Digital Signal Processor Based Measurement System in a Control Application

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DIGITAL SIGNAL PROCESSOR BASED MEASUREMENT SYSTEM IN A CONTROL APPLICA TION Z. Q. Bo, E. Swidenbank and B. W. Hogg OI'/mrl lllt' lIl

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Abstract. This paper provides a brief review of a research and development program that is to investigate the technical feasibility of using digital signal processors(DSP) for measurement functions in the voltage regulator aspect of excitation systems. An advanced digital signal processor measurement and control system provides special features for control of a turbogenerator unit. The independent measurement system composed of analog and digital input modules. controlled by a digital Signal processor, samples voltages, currents and digital information necessary to drive the machine. It also processes these values, to produce all the quantities necessary to control the system. A package of software, which includes three data processing algorithm, has been used with the system. This allows a variety of control algorithms to be tested to improve the performance of the power generator unit.

Key Words. Digital control; Power system control; Data Acquisition and processing; Generators.

INTRODUCTION The development of modern electric-power systems is characterized by a constant increase in the per-unit power of equipment. complication of the power-system circuits, and increased load-curve nonuniformity. These features of power-system development complicate the requirements for automatic control and regulation devices, motivating constant improvement in control algorithms and hardware for their execution. Conventional excitation control schemes for large turbine generators employ analogue signal processing techniques, using electronic circuits. The technology used has not changed for many years, even though rapid advances have been made in the field of digital control. A wide variety of digital process controllers, some incorporating advanced control algorithms are now available and are widely applied in process control situations. Excitation and governing control can be viewed as the examples of the processor controls, and therefore attention turns to the replacement of the analogue automatic voltage regulator and governor by the digital controllers. Implementation of control algorithms based on advanced control techniques such as self-tuning demands powerful microprocessors. For slowly varying processes, conventional microprocessor technology is sufficient as the sampling rate can be low without loss of stability. The uses of general-purpose microprocessors or microcontrollers fall short when they are applied to high speed tasks such as excitation control in power systems. The problem is that advanced control algorithms, as used in digital filtering and discrete Fourier transforms, demand numerous multiplications and additions. When performed in software on an ordinary processor, these operations can consume too much time to provide high-speed control. Most new classes of control algorithms, along with other algorithms such as state modeling, state estimation, Kalman filtering, and optimal control can be implemented with analog circuitry. In practice, however, it is difficult to design analog

hardware that handles precise and often nonlinear behaviour in real applications. In addition, the modification of a control algorithm implemented in hardware can also be complicated. Changes may sometimes be made simply by substituting a simple component, but can also involve redesigning all part of the system. The approach to solving the speed requirements associated with modern control algorithms is to use a special kind of processor chip. Digital signal processors are constructed to speedily perform the kinds of arithmetic operations associated with digital filtering and processing. Harvard architectures, which employ separated data and instruction memories accessed by separate bus, and high speed hardware multipliers greatly increase speed •

The application of digital signal processorbased systems to the real-time control of generator terminal voltage is a novel approach. In addition to the main task of voltage regulation, the DSP can perform traditional limiting and protective functions. Digital technology also provides the opportunity for remote communication with the power plant central processor and the turbine controls. Another important advantage resulting from the utilization of DSP-based control is that the system is flexible and the parameters and options required for each individual installation are engineered into the software. This paper describes a research project aimed at the development of hardware and software necessary to implement advanced control of terminal voltage on a laboratory model turbogenerator. This is a 3KYA 4-pole machine which is driven by a d.c. motor. The generator is connected to the grid via a lumped parameter transmission line simulator. The project is divided into two sections, relating to measurement and control. The former is to be discussed in detail.

524

Z. Q. Ba, E. Swidenbank and B. W. Hogg SYSTEM DESCRIPTION

For the application mentioned, a modular, simple-to-use DSP control system is required. A possible solution is to use separate measurement and control processors. This introduces "pipelining" into the system, increasing data throughput. The idea is that an independent measurement system will undertake the task of sampling and processing all machine terminal quantities necessary to monitor system operation. This machine transmits all the information necessary for control to the relevant processors. The overlap in processing allows the secondary, control processors to implement complex algorithms within the required sampling time. The configuration of the direct digital excitation-control system for a large synchronous generator is shown in Fig.1. The whole system is designed in modular form. Two DSPs are employed in the system to perform functions of both measurement and control. The system includes the following basic units: 1. DSP processor module; 2. Digital input module (DIN); 3. Analog input module(AIN); The Processor Module The DSP (TMS320) is a single-chip processor, supported circuit are designed to support its operation. The control logic allows both TMS 320 processor and the outside device to control the address bus and data bus of the expended RAM, therefore the application program can be downloaded from outside device. As in most CPU architectures, the TMS supports one interrupt only. The measurement systems are asynchronously interrupting devices and priority interrupt control hardware was developed to support the control hardware design required by the complete system operation. This unit also arbitrates between communicating devices. The AIN Module The r .m. s. voltage, r .m. s. current, and the active and reactive power generated at machine terminals are important quantities in the operation of a synchronous generator. The voltage and current signals are obtained from voltage and current transformers. A second order low-pass filter eliminates the high frequency components and noise from the signal. Sample-and-hold is used to avoid significant errors caused by the delay in sampling. Each input is sequentially connected to an analog multiplexer, the output of which is connected to a 12 bit analog-to-digital converter (A/D). The A/D translates the analog signal into an encoded digital format.

counters, each contains two 8-bit counters, records digital signals from pulse sample circuit which AND with pulse generate clock to produce the numeric information to the processor. The contents of the register which are read by the processor at regular intervals provide sufficient information for calculate rotor angle and slip. MEASUREMENT PHILOSOPHY Although a broad spectrum of arrangements are possible for application of processors to power system measurement, the interest here centred around the fast data processing, as applied to measurement of machine terminal quantities. With the use of DSPs, much improved control performance can be achieved. The speed of these devices allows the measurement software to perform several important tasks. A fast response from the measurement system is required for sending warning semaphores to the supervision scheme of adaptive control controllers. These can be used to detect transient conditions on the system which may deteriorate model estimation. Inaccurate measurements occur frequently in power systems. Unbalanced phases and non-pure waveforms can be dealt with by the use of appropriate algorithms. Controller performance under these conditions can therefore be improved. Current research on adaptive control in the department relies on the additional feature provided by this system. Information from the past twelve samples (one cycle) is used to overcome these problems. At each sample interval (1.6 ms) the algorithm must act on a window of twelve previous samples. This heavy processing demand requires appropriate technology for implementation. The requirements are fulfilled by the use of a DSP. MEASUREMENT SOFTWARE Programs were written in assembly language because of the priority given to execution speed. These provide a solution of the follow i ng problems: sampling of analog and digital data; monitoring, processing, and transfer of data to the control processor. Tasks run asynchronously using a interrupt structure. They supply information to a central algorithm which produces the required output. On-line adjustment of timing enables the software to operate at exactly twelve times per mains cycle (50 Hz). The techniques for implementing the measurement algorithms are given in[ 2], All calculations employ integer arithmetic. To avoid loss of precision careful attention was given to the order in which the arithmetic operations were double-length arithmetic with performed and appropriate scaling was used where necessary.

The DIN Module The rotor angle of a synchronous machine is useful for determining the performance of the controller under test. Measurement of rotor angle and speed deviation (slip) are taken from the machine by means of an optical transducer which uses lamps and light sensors [ 1 ]. A signal conditioning circuit produces the pulses acceptable to the interface logic unit. The pulses from the transducer provide information relating to rotor speed and position. Digital signals from optica1-e1ectric transducer logic and are combined in hardware and used to enable the logic gate unit for proper logical operations. A 4 MHz crystal was chosen to form the pulse generator to produce maximum accuracy for the measurements. Two pair of

A number of algorithms have been developed over the years, most of which can be divided into the following Sample Plus Derivative[ 3-5] these calculate the peak amplitude and phase position from uniform samples by using relationships between the value and its derivative at an arbitrary point of the wave; Fourier and Wa1sh Transforms[ 6-7] - these utilize a pair of base functions which are correlated with the data samples to extract the component of the base function in the waveform; General Curve Fit[8] - these attempt to find the parameters which would synthesize the waveform most like that actually being provided by the power

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system. Several techniques for implementing the measurement algorithms were considered three of which are presented. Root Mean (RMSb)

Square Algorithm

for

Balanced

System

The RMSb algorithm was that originally used in previous research[ 1), and is only valid for balanced three phase systems. The following equations are used to calculate the required quantities in terms of the instantaneous voltage and currents in each phase.

v I

P

Q where VRy ' VyB ' VBR are the instantaneous phasephase v6Itages. I R, I y ' IB are the instantaneous line currents V, I, P, Q are the r.m.s. ph-ph voltage r.m.s. line current, real power and reactive power respectively. Sample Plus Derivative algorithm The SPD algorithm[ 3-5) was originally used in transmission line fault analysis. Detection of single phase fault location was found by instantaneous calculation of line impedance. The technique was adapted for three phase, non-balanced systems. A small number of current and voltage samples are used to estimate numerically the peak value of current and voltage. From these the active and reactive power can be calculated. Using values of v ' v ', i , i ', terminal quantities were k k k k derived by averaging information from the past three samples in a moving window. A central difference expression was used to calculate derivatives[ 3). V 2 pk 2 Ipk P

Q

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(v ' / W)2 k + k . 2 (i '/W)2 + 1k k . v )/2 (i k ' vk '/ W 2 + 1k k

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(v k ' i k - vk i k ' )/2W

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v

V - Peak Voltage, pk

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Ipk - Peak Current,

Fourier Analysis Algorithm The FA algorithm based on Fourier series technique to measure voltage, active and reactive power in the three-phase system is described in this section. terminal

quantities

This algorithm offers a weighted averaging process called finite time integrator. It acts as a filter centred around the main power frequency. With one period window length, this filter has the abil i ty to completely rejects DC, higher order harmoniCS, and to attenuate low frequencies. PERFORMANCE The two principle criteria for usefulness of any algorithm are accuracy and speed. Any of the methods are perfectly accurate when assumptions from which they are generated are strictly observed. However since power generator faults produce complex transient wa veforms which can not be perfectly characterized, the results will contain errors. Algorithms based on restrictive assumptions, such as th ose presuming pure 50 Hz sinusoids, performed well since the y do not process data to establish what components are actually present. However, signals other than those presumed, appear as noise and cause errors. Conversely, al gorithms based on the presumption of complex waveforms, process data more elaborately to extract the 50 Hz result from the expected transients. This improves accuracy, but may take longer. Execution Time The program execution time is an important criteria in assessment of the algorithms. For the measurement of machine terminal quantities, the fastest is the RMSb algorithm, which only provides terminal quantities for a three-phase balanced system. It can produce machine terminal quantities 12 times per cycle, and executes over 10 times faster than conventional mi cro processors. Transient State Performance The performance of the measurement system with its algorithms were tested on the micromachine system. To assess quality, the machine transient behaviour was observed to investigate performance. A short-circuit of 120 ms at machine terminals was applied for various operating conditions.

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Upper case - RMS terminal quantities, Lower case-instantaneous phase quantities. x' - derivative of x

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It should be mentioned that even though the same operation points are used for different algorithms, differences in response are due to changes in test conditions . The RMSb al gorithm was tested against a conventional, well established me asurement system for comparison. Fig.2 shows the measurement of machine terminal quantities. The results show that there is little difference between the two systems, except that the DSP can record higher peak values of terminal current when a short-circuit occurs. With respect to terminal power and reactive power, it shows that the DSP system produces higher values in reactive power when a short-circuit occurs. This improvement in accuracy is due to the use of the 12 sample window.

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(10)

P

(Vd Id + Vq I q ) / 2

(11)

Q

(Vd I q - Vq I d )/2

(12)

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Fig.3 show the transient performance of the SDP algorithm. As shown in the Figure, there is noise on the measurement, especially on real and reactive power. There are also differences between three phases, the most obvious one being terminal power, particularly when transient state occurs. The differences result from the small un balances in the phases during machine operation. Since the algorithm strictly assumes sine and 50 Hz waveform, the noise on measured quantities and harmonics within the signals are the cause of degraded measurement quality.

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The performance of the FA algorithm is shown in Fig. 4. The dissimilar behaviour of the three phases when transients occur, confirms that these are small un balances in the machine. The inherent filter within the algorithm results in smoother measurements. In order to observe the differences between the three algorithms closely, three waves are plotted together in Fig.5, the quantities of SPD and FA algorithm are taken from averaging three phases. Graphics show that the RMSb algorithm seems to give better results, since a reasonable transient behaviour of both active and reactive power are evident. The FA algorithm shows more stable responses than the SPD because of its ability to filter DC, but the SPD algorithm gives reasonable responses during transients, particularly with the reactive power. This figure gives an indication of the nonlinearity of the generator. The major differences in responses are due to a slight change in operating conditions, and not to algorithm performance. Numerical Quality Comparison Responses of different algorithms are compared against each other. Numerical quality is calculated for each operating point as the ratio of mean square signal to mean square error (residual). In transient performance comparison, the original RMSb algorithm system was taken as the basic measurement system response. This is not necessarily the best system, but is used for comparison. Responses were compared, and accuracy at different operating points assessed. Table give a comparison of numerical quality of the algorithms. Results show significant differences between algorithms with respect to the quantities of Pt. and Qt' due to the different calculation methoas used. CONCLUSION In the application, the machine transient behaviour is taken as a principle means of assessing the performance of the algorithms. It is not easy to give a uniform criteria to compare methods which have not previously been the subject of any universal comparison, especially with application to practical systems rather than a mathematical simulation. In the comparison of the algorithms for measurement of machine terminal quantities, it appears the Fourier Analysis method gives a better performance. This conclusion is only valid for the case where machine terminal quantities are required. Performance evaluation may change under different applications. A change in requirements or applications may change the results - for example, a particular combination of algorithm, sampling rate and program size may produce an efficient, easy to implement program whose advantages may override other performance deficiencies in a particular application.

The DSP-based digital control system developed in the project is an advanced concept in excitation control and protection. Tests show that the system is able to provide more accurate and faster measurements than the conventional computer or microprocessor based systems. The great advantage also comes from separating measurement from control in hardware design, this saves the control processor from sampling and data processing, and enables advanced control algorithm to be performed. Satisfactory results from the measurement system have been produced, applications of both advanced measurement and control algorithms are currently under investigation. REFERENCE 1. Pullman R.T. and Hogg, B.W. (1977). Automated measurements of computer control of a micromachine system. lEE Conference Publication No. 152. 2. ZhiQian Bo (1988). Development of a multiprocessor system for control of a laboratory turbogenerator. Ph.D. Thesis. 3. Barry J. Mann, and I.F. Morrison (1971). Digital calculation of impedance for transmission line protection. IEEE PAS-90 No.l, 270-279. 4. M. Ramamoorty (1971). A Note on impedance measurement using digital computers. IEE-IERE proc. (India) Volume 9, N06, 234-7. 5. G.D. Rockefeller. and E.A. Udren (1972). Highspeed distance relaying using a digital computer 1system description, and 11 - test results. TPA S-9l, No.3, 1235-1258 6. A. G. Phadke, T. Hlibka, and M. Ibrahim (1975). A digital computer system for VHV substations; analysis and field tests. Summer Power Meeting. IEEE Paper No. F75, 543-9. 7. O. P. Malik, G. S. Hope and J. Chang (1981). A microprocessor-based power measurement device for control applications. The Eighth Triennial Word Congress of IFAC, 2099-2104 8. J. G. Gilbert and R. J. Shovlin (1975). Highspeed transmission line fault impedance calculation using a dedicated minicomputer. TPAS-94, No.3, 872883 9. Edwin, Swidenbank (1984). Identification of large turbogenerator units. Ph.D Thesis, Dept. of Elec. Eng., Queen's Univ. of Belfast. 10. Z. Q. Bo, E. Swidenbank and B. W. Hogg (1988). An advanced microprocessor system for control of laboratory turbogenerator. Control 88', lEE International conference. 11. Wu,Q.H. and Hogg,B.W. (1987). Self-tuning regulators in multi-machine power system. Proc. 22th Universities Power Engineering Conference, 5-

8. 12. IBRAHIM, A.S., HOGG, B.W. and SHARAF, M.M. (1986). Self-tuning regulators for turbogenerators. Proc. 2nd IFAC Workshop on Modelling and Control of Electric Power Plants, Philadelphia, 25-30.

The experimental results also show that the programs developed are able to give better performance than the existing system, with more information and greater speed. Consideration has been given towards developing a package of complete software for real time measurement applications in power plant. Additional features, such as protection schemes can be easily added, since the program can be easily expanded due to its structure.

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ALGORITHMS RMSb

SPD

FA

VOLTAGE

99.29595%

99.42794%

99.54465%

CURRENT

96.94576%

93.49604%

97.08705%

POWER

98.77885%

97.52987%

96.56910%

R. POWER

90.75313%

87.68510%

91.31882%

TOTAL

96.44342%

94.53474%

96.12991%

TABLE 1.

COMPARISON OF ALGORITHMS (Transient-State)