Jiaqi Liang

Feed-Forward Transient Current Control for Low-Voltage Ride-Through Enhancement of DFIG Wind Turbines

High penetration of wind power requires reliable wind energy generation. A successful low-voltage ride-through (LVRT) scheme is a key requirement to achieve reliable and uninterrupted electrical power generation for wind turbines equipped with doubly fed induction generators (DFIGs). This paper proposes a feed-forward transient current control (FFTCC) scheme for the rotor side converter (RSC) of a DFIG to enhance its LVRT capability. This new control scheme introduces additional feed-forward transient compensations to a conventional current regulator. When three phase faults occur, these compensation terms correctly align the RSC ac-side output voltage with the transient-induced voltage, resulting in minimum transient rotor current and minimum occurrence of crowbar interruptions. With little additional computational effort, the proposed control scheme helps relieve the transient current stress on the RSC and helps maintain an uninterrupted active and reactive power supply from the wind turbines to the power grid. Simulation results are shown to demonstrate the effectiveness of the proposed FFTCC scheme in suppressing transient rotor currents.

Increased Wind Revenue and System Security by Trading Wind Power in Energy and Regulation Reserve Markets

Due to the variability and limited predictability of wind power, wind producers participating in most electricity markets are subject to significant deviation penalties during market settlements, and system operators need to schedule additional reserve to balance the unpredicted wind power variations. This paper proposes a combined energy and regulation reserve market model to encourage wind producers to regulate their short-term outputs. With a reserve market designed with lower deviation penalties, wind producers can increase their revenue by optimally bidding in the energy and reserve markets to reduce their deviation penalties. Meanwhile, part of the intrahour wind variations, which would have appeared in the system energy balance, is diverted into the system regulation reserve. The system then benefits from facing less wind energy intrahour variations, demanding less short-term reserve for wind variations, and having additional fast, although variable, regulation reserve from wind plants, which are likely to enhance grid security and operations in high wind penetration scenarios. A test case is studied to demonstrate the effectiveness of the proposed market model and bidding strategy on increasing the wind plant revenue and grid security.

Wide-Area Measurement Based Dynamic Stochastic Optimal Power Flow Control for Smart Grids With High Variability and Uncertainty

Summary form only given. To achieve a high penetration level of intermittent renewable energy, the operation and control of power systems need to account for the associated high variability and uncertainty. Power system stability and security need to be ensured dynamically as the system operating condition continuously changes. A wide-area measurement based dynamic stochastic optimal power flow (DSOPF) control algorithm using the adaptive critic designs (ACDs) is presented in this paper. The proposed DSOPF control replaces the traditional AGC and secondary voltage control, and provides a coordinated AC power flow control solution to the smart grid operation in an environment with high short-term uncertainty and variability. The ACD technique, specifically the dual heuristic dynamic programming (DHP), is used to provide nonlinear optimal control, where the control objective is explicitly formulated to incorporate power system economy, stability and security considerations. The proposed DSOPF controller dynamically drives the power system to its optimal operating point by continuously adjusting the steady-state set points sent by the traditional OPF algorithm. A 12-bus test power system is used to demonstrate the development and effectiveness of the proposed DSOPF controller.

Feedforward Transient Compensation Control for DFIG Wind Turbines During Both Balanced and Unbalanced Grid Disturbances

A feedforward transient compensation (FFTC) control scheme with proportional-integral-resonant current regulators is proposed to enhance the low-voltage ride through (LVRT) capability of doubly fed induction generators (DFIGs) during both balanced and unbalanced grid faults. Compensation for the DFIG stator transient voltage is feedforward injected into both the inner current control loop and the outer power control loop. The FFTC current controller improves the transient rotor-current control capability and minimizes the DFIG control interruptions during both balanced and unbalanced grid faults. Without the need of sequence-component decomposition, the torque ripple is reduced by injecting 60- and 120-Hz rotor-current components during unbalanced stator voltage conditions. The proposed FFTC control introduces minimal additional complexity to a regular DFIG vector-control scheme and shows promising enhancements in the LVRT capability of DFIGs. Simulation and experimental results are presented to demonstrate the effectiveness of the proposed FFTC control scheme.

Intelligent Local Area Signals Based Damping of Power System Oscillations Using Virtual Generators and Approximate Dynamic Programming

This paper illustrates the development of an intelligent local area signals based controller for damping low-frequency oscillations in power systems. The controller is trained offline to perform well under a wide variety of power system operating points, allowing it to handle the complex, stochastic, and time-varying nature of power systems. Neural network based system identification eliminates the need to develop accurate models from first principles for control design, resulting in a methodology that is completely data driven. The virtual generator concept is used to generate simplified representations of the power system online using time-synchronized signals from phasor measurement units at generating stations within an area of the system. These representations improve scalability by reducing the complexity of the system “seen” by the controller and by allowing it to treat a group of several synchronous machines at distant locations from each other as a single unit for damping control purposes. A reinforcement learning mechanism for approximate dynamic programming allows the controller to approach optimality as it gains experience through interactions with simulations of the system. Results obtained on the 68-bus New England/New York benchmark system demonstrate the effectiveness of the method in damping low-frequency inter-area oscillations without additional control effort.

Two-Level Dynamic Stochastic Optimal Power Flow Control for Power Systems With Intermittent Renewable Generation

High penetration of intermittent renewable energy imposes new challenges to the operation and control of power systems. Power system security needs to be ensured dynamically as the system operating condition continuously changes. The dynamic stochastic optimal power flow (DSOPF) control algorithm using the Adaptive Critic Designs (ACDs) has shown promising dynamic power flow control capability and has been demonstrated in a small system. To further investigate the potential of the DSOPF control algorithm for large power systems, a 70-bus test power system with different generation resources, including large wind plants, is developed. A two-level DSOPF control scheme is proposed in this paper to scale up the DSOPF algorithm for this 70-bus system. The lower-level area DSOPF controllers control their own area power network. The top-level global DSOPF controller coordinates the area controllers by adjusting the inter-area tie-line flows. This two-level architecture distributes the control and computation burden to multiple area DSOPF controllers, and reduces the training difficulty for implementing the DSOPF control for a large power network. Simulation studies on the 70-bus power system with large wind variation are shown to demonstrate the effectiveness of the proposed two-level DSOPF control scheme.

Direct transient control of wind turbine driven DFIG for low voltage ride-through

Wind energy penetration to the power market has been continuously increasing over the past decades. High penetration level requires the wind energy generation to be more reliable. For wind farms equipped with doubly fed induction generators (DFIGs), a successful low voltage ride-through scheme has been a key issue to achieve reliable and uninterrupted wind energy generation. This paper proposes a new current control scheme, called “direct transient current control (DTCC),” as a solution to the low voltage ride through problem. This new scheme adds two additional feed-forward transient compensation terms to a regular decoupling current regulator. These transient terms compensate for the transient effects of stator terminal voltage dips on the rotor currents. Simulation results show that this control scheme could help limit the transient rotor current oscillations, keep the wind turbine DFIG system connected to the power grid, and thus maintain uninterrupted active and reactive power supply to the power grid.

Pumped storage hydro-plant models for system transient and long-term dynamic studies

The detailed dynamic modeling of pumped storage hydro-plants for system dynamic studies is revisited in this paper. Both rigid and elastic dynamic models for different water tunnel penstock configurations are presented. During the generating mode, the system is modeled following the conventional modeling method for hydro-turbines. During the pumping mode, the system is modeled using the pump head-flow curve, and the gating effects are introduced as an additional friction to the system. Different plant operating conditions under different system contingencies are simulated to study the transient and the long-term dynamic responses. The results show that a rigid model is sufficient for system transient dynamic studies, while an elastic model is more accurate for long-term dynamic studies.

Short-Circuit Modeling of DFIGs With Uninterrupted Control

Doubly fed induction generators (DFIGs) exhibit very different short-circuit behavior than synchronous generators, and the conventional voltage-behind-reactance model typically used for short-circuit calculations is not appropriate for generators of this type. A new short-circuit model is proposed in this paper for DFIGs under balanced faults and uninterrupted control of the rotor-side converter (RSC) and grid-side converter (GSC). The proposed positive-sequence short-circuit model represents the RSC and GSC as controlled current sources within the conventional induction machine steady-state equivalent circuit. Short-circuit calculations using the proposed positive-sequence model of the DFIG are compared with transient simulations of a megawatt-scale DFIG under a three-phase fault. Additionally, calculations using the proposed model are compared with experimental short-circuit test results on a 6.8 kVA, 230 V DFIG testbed. From the experimental tests, it is found that mutual-flux saturation in the DFIG significantly affects the short-circuit behavior, and these effects are discussed in detail in this paper.

Adaptive critic design based dynamic optimal power flow controller for a smart grid

An adaptive critic design (ACD) based dynamic optimal power flow control (DOPFC) is proposed in this paper as a solution to the smart grid operation in a high short-term uncertainty and variability environment. With the increasing penetration of intermittent renewable generation, power system stability and security need to be ensured dynamically as the system operating condition continuously changes. The proposed DOPFC dynamically tracks the power system optimal operating point by continuously adjusting the steady-state set points from the traditional OPF algorithms. The ACD technique, specifically the dual heuristic dynamic programming (DHP), is used to provide nonlinear optimal control, where the control objective is formulated explicitly to incorporate system operation economy, stability and security considerations. A 12 bus test power system is used to demonstrate the development and effectiveness of the proposed ACD-based DOPFC using recurrent neural networks.