Model-Free Voltage Control for Inverter-Based Energy Resources: Algorithm, Simulation and Field Test Verification

Inverter-based resources (IBRs) are required to provide dynamic voltage support (DVS) during voltage dips to enhance the low-voltage ride-through capability. In this paper, a model-free control method is developed to achieve the optimal DVS (ODVS) without relying on the knowledge of grid parameters. Delving into the optimum trajectory of the ODVS problem, it is found that the current constraint and the maximum active power constraint of IBRs are both binding, or one of them is binding. This inspires us to search for the optimum in a closed-loop way by a perturb-and-observe (P&O)-based optimum seeking (OS) controller with either the power factor angle or the reactive current being the manipulated (perturbed) variable. The system is guaranteed to converge asymptotically to the optimum provided the stepsize sequence is diminishing and non-summable. The proposed model-free optimal control is finally implemented within a single-stage photovoltaic (PV) system, where dynamic simulations demonstrate the optimal and fast DVS performance. Moreover, the implementation strategy for other types of IBRs that are not self-protected by nature is also discussed.

With increasing focus on economical as well as environmentally friendly means for mass transit, rail transport is gaining renewed momentum in many parts of the world. This means investing in novel rail infrastructure as well as upgrading and electrifying existing facilities. The TEN (Trans-European Network) program within the European Union is but one current example of the importance attributed to more and better mass transit all over the world. The feeding of heavy rolling stock from AC grids will in many cases cause unacceptable voltage drops as well as unsymmetry between phases of the feeding grid. A traditional way to improve the situation would be to build additional power transmission lines and/or step up the feeding voltage to a higher level. This, however, may be undesirable or even impossible, for cost reasons as well as for environmental reasons. FACTS devices offer means of remedy within the existing feeding grid, restoring grid symmetry as well as voltage stability, and also mitigating harmonic distortion emanating from rolling stock. FACTS devices such as SVC (Static Var Compensator) and STATCOM (Static Compensator) are well proven and commercially available today. The paper treats dynamic load balancing of grids supplying power to rail transport, as well as dynamic voltage support and harmonic mitigation, by means of SVC as well as STATCOM.

Similar to many complex systems, the operation process of electric balanced forklifts has characteristics such as time-varying model parameters and nonlinearity. Establishing an accurate mathematical model becomes challenging, making it difficult to apply model-based control methods in engineering practice. Aiming at the longitudinal control system of electric forklifts containing external disturbances, this paper proposes an improved full-format dynamic linearization model-free adaptive PID control (iFFDL-MFA-PID) method. Firstly, the full-format dynamic linearization (FFDL) method is employed to transform the operating system of the electric balanced forklift into a virtual equivalent linear data model. Secondly, the nonlinear residual term and pseudo-gradient (PG) of the data model are estimated using the difference estimation algorithm and the optimal criterion function, respectively. Furthermore, in order to enhance the robustness of the system, the idea of intelligent PID (iPID) is introduced and the principle of equivalent feedback is utilized to derive the iFFDL-MFA-PID control scheme. The design process of this scheme only requires the use of the input and output data of the system, without relying on the mathematical model of the system. Finally, the iFFDL-MFA-PID method proposed in this paper is simulated and tested with the EFG-BC/320 counterbalanced forklift equipped in the Special Equipment Testing Center and compared with the model-free adaptive control method (FFDL-MFAC) and the PID control method. Simulation results show that the speed-tracking error of the electric forklift truck under the action of the iFFDL-MFA-PID algorithm is maintained within ±0.132 m/s throughout the process, achieving higher tracking accuracy and better robustness compared to the MFAC and PID methods.

Conventional adaptive PI controller is one of the most widely used controllers in industry, but the recent advancement in fractional calculus has introduced applications of fractional order calculus in control theory. One of the prime applications of fractional calculus is fractional adaptive PI controller and it has received a considerable attention in academic studies and in industrial applications. Fractional order adaptive PI controller is an advancement of classical integer order adaptive PI controller. In many a cases fractional order adaptive PI controller has outperformed classical integer order adaptive PI controller. Particularly for the problem of controlling the speed of DC-motors, it is very important use a suitable and efficient controller as any small change can lead to instability of the closed loop system. This research paper, studies the control aspect of fractional order controller in speed control of DC motor. A comparative study of classical adaptive PI controller and fractional order adaptive PI controller has been performed to illustrate the effectiveness and robustness of the proposed fractional adaptive control solution.

Recently, transformerless (TL) inverters are being extensively used in small-scale photovoltaic (PV) systems due to their compact-size, lighter-weight, lower-cost and higher-efficiency compared to their counterpart with transformer. However, the growing penetration of these small-scale based PV systems and low-inertia induction motor (IM) loads in low-voltage distribution networks (DNs) make the grid more vulnerable to short-term voltage stability (STVS). Hence, this paper thoroughly examines the STVS of DN with high-penetration of TL-PV units, and provides countermeasures by TL-PV systems to mitigate any short-term voltage instability. The detailed dynamic model of the TL inverter is developed first. Next, three control strategies: (1) constant peak current (CPC), (2) constant active current (CAC), and (3) constant active power (CAP) with low voltage ride through (LVRT) and dynamic voltage support (DVS) capabilities are proposed to improve STVS. The impacts of different level of PV penetrations and LVRT capability of TL-PV inverters on the STVS are explored. Moreover, countermeasures, such as LVRT with CAC and CAP controls and DVS by the TL-PV systems are designed and implemented. Several case studies are carried out on an IEEE 4 bus system first, and later extended to IEEE 13 node test feeder. The results show that DVS can further improve STVS in residential DNs. In addition, CAP and CAC control strategies can speed-up the postdisturbance voltage recovery compared with the conventional CPC control.

Parallel manipulators with less than six degrees of freedom (DOF) have been increasingly used in high-speed hybrid machine tools. The structural features of parallel manipulators are dynamic, a characteristic that is particularly significant when these manipulators are used in high-speed machine tools. However, normal kinematic control method cannot satisfy the requirements of the control system. Many researchers use model-based dynamic control methods, such as the dynamic feedforward control method. However, these methods are rarely used in hybrid machine tools because of the complex dynamic model of the parallel manipulator. In order to study the dynamic control method of parallel manipulators, the dynamic feedforward control method is used in the dynamic control system of a 3-PSP (prismatic-spherical-prismatic) 3-DOF spatial parallel manipulator used as a spindle head in a high-speed hybrid machine tool. Using kinematic analysis as basis and the Newton-Euler method, we derive the dynamic model of the parallel manipulator. Furthermore, a model-based dynamic feedforward control system consisting of both kinematic control and dynamic control subsystems is established. The dynamic control subsystem consists of two modules. One is used to eliminate the influence of the dynamic characteristics of high-speed movement, and the other is used to eliminate the dynamic disturbances in the milling process. Finally, the simulation model of the dynamic feedforward control system of the 3-PSP parallel manipulator is constructed in Matlab/Simulink. The simulations of the control system eliminating the influence of the dynamic characteristics and dynamic disturbances are conducted. A comparative study between the simulations and the normal kinematic control method is also presented.The simulations prove that the dynamic feedforward control method effectively eliminates the influence of the dynamic disturbances and dynamic characteristics of the parallel manipulator on high-speed machine tools, and significantly improves the trajectory accuracy. This is the first attempt to introduce the dynamic feedfordward control method into the 3-PSP spatial parallel manipulator whose dynamic model is complex and provides a study basis for the real-time dynamic control of the high-speed hybrid machine tools.

Wind generation is required to provide dynamic voltage support (DVS) during fault ride-through (FRT) to enhance system voltage stability. However, DVS causes the FRT behavior of wind generation to be segmented, and its impact on voltage stability in the wind farm (WF) integrated linecommutated converter-based high-voltage direct current (LCCHVDC) sending-end system remains unclear. To achieve a quantitative analysis to this gap, a novel quasi-static piecewise model for the sending-end system is developed, in which the segmented FRT behavior of WF is fully incorporated. Beyond the well-known saddle-node bifurcation (SNB), a new FRT-induced nonsmooth bifurcation (FRTNB), is identified. The influence of WF and the LCC-HVDC system on both SNB-related and FRTNBrelated voltage stability is thoroughly analyzed. Based on the acquired insights, a control strategy is proposed for the LCCHVDC system to proactively utilize its DVS capability, which is adaptive to the segmented FRT behavior of WF and can effectively enhance system voltage stability without requiring knowledge of grid parameters. Dynamic simulations validate the theoretical analysis and the effectiveness of the proposed method under both voltage sag and swell conditions

Enhancing voltage stability against system disturbances is essential for the reliable operation of LCC-HVDC systems under weak grid conditions and high levels of renewable energy integration. LCC-HVDC systems inherently possess the capability to provide over 90% of their rated reactive power as dynamic voltage support. However, conventional control schemes lack the mechanism to coordinate this reactive power in response to voltage disturbances. This paper introduces a droop-based inverter control strategy that enables dynamic DC voltage adjustment, thereby unlocking the reactive power regulation potential of LCC-HVDC systems. A theoretical framework is established to quantify the relationship among voltage deviation, disturbance magnitude, and grid strength. Analytical and simulation results demonstrate that allocating reactive disturbances to stronger grids can reduce voltage deviation by up to 25% and expand the maximum tolerable disturbance (MTD) by nearly 2 times. The proposed strategy offers a control-oriented solution that extends the functional role of LCC-HVDC beyond power transmission, enabling it to serve as a distributed voltage support asset in modern power systems.

This study presents two improved designs of eccentric-shaped permanent magnets and teeth-shaped stators in radial-flux dual three-phase permanent magnet electric machines to reduce cogging torque and torque ripple. The finite element analysis (ANSYS Electromagnetics) has been adopted in simulation, and real radial-flux dual three-phase permanent magnet electric machines have been fabricated in experiment to verify the study. Using the radial-flux dual three-phase permanent magnet electric machines in electric machine systems can improve the reliability and obtain higher output torque. In electrical drives and control, a simplified model-free predictive current control method has been proposed and implemented to drive the radial-flux dual three-phase permanent magnet electric machines, and the control law has been achieved by a TMS320F28377S microcontroller of Texas Instruments. The simplified model-free predictive current control method is senseless to parameter variations and back electromotive force of the permanent magnet electric machines, and only needs current sensors to detect six-phase current. The optimal one has been chosen by 14 various switching modes, which has the minimum cost function, and then the converter can be directly driven and controlled in the next sampling period. The features of the simplified model-free predictive current control method can reduce the algorithm calculation and avoid the defect of conventional model-based predictive current control scheme. A proportional-integral speed controller has also been designed to achieve the speed response of the fixed-speed tracking effect. Finally, the feasibility and effectiveness of the proposed simplified model-free predictive current control method for the dual three-phase permanent magnet electric machines can be verified in the experimental and quantitative results.

From efficiency and reliability standpoints, there are three major issues in coal-fired power plant auxiliary systems: high in-house load, low power factor, and weak disturbance-ride-through capability. This paper presents a cost-effective solution to solve these problems. The proposed solution consists of Variable Frequency Drives (VFDs) with Active Rectifier Units (ARUs), mechanically switched shunt capacitor banks, and coordinated reactive power control strategies implemented in the power plant Distributed Control System (DCS). In this paper, the design principles of the proposed solution will be introduced. Coordinated control strategies of the ARUs and capacitors for which implement the steady-state power factor control and dynamic voltage support under disturbances will be described. The overall potential benefits resulting from the proposed solution will be discussed and demonstrated with example studies corresponding to a 300MW coal-fired power plant.

This paper describes the most recent German regulation on the integration of dispersed power generation into the medium and high voltage grid in terms of the latest grid codes. A special consideration is given to the advanced requirement on frequency control and dynamic voltage support. An overview on the status quo of certification regulations and implementation approaches in selected countries both on single WEC types and on wind farms is provided. Furthermore, the model validation and subsequent certification procedure FGH Certification Office has developed and applied to first wind farm certifications will be presented. A focus will be given to the validation of the WEC model and the simulation of the wind farm's reactive current injection under fault conditions.

Large-scale integration of renewable generation has changed the way that distribution networks are operated, posing significant challenges to voltage control. To address this challenge, system operators need to exploit the potential of inverter-based renewable generation for reactive power regulation. However, the distribution network parameters are usually inaccurate or incomplete, making conventional centralized or model-dependent distributed control methods difficult for fast voltage tracking and optimal reactive power distribution. This paper proposes a model-free distributed Newton method for voltage control based on data-driven lift-dimension linear power flow which does not reply on accurate and complete network parameters. By using matrix splitting to calculate Hessian matrix, the proposed method possesses a super-linear convergence and exhibits superiority in fast response over existing linear methods. Furthermore, a Koopman-based state space mapping method is proposed to obtain global sensitivity and tune the iteration direction in an off-line manner, which can realize model-free voltage control. The convergence and optimality of the proposed method are validated by case studies. Especially, the parameter independence feature of the model-free scheme provides decided superiority in scenarios of incomplete model. Even under communication failures, the proposed method still can maintain voltage stability at a suboptimal point.

This paper applied model free control method to the refrigeration system evaporator minimum stable superheat control. Compared with conventional PID control, model free control method has fast convergence, anti-interference ability. Meanwhile, model free control can reduce the coupling effect between evaporator superheat and evaporating temperature and be well adapted to the variable load control requirements of the refrigeration system, which has good steady state performance and dynamic performance.

Dynamic programming is a very useful tool in solving optimization and optimal control problems. Here, the Approximate Dynamic Programming (ADP) and the notion of neural networks based predictive control are combined with a model-free control method based on SPSA (Simultaneous perturbation stochastic approximation), and a novel ADP based model-free predictive control strategy for nonlinear systems is proposed. Dynamic programming is used to adjust the control parameters in the novel model-free control method and the notion of predictive control is introduced to modify the whole control structure. Finally, the proposed ADP based model-free predictive control strategy is applied to solve nonlinear tracking problems and the effectiveness of this novel control method is fully illustrated though simulation tests on two typical nonlinear systems.

Against the background of the development of control systems, Data Driven Control (DDC) methods are becoming more and more popular, given the system’s independence from physical models and the possibility of quickly tuning the controller. The usefulness of such tuning algorithms increases with the complexity of the plants. Nonlinear models are the main class of processes for which such laws are amenable. According to the literature, a class of DDC methods exist that perform online estimation of plant behavior with an unknown structure, which is generically called Model Free. This title is assumed by two types of algorithms, which contain it in the name. One is the gradient-based algorithm, Model Free Adaptive Control, defined by Hou, which uses the concept of dynamic linearization through pseudo partial derivatives (PPD) and pseudo gradient (PG). The other is a non-gradient based algorithm, Model Free Control, defined by Fliess and Join, which uses the concept of the ultralocal model and intelligent PID controllers (iPID). For the gradient-based methods, in the compact form of dynamic linearization (CFDL), i.e., partial form dynamic linearization (PFDL), two algorithms are proposed to determine the initial value of the time-varying parameters PPD and PG from the dynamic performance perspective as they offer the best responses. The CFDL and PFDL variants of the MFAC control law, which have parameters that result from the application of the proposed algorithms, are compared with iP and iPD controllers on nonlinear control systems.