increase due to the actual reactive current injection.


**Table 2.** Description of the validation tests performed.
