Robust SVC controller design and analysis for uncertain power systems

This paper presents the application of Bees Algorithm (BA) technique for loss minimization in power transmission network. The loss minimization technique is implemented through Static Var Compensator (SVC) installation and the optimization technique is the Bees Algorithm. Bees Algorithm was developed to optimally determine the SVC values to be installed in the power transmission network. In this study, SVC was modeled as an effective capacitive reactance equivalent which aims to alter the transmission lines properties in the system. In order to perform validation process, a 26-bus IEEE Reliability Test System (RTS) will be utilized and tested in minimizing total transmission loss in the system.

A SMES (Superconducting Magnetic Energy Storage System) system with converter composed of self-commutated valve devices such as GTO and IGBT is available to control active and reactive power simultaneously. A SVC (Static Var Compensators) or STATCOM (Static Synchronous Compensator) is widely employed to reduce reactive power in power plants and substations. Owing to progress of power electronics technology using GTO and IGBT devices, power converters in the SMES system and the SVC can easily control power flow in few milliseconds. Moreover, since the valve devices for the SMES are equivalent to those for the SVC, the device cost must be reduced. In this paper the basic control system combined with the SMES and SVC is designed for large pulsed loads of a nuclear fusion power plant. This combined system largely expands the reactive power control region as well as the active one. The simulation results show that the combined system is effective and prospective for the nuclear fusion power plant.

This paper presents a robust control strategy for uninterruptible power systems (UPS) based on the linear matrix inequality (LMI) framework. Taking into account the average model of the UPS, a state feedback controller is proposed that assures the local stability of the closed-loop system for all admissible load variation while minimizing an upper-bound on the 2-norm of the input-to-output operator. A real-life example is used to demonstrate the approach.

This paper presents a novel tuning algorithm for the adaptive reactive power (Var) PI controller as a control part of under-excitation limiter (UEL). The proposed algorithm is designed to adapt to changes in the synchronous generator (SG) plant dynamics without requiring prior knowledge of generator and system parameters. The algorithm is based on the reduced first-order linear plant model, whose parameters are estimated using the Recursive least-squares (RLS) algorithm. Considering that the SG is close to its stability limit when the UEL is operational, if the Var controller is not tuned well, the UEL can generate a negative damping torque on electromechanical oscillations and even lead to SG instability. The proposed algorithm solves this problem by targeting the specific frequency bandwidth of the Var control system that excludes the detected frequency of electromechanical oscillations. This mitigates the negative impact of the UEL on the damping of electromechanical oscillations and prevents overlapping of UEL action with the power system stabilizer (PSS) action. Once the plant model parameters are estimated, and the targeted control system frequency band is identified based on the measured electromechanical oscillation frequency, the controller parameters are tuned using pole-zero cancellation method. The effectiveness and performance of the proposed tuning procedure, encompassing online identification of reduced linear plant model parameters, online measurement of electromechanical oscillation frequency, and subsequent online tuning of the UEL Var controller, have been demonstrated through both simulation and experimental studies. Simulations utilized nonlinear and linear models of a 240 MVA SG connected to an infinite bus and Kundur’s two-area power system model. Experimental validation was conducted in a laboratory environment using a reduced-scale, low-power SG. Dynamic performance indices obtained from various test cases demonstrate the robustness and stability of the Var control system incorporating the UEL controller proposed in this paper.

The placement of FACTS devices in a power network is of great importance to ensure the utilization of the full potential of the transmission network. In this study firstly, a static VAr compensators (SVCs) are placed optimally in a power network by taking into consideration the generation costs of both active and reactive power and the cost of the SVCs. The optimal power flow (OPF) and the low discrepancy sequences (LDS) based optimization procedure are employed to solve the problem of optimal allocation of SVCs. Secondly, a small disturbance stability study is performed in order to investigate how installing the SVCs with additional control loops at such locations could contribute to system small disturbance stability. The study demonstrated that the optimal allocation of SVCs is a cost effective measure since the installed SVCs reduce overall generation costs and additionally contribute to the enhancement of the security of the transmission network by improving the damping of electromechanical oscillations

The placement of FACTS devices in a power network is of great importance to ensure the utilization of the full potential of the transmission network. In this study firstly, a static VAr compensators (SVCs) are placed optimally in a power network by taking into consideration the generation costs of both active and reactive power and the cost of the SVCs. The optimal power flow (OPF) and the genetic algorithm (GA) based optimization procedure are employed to solve the problem of optimal allocation of SVCs. Secondly, a small disturbance stability study is performed in order to investigate how installing the SVCs with additional control loops at such locations could contribute to system small disturbance stability. The study demonstrated that the optimal allocation of SVCs is a cost effective measure since the installed SVCs reduce overall generation costs and additionally contribute to the enhancement of the security of the transmission network by improving the damping of electromechanical oscillations.

The paper explores the influence of power system loads on static VAr compensator (SVC) damping effectiveness. Equipped with properly tuned additional stabiliser SVCs have been successfully used for improving the damping of electromechanical oscillations in power system. The damping improvement is usually achieved through indirect voltage influence through voltage dependent loads. Tuning of additional compensator stabiliser (ACS) traditionally assumes that loads are statically voltage dependent. However load parameters are generally uncertain and loads often exhibit some dynamic response. This uncertain dynamic behaviour of loads can introduce an additional phase shift between voltage and load response and such can detune the ACS. Example of robust tuning of ACS to compensate influence of load dynamics and uncertainty is presented and discussed.

Single machine infinite bus (SMIB) power system and multi-machine power system (MMPS) stability improvement by tuning of static var compensator (SVC) based controller parameters are investigated in the proposed method. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and real-coded genetic algorithm is used for searching optimal controller parameters. SMIB power system and MMPS models are developed using MATLAB’s SIMULINK which incorporates SVC controller. A fault is created on the transmission line. The simulation results of SMIB power system and MMPS without SVC controller and with SVC controller are presented. The simulation results are analyzed which show that the power system becomes unstable on the occurrence of the fault if SVC controller is not used. This paper proves the effectiveness of the proposed design. Thus the proposed method enhances the power system stability.

This paper presents the electric power system analysis and design of an expanding steel cogeneration plant. The power system configuration and the equipment parameters of the cogeneration plant are well designed according to the power flow, short circuit, voltage fluctuation, harmonic flow and transient stability analyses. According to the power flow analysis, the site and capacity of shunt capacitor banks as well as the tap position of transformers are determined to maintain all the buses voltage at acceptable range and to keep the power factor above 0.95. Also, to comply with the restriction of circuit breaker capacity, the high impedance transformers are designed even if they consumed more reactive power from the system. In addition, the voltage fluctuation resulted from the dramatic reactive power variation of hot strip rolling mill can be greatly reduced if proper static var compensator (SVC) is installed. The significant voltage sag due to the starting of induction motor can be effectively improved by applying wye-delta transformer starter. Furthermore, the total voltage harmonic distortion (THD <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">V</sub> ) and the total current demand distortion (TDD <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I</sub> ) are both acceptable if the proper filters are installed. It is also found that the cogeneration system can keep stable operation in isochronous mode by applying the governor control action and the load shedding scheme after tie line tripping. It is concluded that the power system analyses is important for the steel plant with cogeneration unit to identify hidden problems and remedy strategy to ensure the system power quality and operation performance.

Matlab SimPowerSystems is a modern design tool that allows scientists and engineers to rapidly and easily build models that simulate power systems. Not only can you draw the circuit topology rapidly, but your analysis of the circuit can include its interactions with mechanical, thermal, control, and other disciplines. The paper covers some case studies that provide detailed, realistic examples of how to use SimPowerSystems in power system analysis. The following types of studies is coverted on the paper:1. Thyristor‐Based Static Var Compensator: Study the steady‐state and dynamic performance of a static var compensator (SVC) on a transmission system.2. Transient Stability of a Power System with SVC and PSS: Study of the application of static var compensator (SVC) and power system stabilizers (PSS) to improve transient stability and power oscillation damping of the system.3. GTO‐Based STATCOM: Study the steady‐state and dynamic performance of a static synchronous compensator (STATCOM) on a transmission system.4. Control of load flow using UPFC: Study the steady‐state and dynamic performance of a unified power flow controller (UPFC).5. Chopper‐Fed DC Motor Drive: Study of a DC motor drive with armature voltage controlled by a GTO thyristor chopper.6. VSC‐Based HVDC Link: Modeling of a forced‐commutated Voltage‐Sourced Converter high‐voltage direct current (VSC‐HVDC) transmission link.7. Three‐Phase Network with Electrical Machines: Simulation of a three‐phase power system containing electrical machines and other three‐phase models.8. Variable‐Frequency Induction Motor Drive: Study of a PWM inverter‐driven variable‐frequency AC induction motor in variable‐voltage, variable‐speed operation.

Electric motor drives are subjected to severe oscillations that might cause motor shaft fatigue and consequent breakdown during system operation. In this paper, a design of robust proportional integral (PI) controller for induction motor (IM) drives is presented. Uncertainties due to different load conditions of the drive system are modelled by a transfer function with interval coefficients. Instead of stabilising an infinite number of polynomials, the Kharitonov theorem is used to design a robust controller by simultaneous stabilisation of only four polynomials. The controller parameters are optimised so that the maximum eigenvalue among the four polynomials is pushed to the left in the complex plane. This is accomplished using genetic algorithm (GA) optimisation to achieve the maximum possible rapidity of the system. The proposed controller is tested experimentally using the hardware-in-the-loop (HIL) technique. The simulation and experimental results show the validity and effectiveness of the proposed controller as compared to the auto-tuned PID control at different loading conditions.

It is well known that the power system controller designed by H∞ control is complicated, high order and impractical. In power system applications, practical structures such as proportional integral derivative (PID) etc., are widely used, because of their simple structure, less number of tuning parameters and low-order. However, tuning of controller parameters to achieve a good performance and robustness is based on designer's experiences. To overcome this problem, this paper proposes a fixed structure robust H∞ loop shaping control to design Static Var Compensator (SVC) and Automatic Voltage Regulator (AVR) for robust stabilization of voltage fluctuation in an isolated wind-diesel hybrid power system. The structure of the robust controller of SVC and AVR is specified by a PID controller. In the system modeling, a normalized coprime factorization is applied to represent possible unstructured uncertainties in the power system such as variation of system parameters, generating and loading conditions etc. Based on the H∞ loop shaping, the performance and robust stability conditions are formulated as the optimization problem. The particle swarm optimization is applied to solve for PID control parameters of SVC and AVR simultaneously. Simulation studies confirm the control effect and robustness of the proposed control.

Coordinated tuning of power system controllers using parallel genetic algorithms

A method is proposed in this paper to select supplementary signals for a static var compensator in IEEE first benchmark model. Different input output controllability analyses are used to assess the most appropriate supplementary signals for the static var compensator (SVC) for achieving effective damping of torsional oscillations. After placing the SVCs based on their primary functions, the most appropriate input signal for supplementary controller is also selected. The eigenvalues and hankel singular values of the system are computed incorporating various supplementary signals in the SVC for selecting the best supplementary signal.

A robust complexity reduced proportional-integral-derivative (PID)-like fuzzy controllers is designed for a plant with fuzzy linear model. The plant model is described with the expert's linguistic information involved. The linguistic information for the plant model is represented as fuzzy sets. In order to design a robust fuzzy controller for a plant model with fuzzy sets, an approach is developed to implement the best crisp approximation of fuzzy sets into intervals. Then, Kharitonov's Theorem is applied to construct a robust fuzzy controller for the fuzzy uncertain plant with interval model. With the linear combination of input variables as a new input variable, the complexity of the fuzzy mechanism of PID-like fuzzy controller is significantly reduced. The parameters in the robust fuzzy controller are determined to satisfy the stability conditions. The robustness of the designed fuzzy controller is discussed. Also, with the provided definition of relative robustness, the robustness of the complexity reduced fuzzy controller is compared to the classical PID controller for a second-order plant with fuzzy linear model. The simulation results are included to show the effectiveness of the designed PID-like robust fuzzy controller with the complexity reduced fuzzy mechanism.