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ukZ, Damir NouoselX

s open transmission access is becoming a reality, a major concern of electric power utilities is to maintain the reliability of the grid. Increased power transfers raise concerns about steady-state overloads, increased

risks of voltage collapses, and potential stability problems. Strengthening the protection and control strategies is what utilities must do to prevent a local problem from spreading to other parts of the grid.

This article defir:es the framework and motivation for development of a multilayered protection and control scheme that starts with local measurement devices and integrates higher-level control schemes into an overall control strategy.

Protection and Control Approaches Although the complexity of the voltage collapse problem has beeG studied by various researchers, many questions still remain unanswered. The multitude of approaches have resulted in the implementation of a few protection and control schemes against voltage collapse.

The symptoms often associated with collapse are low voltage profile, high consumption, heavy transmission system loading, long distances between most of the generation and loads, and insufficient reactivepower compensation facil- ities, The onset of voltage collapse can sometimes be precipitated by the activation of limiters when some of the generators reach their reactive generation capability limits and cannot maintain voltages with increasing demand.

Disturbances leading to potential voltage instability problems can be split into two categories:

Disturbances of topology, which may involve equipment outages, or faults followed by equipment outages Load disturbances, representing the fluctuations of load which may have dynamics of their own.

They can be slow load changes (normal random load fluctuations) or fast load fluctuations (such as outages of large blocks of loads). A very typical sce- nario may involve a rapid load pickup (in some recorded cases several hundred MW per minute), corresponding deterioration of the voltage profile in the network, triggering of automatic protection and control events (such as activation of limiters in generator excitation, tap blocking of transformers, load shedding etc.), and final descent to a collapse, often accompanied by a cascaded action of assorted protective relaying.

An example of voltage collapse simulated on a New England system model is shown in Figure 1. The random load is modeled as increasing in time linearly. The onset of collapse is identified as a point where slopes of load voltages (shown here for 10 representative buses) suddenly change downwards, and the system loses its stable equilibrium.

I ABB Electric Systems Technology Institute Georgia Institute of Technology

40 IEEE Computer Applications in Power ISSN 08950156/97/$10.0001997 IEEE

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Smart Devices An element of great importance in any mitigation scheme is to track the proximity of the power system to a collapse. Knowing such proximity permits proper utilization of control and protective equipment to steer the system from a cri- sis. At present, estimating the proximity to collapse in real-time still faces many difficulties. Beside computational issues (e.g., speed, complexity, etc.), any cen- tralcontrol method is subject to the reliability of longdistance data communications. Although this problem is mitigated by the increasing use of redundant data from microwave, optical fiber, and wireless systems and through state estimation methods, there is always concern when reliance must be placed on receiving data from a remote location. To reduce or eliminate the need for this transmission of data, a local undervoltage relay (or any of its variations) is often used. The collapse is deemed imminent when the observed voltage falls below a threshold. Selecting a proper value for the threshold, however, can be diffi- cult, because systems may experience a normal voltage when they are at the brink of collapse.

Advances in microprocessor technology have made it affordable to improve the computing capabilities of existing decentralized subsystems. Local devices can now utilize advanced algorithms to make local decisions based on local measurements and possibly selected remote information. Utilities can start improving the control and protection of their grids by enhancing devices already in use at substations. The enhanced devices form the line of defense at the low level and offer the most advanced protection schemes that use local information. In time, the communication links will gradually be built to integrate all local devices into a control network. This progressive strategy helps the util- ity to spread its investment over time.

Voltage Instability Prediction Tracking how close a system operation is to a point of collapse has always been a challenging problem. Toward practical applications, the key element that dis- tinguishes one method from another is in regarding what information is required. Most methods in existence today require that system-wide information be available. Fortunately, recent R&D efforts to make effective use of local measurements have resulted in smart algorithms that can predict collapse from

local information. Implementation of such smart algorithms is simpler, faster,

&fultilayeg-ed protection and less costly when compared with the

and control schemes Figure 2 shows a load bus and the traditional approach.

start with L Q C ~ rest of the system treated as a Thevenin equivalent. The following principle is well known in electriccircuit theory: measurement deuices

and integrate higher level control schemes Maximal power transfer tf lZapp I = I.&" I

where the apparent impedance Zcpp is merely the ratio between the voltage and current phasors measured at the bus. This maximal-power-transfer relation, holding true regardless of the load char- acteristic, separates the impedance plane into two regions, as shown in Figure 3. As the load varies, its Zapp traces a path in the plane, and voltage instability

.- occurs, in the steady-state sense, when ZaDp crosses the Thevenin circle. Tracking parameters as the system approaches voltage instability, th

fore, becomes the problem of tracking the distance of the present-time Z, the Thevenin circle. This is the principle behind the voltage instability pre tor (VIP). The circle is not a fixed object, because it represents the rest of system lumped together; such collection involves thousands of pieces of eq

ere- ,p to !dit- the uip-

7 41 October 199


Figure I . Voltage collapse simulated on a New England system model

Figure 2. Local bus and the rest of the system treated as a Thevenin equivalent

ment, any of which can change with time. Quite likely when the voltage is unstable, the circle expands (transmission becoming weaker) and the impedance Zu,, moves toward it (increasing load).

Tracking the Thevenin equivalent is essential for a VIP-based device to properly detect a voltage collapse. There are many methods to track the Thevenin parameters, and they can be based on the relation E =I/ + Z,,,, . I , where the unknowns are E (equivalent source in Figure 2) and Z,,,. In the ideal condition, two different measurement sets (V and I) taken at two different times are sufficient to com- pute the two unknowns. In the real environment, however, measurements are not precise, and the Thevenin parameters drift due to the system’s changing conditions. To suppress numerical oscil- lations in the estimated parameters, a larger data window must be used. Intuitively, this window must contain sufficient variations in the measurements. Since load variations take place with a nonuniform rate, the time span of the window is not fixed. In fact, a faster variation in the data takes less time for a VIP-based device to produce an output.

For illustration, a multinode power network model is driven to maximal transfer by gradually increasing the load demand. The critical loading is 163.4 percent of the base-case loading; beyond this loading level, the power-flow equations admit no solutions. A VIP is placed at each load bus and is unaware of the changes that take place in the rest of the network (no data communications). Its inputs are the local measurements (bus voltage and load current) and its output is a stream of Thevenin parameters which vary with time. The plot in Figure 4 shows that the estimated Thevenin impedance merges with the load impedance at the point of collapse. The load increase is evident by a decaying load-impedance profile.

VIP Interpretation and Applications VIP can be viewed as an adaptive relay. Two different interpretations can be given. The first interpretation of VIP is direct from Figure 3: an impedance relay with a self-tuned setting (the setting being the vary ing radius of the red circle). The second interpretation is an adaptive voltage relay, and can be better seen when the two curves in Figure 4 are multiplied by the load current profile. The result is shown in Fig- ure 5; the green curve is associated with the load voltage, and the red curve is associated with the voltage drop across the Thevenin impedance. If one views the red curve as the voltage setpoint of the relay, then the setpoint is tuned so that at the collapse, the load voltage is equal to the setpoint. Recall that the conventional voltage relay measures the voltage only, and its decision is based on a fixed set-

42 IEEE Computer Applications in Power

I 1


Tracking the Thevenin equivalent is essential for a VIP-based device to properly

detect a voltage collapse

point. The VIP, on the other hand, makes use of an additional input (namely, electric current) to adapt its setpoint to the system’s condition.

The algorithm can be coded and embedded in existing microprocessor-based relays/controllers, or implemented as an individual unit. The required inputs are local bus voltage and load current, which are already available at substations for other applications. The output of the VIP can be used to guide control actions at the substation. For example, if the total load connected to the substation is found to be excessive by the VIP (Zapp in Figure 3 is sufficiently close to the red circle), a partial shedding can be issued to maintain a sufficient margin. In another example, tap-changing transformers are frequently used to regulate the voltage on the load side. Their actions basically drain the reactive power from the system to support the voltage at their loads. A VIP that processes measurements on the primary side of a tap-changing transformer can detect when the drain is excessive, and thus the decision to block the tapchanging action can be carried out.

Another application is to enhance the performance of a static var controller (SVC) by adding voltage-collapse prediction. Traditionally, SVC behavior can mask the imminent collapse, leading to sudden and unexpected loss of reliable power supply. The VIP can be incorporated to ensure accurate collapse prediction taking into account the SVC operation.

Integrated Control and Protection Today’s communication and computer technologies have created a new revolution in the power industry, especially in the field of power system control where vertical integration is much improved. Communica- tion capability is one of the potential benefits for computer relays, which communicate not only with a center, but with each other. This in turn will facilitate the overall system-wide protection and control phi- losophy.

The Self-Managing And Reliable Transmission Grid (SMARTGrid) is seen as the future of protection and control systems. It is an automated system of monitoring, control, and protection devices that improves the reliability of the transmission grid by preventing wide-spread break-ups. It utilizes information technology to improve grid reliability and capability. It builds on existing components such as

Figure 3. Maximal power transfer is reached (voltage instability) when the apparent impedance o f the load lands on the Thevenin circle, I zapp I = I zm,, I

Figure 4. Thevenin impedance and load impedance merge a t the point of collapse

Figure 5. VIP can be viewed as a voltage relay with an adaptive setpoint

October 1997 43


G f i eir gri

the local controllers together: ‘Ontinu-

OuS1Y report their to the The ten- tral computer combines the reported proximities to collapse, performs extra calculations and issues coordinating The central computer can override the load-shedding decision of individual devices.

Smart devices processing Only local measurements can be counted upon when center-based emergency con- trois fail to mitigate an aggravating situation. These

In a SMARTGrid’ smart devices such as

relays, sensors, meters, energy manage- ment systems, SCADA, SVC, etc., by adding better algorithms and utilizing information more effectively. The devices are coordinated under several hierarchical levels. Figure 6 shows a two-level design.

At the substation level, each device processes local measurements (substation voltage, load current, etc.), assesses the proximity to system instability or thermal capability, and carries out its own control decisions. No long-distance communications are required to implement the SMARTGrid concept at the substation level. At the regional level, several regional computers from substation-level devices and perform the coordinating role. The process is simi-

Figure 6. Smart devices such as VIP-based devices are deployed to form raw and processed data the low-level control, and communication links to regional centers and

h &her are needed for proper coordination

of Washington. He was a visiting faculty member at Clemson University during 1991-1993, and is now with the Power Systems Center, ABB Elec- tric Systems Technology Institute, in Raleigh, North Carolina. His areas of interest in power systems include stability, computer-based protection and control, and power quality. He is an IEEE member.

Miroslav M. Begovic received his BSEE and MSEE from Belgrade University, and his PhD in electrical engineering from Virginia Polytech- nic Institute and State University. Since 1989, he has been a member of the faculty of the School of Electrical and Computer Engineering, Geor- gia Institute of Technology in Atlanta, Georgia, where he currently holds the position of associate professor. His current interests are in the general area of computer applications in power system monitoring,

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lar at the global level. Long-distance communications (SCADA or dedicated links) are required for the regional and global levels.

There are two major steps in realizing a SMARTGrid. The first step is to provide immediate solutions by means of enhanced products that will improve the system reliability and performance. For example, imple- menting the VIP method is done at the device level, and does not require communication links. This strategy is appealing to utilities, because they need not invest in developing new techniques, but can actually implement existing technologies. Implementation of these technologies form the substation or local level of SMARTGrid hierarchy. The second step is the integration, which rewires advanced technologies and methods to tie all

devices also form the fall-&k protection and control scheme when communications channels fail.

for any global

Estimate Voltage-Stability Margin,” PICA ’97: Proceedings of the 20th Intemational Conference on Power Industry Computer Application, IEEE, May 1997.

C. W. Taylor, Power System Voltage Stability, McGraw-Hill, 1994. Proceedings of Bulk Power System Voltage Phenomena-Ill: Voltage Sta-

bility, Security, and Control, Davos, Switzerland, August 1994. IEEE Power Systems Relaying Committee, Working Group K12,

“Voltage Collapse Mitigation,” 1995, available on the World-Wide Web, http://www.rt66.com/-w5sr/psrc.html.

C. Barbier and J. Barret, “An Analysis of Phenomena of Voltage Col- lapse on a Transmission System,” Revue Genem.de de I’Electricite, spe- cial CIGFE issue, pages 3-21, July 1980.

N. Grudunin and I. Roytelman, “Heading Off Emergencies in Large Electric Grids,” IEEE Spectrum, April 1997, pp. 4247.

protection and Control, and design and analysis of renewable energy sources. He is a member of Sigma Xi, Tau Beta Pi, Eta Kappa Nu, and

Damir Novosel is manager of the Power System Center at ABB Elec- Phi Kappa Phi, and is an IEEE Senior Member.

Biographies Khoi Vu received his BSEE, MSEE, and PhD degrees from the University

I tric Systems Technology Institute. He received his PhD from Mississip- pi State University, where he was a Fulbright scholar, in 1991. His research area is computer-based protection and control of power sys- terns. He is a member of Eta Kappa Nu and an IEEE Senior Member.

For Further ing K. VU, M. Begovic, D. Novosel, M. Saha, “Use of Local Measurements to

44 IEEE Computer Applications in Power


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