The increasing penetration of wind power presents many technical challenges to power system operations. An important challenge is the need of voltage control to maintain the terminal voltage of a wind plant to make it a PV bus like conventional generators with excitation control. In the previous work for controlling wind plant, especially the Doubly Fed Induction Generator (DFIG) system, the proportional-integral (PI) controllers are popularly applied. These approaches usually need to tune the PI controllers to obtain control gains as a tradeoff or compromise among various operating conditions. In this paper, a new voltage control approach based on a different philosophy is presented. In the proposed approach, the PI control gains for the DFIG system are dynamically adjusted based on the dynamic, continuous sensitivity which essentially indicates the dynamic relationship between the change of control gains and the desired output voltage. Hence, this control approach does not require any good estimation of fixed control gains because it has the self-learning mechanism via the dynamic sensitivity. This also gives the plug-and-play feature of DFIG controllers to make it promising in utility practices. Simulation results verify that the proposed approach performs as expected under various operating conditions.
The global warming problem has received increasing concerns due to pollutant emission, significant portion of which is produced by the conventional thermal power plant fueled by coal and natural gas. As an important solution to reduce the emission from power generation, renewable energy resources are growing fast in many countries. Among all renewables, wind energy is the most outstanding one. In the US, most of the states have Renewable Portfolios Standard, which is an individual state-wide policy aiming at achieving a certain percentage of their power from renewable energy sources by a certain date, typically targets a range from 10% to 20% of total capacity by 2020. However, the increasing penetration of renewable energy sources, in particular, wind energy conversion system (WECS), in the conventional power system has put tremendous challenges to the power system operators and planners [
These challenges include the optimal scheduling of wind power from the longer-term viewpoint, as well as the stability and control issues from the shorter-term viewpoint. Here, this paper is aimed to address the challenge of maintaining a stable voltage profile because the voltage and reactive power control is a pressing issue for DFIG integration. Further, since a wind plant, usually modeled as a PV bus like other generator buses, must maintain a given voltage schedule, investigation of voltage regulation from the dynamic study is a realization of a DFIG bus as a PV bus.
A doubly fed induction generator (DFIG) gives better wind energy transfer efficiency as opposed to other wind generators. They can also offer significant enhancement for transmission support regarding voltage control, transient performance, and damping [
The decoupled control of DFIG has been popular in recent research. It has four controllers, named
Many previous works in gain tuning for DFIG are based on some optimization approaches to reach a tradeoff or compromise such that the wind system can achieve good, but not always the best performance under various operating conditions and avoid worst-case performance under some extreme conditions. Different from these previous approaches for DFIG control, this research work uses a different philosophy to achieve ideal performance based on dynamic tuning of control gains for a DFIG-based wind system. A similar philosophy has been successfully applied in [
The wind turbine doubly fed induction generator (DFIG) system is shown in
The control system generators voltage signals to control the power output, terminal voltage, and DC voltage. There are three control parts: Rotor Side Control, Grid Side Control, and Pitch Angel Control.
The rotor-side converter is used to control the wind turbine power output and the voltage measured at the grid terminal. The wind power output is controlled to follow a pre-defined curve, see
The rotor side control loop is illustrated in
As shown in
As shown in
The grid side control system is illustrated in
A proportional-integral (PI) controller is used to reduce the error between
The pitch angle is kept constant at zero degree until the wind speed reaches a specified value (see
When there is a drop of the terminal voltage of the DFIG due to wind speed change or load change, it needs to quickly recover to its scheduled value pre-defined by operators. In the proposed approach, we first define an exponential curve, as illustrated in
dule). The transition from
Here, a period of
the operators prefer the voltage rise time is
Next, the PI controllers with dynamical adjustment are applied to reduce the error between the actual voltage response and the ideal (desired) response to zero. Initially, very small values of the PI controller gains are applied, which lead to a large error. However, the control gains may be gradually increased to speed up the reduction of the error such that the actual voltage may catch up the desired voltage regulation curve. The increasing pattern may be stopped when the actual voltage curve is aligned with the desired curve. The above process is somewhat similar to accelerate a moving object to catching another moving target at the desired velocity. Once the object reaches the desired velocity, the acceleration may be stopped (to avoid overshoot).
Hence, the above control process differs from conventional PI control and/or gain tuning because of the dynamic adjustment of the PI control gains during the voltage regulation process, while conventional PI control uses fixed control gains during the process or different control gains under different scenarios. Since the proposed control process starts with a small value of control gains, it will not have the overshoot problem at the very beginning. Then, the gains will be gradually increased such that the actual voltage response can “speed up” to eventually catch up the desired response curve.
Next, more technical details are elaborated.
The second fixed-gain (i.e.,
The sampling frequency is usually very high (at the level of multiple kHz) so
We may define a sensitivity
This sensitivity
In this DFIG design,
Since
In DFIG, the positive sequence phasor model for the asynchronous machine can be written as
Hence, we have
With
where,
Here,
where,
Then, we have
Since
Therefore, we have
To ensure
Equation (15) gives the upper bound of the initial value of the control gains. It can guarantee that
The key of the proposed control is to dynamically adjust the control gains,
The value of
The effect of the integral part is set roughly equal to the effect of the proportional part when the difference between the reference and the terminal voltage reaches the maximum. If the time needed for the process is
Also, we consider the control gains are changed by a co-efficient
Assuming the “catching-up” process ends after
where
where
Hence, the value of
The goal of the proposed method is to control the terminal voltage such that it can reach the final value smoothly following the ideal response curve as much as possible. At the beginning of this voltage control process, the error between the reference and the voltage increases and essentially reaches the peak value. Then, it starts to decrease. As previously described, here the dynamically adjusted control gains play as the “acceleration factor” or “de-acceleration factor” during this control process. By doing so, the voltage error may go to zero without going to negative (i.e., overshoot). Thus, there should be a maximal value of
With (12), we can obtain
It is necessary to ensure the following equation such that there will not be any overshoot
Hence, we have
Therefore, we have
To ensure that
The whole control process is briefly presented in the flowchart shown in
The power system under study is as shown in
In this section, first, a demonstration of inappropriate fixed PI gains is shown to verify the importance of PI gains. Then, several case studies are carried out to illustrate that the proposed approach of dynamically adjusted PI gains can achieve desired performance under various operating conditions.
As previously mentioned in Sections 1 and 2, the motivation of this paper is to present an approach to avoid the potential instability raised by fixed control gains. With inappropriate
to 1.01 p.u. to mimic a small disturbance. Control gains of
As mentioned in the opening part in Section 3, users may define the desired time to regulate the terminal voltage from the time of disturbance to the final steady-state value. Here the transient time for voltage is set to 0.5 seconds since this is fast enough before other conventional (usually much slower) voltage controls take effect or are activated. Since an exponential decay of the voltage difference, i.e.,
In this case study, a step change of voltage reference is made from 1.0 to 1.01 per unit. The dynamically adjusted control gains are employed. As shown in
Different loads may have different effects on the terminals voltage of the wind turbine DFIG system. Hence, three additional case studies are performed. These cases are similar to Case One, but differ in the amount of load. Considering the load in Case One is 500 kW, the load levels in Cases Three, Four, and Five are changed to 200 kW, 800 kW, and 1100 kW, respectively. The results of the three most important variables, voltage error in p.u., voltage in p.u., and
As observed in these figures, the proposed control approach gives dynamically adjusted control gain
In this paper, a new DFIG voltage control approach based on a philosophy different from the previous works is presented. In the proposed approach, the PI control gains for the DFIG system are dynamically adjusted based on the dynamic, continuous sensitivity which essentially indicates the dynamic relationship between the change of control gains and the desired output voltage. Hence, this control approach does not require any good estimation of fixed control gains because it has the self-learning mechanism via the dynamic sensitivity. This also gives the plug-and-play feature of the proposed DFIG controller to make it promising in utility practices. Simulation results verify that the proposed approach performs as expected under various operating conditions.
Future works may include the study of multiple wind plants in a system as well as the control of real power especially when an energy storage system is connected to the wind plant.
This work made use of engineering research center shared facilities supported by the engineering research center program of the national science foundation and the department of energy under NSF award Number EEC- 1041877 and the CURENT industry partnership program. Thanks so much to my supervisor, Dr. Fangxing “Fran” Li’s great help and guidance.