Enhanced dynamic performance of grid feeding distributed generation under variable grid inductance

<p>Controlling weak grid-connected systems is very challenging. In transient, frequency and voltage oscillations may lead to voltage and/or frequency stability problems and finally lead to system collapse. During steady-state operation and at the point of common coupling (PCC), voltage degradation and grid voltage background harmonics restrict the inverter's functionality, reduce the power flow capability and cause poor power quality. With weak grid connection, grid impedance variance will contaminate the voltage waveform by harmonics and augment the resonance, destabilizing the inverter operation. In this paper, complete mathematical modeling is carried out and state feedback-plus-integral control is implemented to support the stabilization of the system. The proposed controller is adopted to provide a smooth transient under sudden load change by controlling the injected grid current under different grid inductance values. Furthermore, the proposed control is used to reduce the order and size of the inverter output filter while maintaining system stability. The proposed control has been compared with the conventional proportional integral (PI) controller under different scenarios to validate its effectiveness and to strengthen its implementation as a simple controller for distributed generator applications.</p>

Evaluation of the steady state performance of a squirrel cage induction motor using per-phase equivalent circuit

The performance evaluation of cage induction motor continues to receive tremendous attention because of its vital effect on the overall system stability. The model has predicted the behavior of cage induction motor under different operating conditions and in selecting the appropriate motor for a specific load application. There is often a challenge when a squirrel cage induction motor is connected to a time-varying load, particularly when the motor is selected without considering the effects of pulsating torques. The usual method used for steady state analysis of induction motors is the equivalent circuit method. Using the per phase equivalent circuit of the induction motor, stator current and referred rotor current were computed using simple circuit analysis. Once the currents are available, then power can be computed because the voltage is already known.

An Extreme Learning Machine Based Adaptive VISMA for Stability Enhancement of Renewable Rich Power Systems

Maintaining power system stability in renewable-rich power systems can be a challenging task. Generally, the renewable-rich power systems suffer from low and no inertia due to the integration of power electronics devices in renewable-based power plants. Power system oscillatory stability can also be affected due to the low and no inertia. To overcome this problem, additional devices that can emulate inertia without adding synchronous machines can be used. These devices are referred to as virtual synchronous machines (VISMA). In this paper, the enhancement of oscillatory stability of a realistic representative power system using VISMA is proposed. A battery energy storage system (BESS) is used as the VISMA by adding an additional controller to emulate the inertia. The VISMA is designed by using Fruit Fly Optimization. Moreover, to handle the uncertainty of renewable-based power plants, the VISMA parameters are designed to be adaptive using the extreme learning machine method. Java Indonesian Power Grid has been used as the test system to investigate the efficacy of the proposed method against the conventional POD method and VISMA tuning using other methods. The simulation results show that the proposed method can enhance the oscillatory stability of the power system under various operating conditions.

Robust Power Designing of Supplementary Damping Controller in VSC HVDC System to Improve Energy Conversion Efficiency of Wind Turbine and Power System Stability

Because of low losses and voltage drop, fast control of power, limitless connection distance, and isolation issues, using high-voltage direct-current (HVDC) transmission system is recommended to transfer power in the power systems, including wind farms. This paper aims to propose a supplementary damping controller (SDC) based on the HVDC to improve not only power system dynamic stability but also energy conversion efficiency and torsional vibration damping in the wind power plants (WPPs). When the WPPs are working in power control mode, the active power is set to its reference value, which is extracted from power-speed curve. This paper shows that torsional oscillations associated with the poorly torsional modes can be affected by different operating regions of the power-speed curve of WPP. Therefore, it is essential to employ an SDC to have the optimum energy conversion efficiency in the wind turbine and the most dynamic stability margin in the power system. The SDC is designed using a fractional-order PID controller (FOPID) based on the multiobjective bat-genetic algorithm (MOBGA). The simulation results show that the proposed control strategy effectively works in minimizing the torsional and electromechanical oscillations in power system and optimizing the energy conversion efficiency in the wind turbine.

Enhancing Doubly Fed Induction Generator Low-Voltage Ride-Through Capability Using Dynamic Voltage Restorer with Adaptive Noise Cancellation Technique

Some of the major challenges facing micro-grids (MGs) during their connection with the utility grid are maintaining power system stability and reliability. One term that is frequently discussed in literature is the low-voltage ride-through (LVRT) capability, as it is required by the utility grid to maintain its proper operation and system stability. Furthermore, due to their inherent advantages, doubly fed induction generators (DFIGs) have been widely installed on many wind farms. However, grid voltage dips and distortion have a negative impact on the operation of the DFIG. A dynamic voltage restorer (DVR) is a commonly used device that can enhance the LVRT capability of DFIG compared to shunt capacitors and static synchronous compensator (STATCOM). DVR implements a series compensation during fault conditions by injecting the proper voltage at the point of common coupling (PCC) in order to preserve stable terminal voltage. In this paper, we propose a DVR control method based on the adaptive noise cancelation (ANC) technique to compensate for both voltage variation and harmonic mitigation at DFIG terminals. Additionally, we propose an online control of the DC side voltage of the DVR using pulse width modulation (PWM) rectifier to reduce both the size of the storage element and the solid-state switches of the DVR, aiming to reduce its overall cost. A thorough analysis of the operation and response of the proposed DVR is performed using MATLAB/SIMULINK under different operating conditions of the grid. The simulation results verify the superiority and robustness of the proposed technique to enhance the LVRT capability of the DFIG during system transients and faults.

Adaptive Robust Control for Uncertain Systems via Data-Driven Learning

Although solving the robust control problem with offline manner has been studied, it is not easy to solve it using the online method, especially for uncertain systems. In this paper, a novel approach based on an online data-driven learning is suggested to address the robust control problem for uncertain systems. To this end, the robust control problem of uncertain systems is first transformed into an optimal problem of the nominal systems via selecting an appropriate value function that denotes the uncertainties, regulation, and control. Then, a data-driven learning framework is constructed, where Kronecker’s products and vectorization operations are used to reformulate the derived algebraic Riccati equation (ARE). To obtain the solution of this ARE, an adaptive learning law is designed; this helps to retain the convergence of the estimated solutions. The closed-loop system stability and convergence have been proved. Finally, simulations are given to illustrate the effectiveness of the method.

Singularity-Free Adaptive Controller for Uncertain Hysteresis Suspension Using Magnetorheological Elastomer-Based Absorber

The magnetorheological elastomer (MRE) is a smart material widely used in recent vibration systems. A system using these materials often faces difficulties designing the controller such as unknown parameters, hysteresis state, and input constraints. First, a model is designed for the MRE-based absorber to portray the behavior of MRE and predict the appropriate electric current supplied. The conventional adaptive controller often suffers from so-called control singularities. The singularity-free adaptive controller is proposed to eliminate the singularity with parametric uncertainty. The proposed controller consists of four components: an adaptive linearizing controller, a deputy adaptive neural network controller, an auxiliary part designed for the controller to overcome the input constraint problem, and a smooth switching algorithm used to exchange the takeover rights of the two controllers. Moreover, the controller is designed to obtain the stabilization of hysteretic state estimation for the vibration system. The adaptive algorithms are proposed to update the unknown system parameters and to observe the unmeasurable hysteretic state. Meanwhile, closed-loop system stability is comprehensively assessed. Finally, the simulation performed on a quarter-car suspension with an MRE-based absorber shows the proposed controller's efficiency.

An Overview of System Strength Challenges in Australia’s National Electricity Market Grid

The national electricity market (NEM) of Australia is reforming via the rapid uptake of variable renewable energy (VRE) integration concurrent with the retirement of conventional synchronous generation. System strength has emerged as a prominent challenge and constraint to power system stability and ongoing grid connection of VRE such as solar and wind. In order to facilitate decarbonization pathways, Australia is the first country to evolve system strength and inertia frameworks and assessment methods to accommodate energy transition barriers, and other parts of the world are now beginning to follow the same approach. With the evolvement of the system strength framework as a new trending strategy to break the transition barriers raised by renewable energy project development and grid connection studies, this paper provides a high-level overview of system strength, covering such fundamental principles as its definition, attributes, and manifestations, as well as industry commentary, cutting-edge technologies and works currently underway for the delivery of a secure and reliable electricity system with the rapid integration of inverter-based resources (IBRs) in the NEM grid. The intent of this study is to provide a comprehensive reference on the engineering practices of the system strength challenge along with complementary technical, regulatory, and industry perspectives.

D3 Dihedral Logistic Map of Fractional Order

In this paper, the D3 dihedral logistic map of fractional order is introduced. The map presents a dihedral symmetry D3. It is numerically shown that the construction and interpretation of the bifurcation diagram versus the fractional order requires special attention. The system stability is determined and the problem of hidden attractors is analyzed. Furthermore, analytical and numerical results show that the chaotic attractor of integer order, with D3 symmetries, looses its symmetry in the fractional-order variant.

Electronic Expansion Valve Experimental System Debugging Solution Based on PI Control Algorithm on Single-Tube Heat Exchange Experimental Platform

In this paper, the electronic expansion valve (EXV) on the single-tube heat exchange experimental platform was used as a research object. Firstly, the EXVs were selected according to the experimental requirements, and the functional parameters were set. Subsequently, the effective opening ranges of the EXVs were determined by manual control, and the control effects of the EXVs installed at the front and back ends of the test section were compared. Finally, by self-tuning and optimizing the best response curves, the proportional and integral coefficients suitable for the experimental platform were obtained; thus, the automatic intelligent control of EXV based on the proportional integral (PI) control algorithm was realized. From setting EXV functional parameters to realizing PI control, an appropriate experimental system-debugging solution for the whole process could be obtained. Based on the solution, the system stability could be improved, and the transition process time could be shortened. Furthermore, the solution also provided a method to guarantee the accuracy of experimental data and could be applied to the debugging of similar experimental systems.