Encyclopedia of Systems and Control

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Active Power Control of Wind Power Plants for Grid Integration

  • Lucy Y. PaoEmail author
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DOI: https://doi.org/10.1007/978-1-4471-5102-9_272-2


Increasing penetrations of intermittent renewable energy sources, such as wind, on the utility grid have led to concerns over the reliability of the grid. One approach for improving grid reliability with increasing wind penetrations is to actively control the real power output of wind turbines and wind power plants. Providing a full range of responses requires derating wind power plants so that there is headroom to both increase and decrease power to provide grid balancing services and stabilizing responses. Results thus far indicate that wind turbines may be able to provide primary frequency control and frequency regulation services more rapidly than conventional power plants.


Active power control Automatic generation control Frequency regulation Grid balancing Grid integration Primary frequency control Wind energy 


Wind penetration levels across the world have increased dramatically, with installed capacity growing at a mean annual rate of 17% over the last decade (Broehl and Asmus 2018). Some nations in Western Europe, particularly Denmark, Ireland, Portugal, Spain, the United Kingdom, and Germany, have seen wind provide more than 18% of their annual electrical energy needs (Wiser and Bolinger 2018). To maintain grid frequency at its nominal value, the electrical generation must equal the electrical load on the grid. This balancing has historically been left up to conventional utilities with synchronous generators, which can vary their active power output by simply varying their fuel input. Grid frequency control is performed across a number of regimes and time scales, with both manual and automatic control commands. Further details can be found in Diaz-Gonzalez et al. (2014) and Ela et al. (2011).

Wind turbines and wind power plants are recognized as having the potential to meet demanding grid stabilizing requirements set by transmission system operators (Ela et al. 2011; Aho et al. 2013a, b; Diaz-Gonzalez et al. 2014; Ela et al. 2014; Fleming et al. 2016). Recent grid code requirements have spurred the development of wind turbine active power control (APC) systems (Diaz-Gonzalez et al. 2014), in some cases mandating wind turbines to participate in grid frequency regulation and provide stabilizing responses to changes in grid frequency. The ability of wind turbines to provide APC services also allows them to follow forecast-based power production schedules.

For a wind turbine to fully participate in grid frequency control, it must be derated (to Pderated) with respect to the maximum power (Pmax) that can be generated given the available wind, allowing for both increases and decreases in power, if necessary. Wind turbines can derate their power output by pitching their blades to shed aerodynamic power or reducing their generator torque in order to operate at higher-than-optimal rotor speeds. Wind turbines can then respond at different time scales to provide more or less power through pitch control (which can provide a power response within seconds) and generator torque control (which can provide a power response within milliseconds) (Aho et al. 2016).

Wind Turbine Inertial and Primary Frequency Control

Inertial and primary frequency control is generally considered to be the first 5–30 s after a frequency event occurs. In this regime, the governors of capable generators actuate, allowing for a temporary increase or decrease in the utilities’ power outputs. The primary frequency control (PFC) response provided by conventional synchronous generators can be characterized by a droop curve, which relates fluctuations in grid frequency to a change in power from the utility. For example, a 3% droop curve means that a 3% change in grid frequency yields a 100% change in commanded power.

Although modern wind turbines do not inherently provide inertial or primary frequency control responses because their power electronics impart a buffer between their generators and the grid, such responses can be produced through careful design of the wind turbine control systems. While the physical properties of a conventional synchronous generator yield a static droop characteristic, a wind turbine can be controlled to provide a primary frequency response via either a static or time-varying droop curve. A time-varying droop curve can be designed to be more aggressive when the magnitude of the rate of change of frequency of the grid is larger.

Figure 1 shows a simulation of a grid response under different scenarios when 5% of the generating capacity suddenly goes offline. When the wind power plant (10% of the generation on the grid) is operating with its normal baseline control system that does not provide APC services, the frequency response is worse than the no-wind scenario, due to the reduced amount of conventional generation in the wind-baseline scenario that can provide power control services. However, compared to both the no-wind and wind-baseline cases, using PFC with a droop curve results in the frequency decline being arrested at a minimum (nadir) frequency fnadir that is closer to the nominal fnom = 60 Hz frequency level; further, the steady-state frequency fss after the PFC response is also closer to fnom. It is important to prevent the difference fnom − fnadir from exceeding a threshold that can lead to underfrequency load shedding (UFLS) or rolling blackouts. The particular threshold varies across utility grids, but the largest such threshold in North America is 1.0 Hz.
Fig. 1

Simulation results showing the capability of wind power plants to provide APC services on a small-scale grid model. The total grid size is 3 GW, and a frequency event is induced due to the sudden active power imbalance when 5% of generation is taken offline at time = 200 s. Each wind power plant is derated to 90% of its rated capacity. The system response with all conventional generation (no wind) is compared to the cases when there are wind power plants on the grid at 10% penetration (i) with a baseline control system (wind baseline) where wind does not provide APC services and (ii) with an APC system (wind APC) that uses a 3% droop curve where either 50% or 100% of the wind power plants provide PFC

Stability issues arising from the altered control algorithms must be analyzed (Buckspan et al. 2013; Wilches-Bernal et al. 2016). The trade-offs between aggressive primary frequency control and resulting structural loads also need to be evaluated carefully. Initial research shows that potential grid support can be achieved while not causing increases in average structural loading (Fleming et al. 2016). Further research is needed to more carefully assess how changes in structural loading affect fatigue damage and operations and maintenance costs.

Wind Turbine Automatic Generation Control

Secondary frequency control, also known as automatic generation control (AGC), occurs on a slower time scale than PFC. AGC commands can be generated from highly damped proportional integral (PI) controllers or logic controllers to regulate grid frequency and are used to control the power output of participating power plants. In many geographical regions, frequency regulation services are compensated through a competitive market, where power plants that provide faster and more accurate AGC command tracking are preferred.

An active power control system that combines both primary and secondary/AGC frequency control capabilities has been detailed in Aho et al. (2013a). Figure 2 presents experimental field test results of this active power controller, in response to prerecorded frequency events, showing how responsive wind turbines can be to both manual derating commands and rapidly changing automatic primary frequency control commands generated via a droop curve. Overall, results indicate that wind turbines can respond more rapidly than conventional power plants. However, increasing the power control and regulation performance of a wind turbine should be carefully considered due to a number of complicating factors, including coupling with existing control loops, a desire to limit actuator usage and structural loading, and wind variability.
Fig. 2

The frequency data input and power that is commanded and generated during a field test with a 550 kW research wind turbine at the US National Renewable Energy Laboratory (NREL). The frequency data was recorded on the Electric Reliability Council of Texas (ERCOT) interconnection (data courtesy of Vahan Gevorgian, NREL). The upper plot shows the grid frequency, which is passed through a 5% droop curve with a deadband to generate a power command. The high-frequency fluctuations in the generated power would be smoothed when aggregating the power output of an entire wind power plant

Active Power Control of Wind Power Plants

A wind power plant, often referred to as a wind farm, consists of many wind turbines. In wind power plants, wake effects can reduce generation in downstream turbines to less than 60% of the lead turbine (Barthelmie et al. 2009; Porté-Agel et al. 2013). There are many emerging areas of active research, including the modeling of wakes and wake effects and how these models can then be used to coordinate the control of individual turbines so that the overall wind power plant can reliably track the desired power reference command (Knudsen et al. 2015). A wind farm controller can be interconnected with the utility grid, transmission system operator (TSO), and individual turbines as shown in Fig. 3. By properly accounting for the wakes, wind farm controllers can allocate appropriate power reference commands to the individual wind turbines. Individual turbine generator torque and blade pitch controllers, as discussed earlier, can be designed so that each turbine follows the power reference command issued by the wind farm controller. Methods for intelligent, distributed control of entire wind farms to rapidly respond to grid frequency disturbances can significantly reduce frequency deviations and improve recovery speed to such disturbances (Boersma et al. 2019; Shapiro et al. 2017). Note that distributing a wind farm power reference among the operating individual wind turbines, in general, does not have a unique solution; further optimization can lead to structural load alleviation and thus prolongation of the operational lifespan of the individual wind turbines (Vali et al. 2019).
Fig. 3

Schematic showing the communication and coupling between the wind farm control system, individual wind turbines, utility grid, and the grid operator. The wind farm controller uses measurements of the utility grid frequency and automatic generation control power command signals from the grid operator to determine a power reference for each turbine in the wind farm

Summary and Future Directions

Ultimately, active power control of wind turbines and wind power plants should be combined with both demand-side management and storage to provide a more comprehensive solution that enables balancing electrical generation and electrical load with large penetrations of wind energy on the grid. Demand-side management (Callaway and Hiskens 2011; Palensky and Dietrich 2011) aims to alter the demand in order to mitigate peak electrical loads and hence to maintain sufficient control authority among generating units. As more effective and economical energy storage solutions (Pickard and Abbott 2012; Castillo and Gayme 2014) at the power plant scale are developed, wind (and solar) energy can then be stored when wind (and solar) energy availability is not well matched with electrical demand. Advances in wind forecasting (Pinson 2013; Okumus and Dinler 2016) will also improve wind power forecasts to facilitate more accurate scheduling of larger amounts of wind power on the grid. Finally, considering active power control in conjunction with reactive power and voltage control of wind power plants is also important for the stability and synchronization of the electrical power grid (Jain et al. 2015; Karthikeya and Schutt 2014).

Recommended Reading

A comprehensive report on active power control that covers topics ranging from control design to power system engineering to economics can be found in Ela et al. (2014) and the references therein.


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2020

Authors and Affiliations

  1. 1.University of ColoradoBoulderUSA

Section editors and affiliations

  • Joe Chow
    • 1
  1. 1.Electrical & Computer Systems Engineering, Rensselaer Polytechnic InstituteTroyUSA