Controlling Techniques for STATCOM using Artificial Intelligence

The static synchronous compensator (STATCOM) is a power electronic converter designed to be shunt-connected with the grid to compensate for reactive power. Although they were originally proposed to increase the stability margin and transmission capability of electrical power systems, there are many papers where these compensators are connected to distribution networks for voltage control and power factor compensation. In these applications, they are commonly called distribution static synchronous compensator (DSTATCOM). In this paper we have focussed on STATCOM and the controlling techniques which are based on artificial intelligence

Adaptive Control for Power System Voltage and Frequency Regulation

Variable and uncertain wind power output introduces new challenges to power system voltage and frequency stability. To guarantee the safe and stable operation of power systems, the control for voltage and frequency regulation is studied in this work. Static Synchronous Compensator (STATCOM) can provide fast and efficient reactive power support to regulate system voltage. In the literature, various STATCOM control methods have been discussed, including many applications of proportional–integral (PI) controllers. However, these previous works obtain the PI gains via a trial and error approach or extensive studies with a tradeoff of performance and applicability. Hence, control parameters for the optimal performance at a given operating point may not be effective at a different operating point. To improve the controller’s performance, this work proposes a new control model based on adaptive PI control, which can self-adjust the control gains during disturbance, such that the performance always matches a desired response in relation to operating condition changes. Further, a new method called the flatness-based adaptive control (FBAC), for STATCOM is also proposed. By this method, the nonlinear STATCOM variables can easily and exactly be controlled by controlling the flat output without solving differential equations. Further, the control gains can be dynamically tuned to satisfy the time-varying operation condition requirement. In addition to the voltage control, frequency control is also investigated in this work. Automatic generation control (AGC) is used to regulate the system frequency in power systems. Various control methods have been discussed in order to design control gains and obtain good frequency response performances. However, the control gains obtained by existing control methods are usually fixed and designed for specific scenarios in the studied power system. The desired response may not be obtained when variable wind power is integrated into power systems. To address these challenges, an adaptive gain-tuning control (AGTC) for AGC with effects of wind resources is presented in this dissertation. By AGTC, the PI control parameters can be automatically and dynamically calculated during the disturbance to make AGC consistently provide excellent performance under variable wind power. Simulation result verifies the advantages of the proposed control strategy

Voltage Compensation In Wind Power System Using STATCOM Controlled By Soft Computing Techniques

When severe voltage sags occur in weak power systems associated with grid-connected wind farms employing doubly fed induction generators, voltage instability occurs which may lead to forced disconnection of wind turbine. Shunt flexible AC transmission system devices like static synchronous compensator (STATCOM) may be harnessed to provide voltage support by dynamic injection of reactive power. In this work, the STATCOM provided voltage compensation at the point of common coupling in five test cases, namely, simultaneous occurrence of step change (drop) in wind speed and dip in grid voltage, single line to ground, line to line, double line to ground faults and sudden increment in load by more than a thousand times. Three techniques were employed to control the STATCOM, namely, fuzzy logic, particle swarm optimization and a combination of both. A performance comparison was made among the three soft computing techniques used to control the STATCOM on the basis of the amount of voltage compensation offered at the point of common coupling. The simulations were done with the help of SimPowerSystems available with MATLAB / SIMULINK and the results validated that the STATCOM controlled by all the three techniques offered voltage compensation in all the cases considered

Advances and Trends in Mathematical Modelling, Control and Identification of Vibrating Systems

This book introduces novel results on mathematical modelling, parameter identification, and automatic control for a wide range of applications of mechanical, electric, and mechatronic systems, where undesirable oscillations or vibrations are manifested. The six chapters of the book written by experts from international scientific community cover a wide range of interesting research topics related to: algebraic identification of rotordynamic parameters in rotor-bearing system using finite element models; model predictive control for active automotive suspension systems by means of hydraulic actuators; model-free data-driven-based control for a Voltage Source Converter-based Static Synchronous Compensator to improve the dynamic power grid performance under transient scenarios; an exact elasto-dynamics theory for bending vibrations for a class of flexible structures; motion profile tracking control and vibrating disturbance suppression for quadrotor aerial vehicles using artificial neural networks and particle swarm optimization; and multiple adaptive controllers based on B-Spline artificial neural networks for regulation and attenuation of low frequency oscillations for large-scale power systems. The book is addressed for both academic and industrial researchers and practitioners, as well as for postgraduate and undergraduate engineering students and other experts in a wide variety of disciplines seeking to know more about the advances and trends in mathematical modelling, control and identification of engineering systems in which undesirable oscillations or vibrations could be presented during their operation

Performance investigation of stand-alone induction generator based on STATCOM for wind power application

Self-Excited induction generators (SEIG) display a low voltage and frequency regulation due to variable applied load and input rotation speed. Current work presents a simulation and performance analysis of a three-phase wind-driven, SEIG connect to a three-phase load. In addition, an investigation of the dynamic operation of the induction generator from starting steady state until no-load operation. It is assumed that the input mechanical power is constant where the rotor of the SEIG rotates at a constant speed. The value of the excitation capacitance which is necessary to the operation of the induction generator also computed to ensure a smooth and self-excitation starting. The output voltage of the generator is adjusted by varying the reactive power injected by STATCOM. A 3-phase IGBT voltage source inverter with a fuel cell input supply is connected as STATCOM which is used to compensate for the reduction in the supply voltage and its frequency due to variation occurred in the applied loads. This work includes introducing a neuro-fuzzyy logic controller to enhance the performance of the SEIG by regulation the generated voltage and frequency The dynamic model of SEIG with STATCOM and loads are implemented using MATLAB/SIMULIN