Using digital signal processor for excitation system of brushless synchronous generator

A new perspective excitation systems of powerful synchronous generators, which are operating in the common energetic system, are considered, their classification and function diagram are presented. The differential equations system, transfer functions and structural diagram of excitation system, as the automatic regulation object, were obtained according to general presumptions. In the cases of deep crashes in the energetic system the mathematical description of electromechanical transient processes are very complicated and limited. In that cases the efficiency of the excitation current regulator one can be increased by using the combined algorithms of the simplex search, when the local aim function in the optimization motion approximate by separabell equation. According to obtained expressions the synthesis diagram with adaptation and optimization blocks is created. The proposed adaptive synthesis diagram enables to eliminate the error of search direction. Ill. 9, bibl. 16 (in Lithuanian; summaries in Lithuanian, English and Russian).

In this paper, we propose a novel excitation system for improvement of the transient stability. The proposed method controls the excitation voltage of synchronous generators (SGs) to promote decrease in an energy function after a disturbance. The abovementioned control action can be achieved by using wide area information obtained by a wide area measurement system (WAMS). Numerical simulations are carried out for a modified IEEE RTS-24 system with 23 generators. The numerical examples show the effectiveness of the proposed method for improvement of the first swing stability by comparing the proposed excitation system with a conventional automatic voltage regulator under three-line-to-ground faults. Impact of the communication latency in the WAMS-based method on the stabilizing effect is also investigated by setting various length of the latency in the numerical simulation.

The evaluation of heat losses in excitation systems of synchronous generators is a vital part of its design process. The excitation system includes an excitation transformer and an excitation cabinet, which are sources of additional heat losses in the electrotechnical complex. The excitation cabinet contains thyristor-rectifier, AC and DC busbars, fuses and cooling system, which has strong influence on the thermal mode of semiconductor valves and their heat losses. This work covers only air-cooling system. The water-cooling systems are out of scope of this work. Since the transformer losses are well-described in literature this work is focused on heat losses of excitation cabinet equipment. To minimize design errors when calculating the heating rate of the thyristor converter we consider structure of cabinets, mutual influence of different components and environment parameters. The computer program was developed in Matlab in order to include proposed estimation method to design process.

Reliable supply of consumers with electric energy largely depends on the reliability of power source function-ing. In the context of this paper it depends on synchronous generators operating in autonomous power supply sys-tems. In contrast to the power plant generators which are part of power systems and are protected from the loads by sufficiently large resistances, power supply systems withautonomous generators are characterized by rather low resistances. Abrupt changes in the supply load parameters, their own transient and emergency modes, for example, short circuits at the generator terminals, forcing excitation, etc. may lead to various failures in the synchronous gener-ator operation. This paper discusses the possibility of over-voltage in the valve excitation system of a synchronous generator with external three-phase short circuits. On the basis of analytical expressions describing the physical pro-cesses occurring in the excitation system of synchronous generators, the conditions for the occurrence of overvolt-ages are identified

Excitation systems of synchronous generators contribute to effective voltage control and power system stability. Although the excitation system is tuned to enable the power system performs properly over a wide range of operating conditions, it may be necessary to retune it with the aim of improving the system stability during operating conditions not considered before. This paper shows how an unstable operating condition, of an oil refinery electric power system, after the occurrence of two simultaneous events may be avoided by simply adjusting the automatic voltage regulator gain in one of its synchronous generators.

This paper presents a Wide Area Control (WAC) design to enhance the transient stability of Doubly Fed Induction Generators (DFIG) integrated power grid. The proposed WAC design is based on a nonlinear optimal control algorithm using Reinforcement Learning (RL) and Neural Networks (NNs), which optimizes the closed-loop performance of the wind integrated power grid through Approximate Dynamic Programming (ADP). The aim of the WAC is to estimate the global energy function of the system, independent of the contingency, and derive supplementary damping control to augment the excitation system of synchronous generators and local active and reactive power control of DFIG. The controller objective is evolved from transient energy function terms developed for synchronous generators and wind farms within the framework of a coupled oscillatory system. The theoretical results are verified by conducting simulation studies on the modified IEEE 68-bus system with three aggregated wind farms modeled in electromagnetic transient simulator test-bed. It has been shown that the method improves transient stability of the test system and damps the interarea oscillations faster, including the active and reactive power support from DFIG during grid transient conditions.

The insertion of communication networks in closed-loop of digital control systems makes the system synthesis and analysis complex. In this paper, we consider the combination of classical reliability, risk and safety evaluation with typical control system through digital networked control systems. The main purpose is to study the influence of transmission delays and packet dropouts on the reliability of digital networked control systems by using a modified statistical method-Monte Carlo simulation. The behaviors of two types of fault are modelled by different statistical distribution. The control strategies we apply for digital control systems are Proportion Integration Differentiation control strategies, generated by Genetic Algorithm. In terms of a realistic system model, we evaluate and compare the influences on the reliability of digital networked control systems with different control strategies from quantitative aspect. Numerical examples are presented to illustrate the effectiveness and correctness of the approach.

This paper discusses the design of genetics algorithm based proportional integral derivative-power system stabilizer and Adaptive Neuro Fuzzy Inference System based power system stabilizer for the stability analysis of the single machine infinite bus system. The controller has been used to generate the appropriate supplementary control signal for the excitation system of synchronous generator. The signal generated has been used to damp the low frequency oscillations and improves the performance of power system dynamics. The non- linear simulations of the system has been carried out, which results show the efficacy and capability of two schemes for the design of PSS under the various disturbances and faults conditions.

This paper gives a survey of two approaches applied to detection of critical power oscillations in electric power systems. The developed techniques are based on models identified in real-time from measured data. The resulting models yield the actual power system dynamics. They can be used for monitoring purposes as well as for design of stabilizing/damping controllers applied to any fast acting power electronic devices installed in power systems such as HVDC, FACTS devices or excitation systems of synchronous generators. The described monitoring algorithms have already been implemented using existing hardware and productized. This makes it possible to show some results and practical experience collected in cooperation with several transmission system operators.

The Field Tests on Power System Stabilizers for Damping Low Frequency Oscillation

In this paper, the novel approach to design the power system stabilizer using artificial neural network based Non Linear Auto Regressive Moving Average-L2 (NARMA-L2) controller has been presented. The controller has been used to generate the appropriate supplementary control signal for the excitation system of synchronous generator. The signal generated has been used to damp the low frequency oscillations and improves the performance of power system dynamics. The analysis of Signal Machine Infinite Bus (SMIB) system has been carried out with NARMA-L2 controller and the performance has been compared with genetics search algorithm based Conventional Power System Stabilizer (CPSS). To reflect the effectiveness of NARMA-L2 based PSS, the non-linear simulations have been performed under various disturbances and different operating conditions.

This paper presents two methods for load angle determination for salient-pole synchronous generator. The first method uses optical encoder to detect the rotor position. In some cases the end of the rotor shaft is not free to be used and mounting of an encoder is impossible. Therefore, the second method proposes estimation of the load angle based on the measured electrical values that have been already used in excitation control system of the synchronous generator. Estimation method uses corresponding voltage-current vector diagram and parameters of the synchronous generator, transformer and transmission lines. Both methods were experimentally verified on the digital control system and synchronous generator connected to power system. The estimation and measured results were compared. The accuracy of load angle estimation method depends on voltage and current measurement accuracy as well as generator, transformer and transmission line parameter accuracy. The estimation method gives satisfactory accuracy for load angles less than 120o el. Thus, it can be applied in excitation control system to provide stable work of synchronous generator in under-excitation operating area.

At present, most of Chinese Nuclear Power Plants (NPPs) in operation and under construction adopt Digital Control System (DCS). As a result, the special High Level Layout and Control Function based on DCS platform are required to fulfill the normal and accident operation tasks. As the supporting systems of safety and safety-related systems, the Heating, Ventilation, and Air Conditioning (HVAC) systems are responsible for shielding the radioactive productions and maintaining the environment temperature in the acceptable scope for the staffs and the important equipments. Considering that the HVAC systems have been involved frequently during normal and accident operating, the special High Level Layout and Control Functions (HLLCF) for HVAC should be designed to present the advantages of DCS platform, but also assist the operators to implement the operating procedures quickly and improve the safety of NPPs.

Recently, the Plant Input Mapping (PIM) method was proposed as a digital-redesign (or an emulation) approach in digital control system design. This method guarantees stability of a redesigned digital control system for a wide range of sampling periods. In this paper the PIM method is applied to the design of a digital model-matching flight control system. In the model-matching control system design a plant must have no unstable zeros. However, unstable zeros appear for small sampling periods in a step invariance model of a continuous-time (CT) plant with the relative degree greater than two, even if the CT plant has no unstable zeros. Hence, in such a case, the direct-digital approach cannot be applied to the design of a digital model-matching control system. By contrast, the digital-redesign approach such as the Tustin's method or the PIM method is free from the problem. Simulation results for an unstable VTOL aircraft show that the proposed method gives better performance than the conventional design methods.

The advent of single-chip programmable digital signal processors (OSP) has expanded digital signal processing into automotive applications. Digital signal processors, compatible in cost to general-purpose microcomputers, offer much higher throughput in performing computationally intensive tasks. Because of this advantage, closed loop control, adaptive control, and digital audio processing can now be implemented in a cost effective manner. Some of the DSP automotive applications include combustion feedback engine control, active suspension systems, anti -skid brakes incorporating traction control and digital audio-based entertainment systems. The availability of digitaI signal processors i s changing many aspects of automotive designs. Early adopters of this technology for innovative automotive products wiII enjoy leadership and financial benefits over their competition. The impact of DSP to the automobile has just begun and will continue beyond the year 2000 ( I ) . This new technology has also presented tremendous challenges to both automotive and semiconductor industries. This paper first discusses digital signal processing characteristics. After reviewing historical digital signal processing solutions, the paper focuses on single-chip programmable digital signal processors and compares their architectural designs to general- purpose microprocessors and microcontrollers. Deficiencies of early digital signal processors are discussed and trends of DSP are explored. Performance and cost benefits of using DSP in digital control systems are explained. Automotive applications of digital signal processors are discussed in areas of powertrain, body and chassis control, and entertainment systems. The last part of the paper discusses the challenges presented to both automotive industry and semiconductor vendors.