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Handling small unobservable pockets in state estimation process
Electric Power Systems Research 50 (1999) 17 – 21
Handling small unobservable pockets in state estimation process Mesut Muslu a,*, Richard D. Shultz b, Mary Churchill c a
b
Electrical Engineering Department, Uni6ersity of Wisconsin-Platte6ille, 1 Uni6ersity Plaza, Platte6ille, WI 53818 -3099, USA College of Engineering Mathematics and Sciences, Uni6ersity of Wisconsin-Platte6ille, 1 Uni6ersity Plaza, Platte6ille, WI 53818 -3099, USA c Wisconsin Power and Light Company, Madison, WI 53701, USA Received 5 April 1998; accepted 27 April 1998
Abstract Most power systems have pockets where not all flows and injects are measured and therefore, a part of the system is not observable. The manner in which these pockets are handled during the state estimation process may make a significant difference in the outcome of the state estimation. This paper addresses the problems arising from such small pockets in a power system and provides a method for handling small pockets. © 1999 Elsevier Science S.A. All rights reserved. Keywords: Unobservable pockets; State estimation; Power systems
1. Introduction State estimation has become a standard component in most energy management systems [1 – 3]. State estimation involves the processing of a set of measurements to accurately estimate the state of the power system in real time. The result of the state estimation forms the basis for monitoring and checking the security of the system, as well as providing data for various optimization techniques. In a power system, when the set of measurements is sufficient in number and well distributed geographically, state estimator (SE) gives an estimate of the state of the system and the power system is called observable [4]. When there is sufficient redundancy in measurements, SE is able to identify ‘bad’ data. In real power systems however, there are always parts of the system that are not fully observable. This unobservable part, which will be called an unobservable pocket, may be a very small part of the system (containing a few buses) or it may contain tens of buses depending on the size of the system. In fact, the number and size of these pockets are dynamic in nature These unobservable pockets may be a result of: (a) a change in the system topology as a result of some switching actions; (b) the * Corresponding author. Tel.: +1-608-3421561; fax: + 1-6083421566.
lack of reliable telemetered data from some RTUs or discarding some bad data coming from RTUs; or (c) tapping of lines without providing additional telemetered data. The way these pockets are handled in the state estimation process may make a significant difference in the outcome of SE, particularly in the unobservable part of the system. This paper describes the problems created by small pockets and suggests a method to minimize the errors involved in and around these small pockets. The paper also presents the experience of a utility with these small pockets in their system and how these problems can be alleviated using the suggested method.
2. Small pocket problem SE uses a topology processor to identify the observable part of the system first. The boundary between the observable system and an unobservable pocket is usually an observable bus with no telemetry. With fully telemetered data at a bus, the voltage at an un-telemetered bus can be estimated from the telemetered line flow between the two buses which is measured at the telemetered bus. The observable un-telemetered bus will be called a barely observable bus in this paper and the telemetered bus which allows it to be observable will be called a connecting bus. This is illustrated in Fig. 1.
0378-7796/99/$ - see front matter © 1999 Elsevier Science S.A. All rights reserved. PII: S0378-7796(98)00079-0
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M. Muslu et al. / Electric Power Systems Research 50 (1999) 17–21
Fig. 1. A power system with small unobservable buses.
After the unobservable pockets are identified, SE estimates the state of the system in two steps. First, it solves for the observable part of the system using telemetered data and calculates the voltages at all buses in the observable system including the voltages at the barely observable buses. To solve the unobservable part of the system however, SE uses the results obtained from the observable system (voltages at barely observable buses for example) and considers them as high quality measurements with very high confidence values. In addition, SE uses pseudo measurements and scattered telemetry not used previously by the state estimator [5] to estimate the state of the system in the unobservable part. Pseudo measurements and scheduled injections are usually treated as low quality measurements with low confidence factors. During state estimation, they are modified more frequently compared to telemetered data. In the state estimation process, since the second step receives data from the first step and treats them as high quality measurements, any error in these estimated values will be dumped on the unobservable system. In the second step, the state estimator allocates these errors among the unobservable buses. Practically, such errors are dumped on the unobservable buses that are closest to the observable system. For example, when the observable system is solved, SE gives the voltages (magnitude and angle) at all connecting buses. Since the power flow from these observable buses are telemetered, the voltages at the barely observable buses can be calculated. Let us assume that two of these buses (buses k and l in Fig. 1) in the pocket are connected to each other by a line. Then, with the voltages at buses k and l estimated, the flows between k and l
and the injects at buses k and bus l can be estimated to match those voltages. If the estimated voltages at the connecting buses are accurate and the telemetered flow from the connecting buses to the barely observable buses are correct, then the estimated voltages and injects at k and l will be accurate. However, a problem arises when SE results in voltages at k and l that have some errors and/or telemetered flow from connecting buses to barely observable buses have some errors. For example, the telemetered flow from connecting buses may result in a higher angle difference between bus k and l. As a result, the estimated power flow from k to l is forced to be very large resulting in bus k looking like a large generator bus and bus l looking like a large load center. Often, in such cases where either the first step of state estimation results in some error at the connecting bus voltages, or telemetered flow from connecting buses to the barely observable buses is erroneous, SE comes up with meaningless bus injections like negative loads at substation load centers or loads that are several times larger than their reasonable values. Such large negative power injections at load centers are observed by many power companies including Wisconsin Power and Light [6] and Illinois Power [5]. This creates problems in two areas. First, when a system operator sees a solution where there are large generation injects at known load buses or where the loads are several times larger than reasonable values, then the confidence in the entire state estimator is diminished. Second, a very large power flow from one bus to another may affect the system losses. This may also adversely affect the B coefficients or penalty factors, impacting optimization calculations.
M. Muslu et al. / Electric Power Systems Research 50 (1999) 17–21
3. Ways to handle small pockets
4. Applications
The primary reason why SEs are coming up with such meaningless flows or injects in state estimation is that they solve for the observable part of the system first and dump the errors from the first step onto the unobservable part of the system in the second step of the state estimation process. In fact, these errors are mostly dumped on the buses close to the observable system to minimize error calculations. Additional error occurs if the SE is using pseudo measurements such as using preset table values for power injects that do not reflect the current system conditions. This additional error can be reduced, however, by simply calculating the net flow into a pocket and distributing that net load to the load points by preset table ratios. Although this would reduce the additional error of not considering existing system conditions, any error from the first step of the state estimation process into the unobservable pocket would still appear at the load points nearest the connecting points. Again, some of the original problems can still exist. Wisconsin Power and Light Company and ABB approached this problem by performing small pocket state estimations before the state of the observable part of the system is estimated. At each small pocket, the telemetered values at the connecting buses along with the pseudo injections as described in the first approach are used as inputs to a state estimation solution for each of the small pockets prior to the observable system state estimation. The results of the small pocket state estimation for each pocket are then used to estimate the state of the observable system. With this approach, any error in telemetered data at the connecting buses will be distributed to more than one bus.
4.1. Case I
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Although this case is an extreme situation, it illustrates the small pocket problem very well. Fig. 2 shows a small pocket (containing two buses, WEI – Y132 and WPK) in the Wisconsin Power and Light Company system. The buses, WKE and MGE – HKP, are the connecting buses and have measured voltages and measured flows into the pocket. The measured data is shown in parentheses. All other values in Fig. 2 are estimated values without small pocket calculations. Note that the estimated voltage (magnitude and angle) at bus WEI – Y132 comes from the voltage at and flow from bus WKE. Similarly, the estimated voltage (magnitude and angle) at bus WPK comes from the voltage at and flow from bus MGE – HKP. The result is that a large voltage drop/angle difference must exist between buses WPK and WEI – Y132 in order to compensate for errors in the estimated voltages at connecting buses or errors in flow measurements into the pocket. This requires the load at WPK to become a large generator (539.3 MW) and the load at WEI – Y132 to increase to 545.9 MW. It is clear that these injections are unreasonable for substations which normally have loads with a maximum value of approximately 30 MW. Fig. 3. shows the same pocket with the small pocket state estimation utilized. In this case, the flows on all lines in the pocket, load at the buses and bus voltages have ‘reasonable’ values. However, a larger mismatch does occur with the estimated values and measured flows on the lines at the connecting buses.
Fig. 2. State estimation without small pocket calculations.
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M. Muslu et al. / Electric Power Systems Research 50 (1999) 17–21
Fig. 3. State estimation with small pocket calculations.
4.2. Case II This case illustrates a more typical situation. Once again, the measured data is shown in parentheses. Fig. 4 shows estimated values without small pocket calculations. All three buses in the pocket are small load buses. The buses BMS and ADM are the barely observable buses and KRW and PTG are the connecting buses. Notice that the injects at bus ADM indicates that it is a generator bus. Also, the injects at bus BMS are significantly higher than their ‘reasonable’ values.
Fig. 5 shows the same pocket where estimated values are obtained by using small pocket calculations. All the loads are well within their ‘reasonable’ values. The VAR flow at the connecting buses is estimated at a value different from the measured data, but is still well within the reasonable range. From the above examples, it can be seen that small pocket calculations are very effective in eliminating large meaningless estimates associated with unobservable pockets in a power system. Notice that a small pocket state estimation has to be carried out for each
Fig. 4. Case II without small pocket calculations.
Fig. 5. Case II with small pocket calculations.
M. Muslu et al. / Electric Power Systems Research 50 (1999) 17–21
pocket in a power system before the observable part of the system can be solved. Experience from the Wisconsin Power and Light Company system indicates that the number of such pockets at any time may be as high as 50 and the number of unobservable buses in each pocket ranges from 2 to 18 buses.
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[5] M. Assadian, R. Goddard, H.W. Hong, D. French, Field operational experience with on line state estimator, IEEE Trans. Power Syst. 9 (1) (1994) 50 – 56. [6] R.D. Shultz, M. Churchill, D. Ellestad, Experience with small unobservable pocket calculations in state estimation solutions, Proc. American Power Conf., Chicago, IL, April 1995.
Biographies
5. Conclusions The manner in which state estimators handle small unobservable pockets in a power system may make a significant difference in the results, particularly around the barely observable buses of the system. When the error from estimating the state of the fully observable part first is dumped on the unobservable part, the SE may come up with ‘unreasonable’ flows and injects that may influence the confidence of the operator in the system, or may impact the losses in the system. Carrying out a small pocket calculation for each unobservable pocket and using the results in estimating the state of the full observable system alleviates most of the problems of meaningless injects and flows associated with these pockets. Performing small state estimations prior to the full observable system state estimation introduces some error into the observable system solution. However, this error is relatively small compared to erroneous flows and injects experienced with other approaches. The results of this approach give reasonable input data for various optimization techniques.
References [1] A. Bose, K. Clements, Real time modeling of power networks, Proc. IEEE 75 (1987). [2] F.F. Wu, Power system state estimation—a survey, Electr. Power Energy Syst. 12 (1990) 80–97. [3] L. Holten, A. Gjelsvik, S. Aam, F.F. Wu, Comparison of different methods in state estimation, IEEE Trans. Power Syst. 3 (4) (1988) 1798 – 1806. [4] A. Monticelli, F.F. Wu, Network observability: theory, IEEE Trans. Power Appar. Syst. PAS-104 (5) (1985) 1042–1048.
.
Mesut Muslu (M) received his B.S. degree in electrical engineering from the Middle East Technical University, Ankara, Turkey in 1979. He received both his M.S. degree in engineering management and Ph.D. degree in electrical engineering from the University of Missouri-Rolla in 1980 and 1986, respectively. He is currently Professor of electrical engineering at the University of Wisconsin-Platteville. His research interest is in computer applications to power systems, state estimation and expert systems. Dr Muslu is a member of the IEEE Power Engineering society, Tau Beta PI and Sigma Xi. He is a registered professional engineer in the state of Wisconsin. Richard D. Shultz (SM) received his B.S.E.E. and M.S.E.E degrees from the University of Illinois Urbana-Champaign in 1973 and 1976, respectively. He received his Ph.D. in electrical engineering from Iowa State University in 1979. Dr Shultz has been associated with several utilities and universities during his career. He is presently chair of the Electrical Engineering Department at the University of Wisconsin-Platteville. His area of interest is computer application to power systems. Mary Churchill Received her B.S. degree in electrical engineering from the University of WisconsinMadison. For the past 7 years, she has worked at the System Operations Center of Wisconsin Power and Light Company. Her duties include the support and development of advanced applications for Wisconsin Power and Light Company’s energy management system.
Handling small unobservable pockets in state estimation process Mesut Muslu a,*, Richard D. Shultz b, Mary Churchill c a
b
Electrical Engineering Department, Uni6ersity of Wisconsin-Platte6ille, 1 Uni6ersity Plaza, Platte6ille, WI 53818 -3099, USA College of Engineering Mathematics and Sciences, Uni6ersity of Wisconsin-Platte6ille, 1 Uni6ersity Plaza, Platte6ille, WI 53818 -3099, USA c Wisconsin Power and Light Company, Madison, WI 53701, USA Received 5 April 1998; accepted 27 April 1998
Abstract Most power systems have pockets where not all flows and injects are measured and therefore, a part of the system is not observable. The manner in which these pockets are handled during the state estimation process may make a significant difference in the outcome of the state estimation. This paper addresses the problems arising from such small pockets in a power system and provides a method for handling small pockets. © 1999 Elsevier Science S.A. All rights reserved. Keywords: Unobservable pockets; State estimation; Power systems
1. Introduction State estimation has become a standard component in most energy management systems [1 – 3]. State estimation involves the processing of a set of measurements to accurately estimate the state of the power system in real time. The result of the state estimation forms the basis for monitoring and checking the security of the system, as well as providing data for various optimization techniques. In a power system, when the set of measurements is sufficient in number and well distributed geographically, state estimator (SE) gives an estimate of the state of the system and the power system is called observable [4]. When there is sufficient redundancy in measurements, SE is able to identify ‘bad’ data. In real power systems however, there are always parts of the system that are not fully observable. This unobservable part, which will be called an unobservable pocket, may be a very small part of the system (containing a few buses) or it may contain tens of buses depending on the size of the system. In fact, the number and size of these pockets are dynamic in nature These unobservable pockets may be a result of: (a) a change in the system topology as a result of some switching actions; (b) the * Corresponding author. Tel.: +1-608-3421561; fax: + 1-6083421566.
lack of reliable telemetered data from some RTUs or discarding some bad data coming from RTUs; or (c) tapping of lines without providing additional telemetered data. The way these pockets are handled in the state estimation process may make a significant difference in the outcome of SE, particularly in the unobservable part of the system. This paper describes the problems created by small pockets and suggests a method to minimize the errors involved in and around these small pockets. The paper also presents the experience of a utility with these small pockets in their system and how these problems can be alleviated using the suggested method.
2. Small pocket problem SE uses a topology processor to identify the observable part of the system first. The boundary between the observable system and an unobservable pocket is usually an observable bus with no telemetry. With fully telemetered data at a bus, the voltage at an un-telemetered bus can be estimated from the telemetered line flow between the two buses which is measured at the telemetered bus. The observable un-telemetered bus will be called a barely observable bus in this paper and the telemetered bus which allows it to be observable will be called a connecting bus. This is illustrated in Fig. 1.
0378-7796/99/$ - see front matter © 1999 Elsevier Science S.A. All rights reserved. PII: S0378-7796(98)00079-0
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M. Muslu et al. / Electric Power Systems Research 50 (1999) 17–21
Fig. 1. A power system with small unobservable buses.
After the unobservable pockets are identified, SE estimates the state of the system in two steps. First, it solves for the observable part of the system using telemetered data and calculates the voltages at all buses in the observable system including the voltages at the barely observable buses. To solve the unobservable part of the system however, SE uses the results obtained from the observable system (voltages at barely observable buses for example) and considers them as high quality measurements with very high confidence values. In addition, SE uses pseudo measurements and scattered telemetry not used previously by the state estimator [5] to estimate the state of the system in the unobservable part. Pseudo measurements and scheduled injections are usually treated as low quality measurements with low confidence factors. During state estimation, they are modified more frequently compared to telemetered data. In the state estimation process, since the second step receives data from the first step and treats them as high quality measurements, any error in these estimated values will be dumped on the unobservable system. In the second step, the state estimator allocates these errors among the unobservable buses. Practically, such errors are dumped on the unobservable buses that are closest to the observable system. For example, when the observable system is solved, SE gives the voltages (magnitude and angle) at all connecting buses. Since the power flow from these observable buses are telemetered, the voltages at the barely observable buses can be calculated. Let us assume that two of these buses (buses k and l in Fig. 1) in the pocket are connected to each other by a line. Then, with the voltages at buses k and l estimated, the flows between k and l
and the injects at buses k and bus l can be estimated to match those voltages. If the estimated voltages at the connecting buses are accurate and the telemetered flow from the connecting buses to the barely observable buses are correct, then the estimated voltages and injects at k and l will be accurate. However, a problem arises when SE results in voltages at k and l that have some errors and/or telemetered flow from connecting buses to barely observable buses have some errors. For example, the telemetered flow from connecting buses may result in a higher angle difference between bus k and l. As a result, the estimated power flow from k to l is forced to be very large resulting in bus k looking like a large generator bus and bus l looking like a large load center. Often, in such cases where either the first step of state estimation results in some error at the connecting bus voltages, or telemetered flow from connecting buses to the barely observable buses is erroneous, SE comes up with meaningless bus injections like negative loads at substation load centers or loads that are several times larger than their reasonable values. Such large negative power injections at load centers are observed by many power companies including Wisconsin Power and Light [6] and Illinois Power [5]. This creates problems in two areas. First, when a system operator sees a solution where there are large generation injects at known load buses or where the loads are several times larger than reasonable values, then the confidence in the entire state estimator is diminished. Second, a very large power flow from one bus to another may affect the system losses. This may also adversely affect the B coefficients or penalty factors, impacting optimization calculations.
M. Muslu et al. / Electric Power Systems Research 50 (1999) 17–21
3. Ways to handle small pockets
4. Applications
The primary reason why SEs are coming up with such meaningless flows or injects in state estimation is that they solve for the observable part of the system first and dump the errors from the first step onto the unobservable part of the system in the second step of the state estimation process. In fact, these errors are mostly dumped on the buses close to the observable system to minimize error calculations. Additional error occurs if the SE is using pseudo measurements such as using preset table values for power injects that do not reflect the current system conditions. This additional error can be reduced, however, by simply calculating the net flow into a pocket and distributing that net load to the load points by preset table ratios. Although this would reduce the additional error of not considering existing system conditions, any error from the first step of the state estimation process into the unobservable pocket would still appear at the load points nearest the connecting points. Again, some of the original problems can still exist. Wisconsin Power and Light Company and ABB approached this problem by performing small pocket state estimations before the state of the observable part of the system is estimated. At each small pocket, the telemetered values at the connecting buses along with the pseudo injections as described in the first approach are used as inputs to a state estimation solution for each of the small pockets prior to the observable system state estimation. The results of the small pocket state estimation for each pocket are then used to estimate the state of the observable system. With this approach, any error in telemetered data at the connecting buses will be distributed to more than one bus.
4.1. Case I
19
Although this case is an extreme situation, it illustrates the small pocket problem very well. Fig. 2 shows a small pocket (containing two buses, WEI – Y132 and WPK) in the Wisconsin Power and Light Company system. The buses, WKE and MGE – HKP, are the connecting buses and have measured voltages and measured flows into the pocket. The measured data is shown in parentheses. All other values in Fig. 2 are estimated values without small pocket calculations. Note that the estimated voltage (magnitude and angle) at bus WEI – Y132 comes from the voltage at and flow from bus WKE. Similarly, the estimated voltage (magnitude and angle) at bus WPK comes from the voltage at and flow from bus MGE – HKP. The result is that a large voltage drop/angle difference must exist between buses WPK and WEI – Y132 in order to compensate for errors in the estimated voltages at connecting buses or errors in flow measurements into the pocket. This requires the load at WPK to become a large generator (539.3 MW) and the load at WEI – Y132 to increase to 545.9 MW. It is clear that these injections are unreasonable for substations which normally have loads with a maximum value of approximately 30 MW. Fig. 3. shows the same pocket with the small pocket state estimation utilized. In this case, the flows on all lines in the pocket, load at the buses and bus voltages have ‘reasonable’ values. However, a larger mismatch does occur with the estimated values and measured flows on the lines at the connecting buses.
Fig. 2. State estimation without small pocket calculations.
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M. Muslu et al. / Electric Power Systems Research 50 (1999) 17–21
Fig. 3. State estimation with small pocket calculations.
4.2. Case II This case illustrates a more typical situation. Once again, the measured data is shown in parentheses. Fig. 4 shows estimated values without small pocket calculations. All three buses in the pocket are small load buses. The buses BMS and ADM are the barely observable buses and KRW and PTG are the connecting buses. Notice that the injects at bus ADM indicates that it is a generator bus. Also, the injects at bus BMS are significantly higher than their ‘reasonable’ values.
Fig. 5 shows the same pocket where estimated values are obtained by using small pocket calculations. All the loads are well within their ‘reasonable’ values. The VAR flow at the connecting buses is estimated at a value different from the measured data, but is still well within the reasonable range. From the above examples, it can be seen that small pocket calculations are very effective in eliminating large meaningless estimates associated with unobservable pockets in a power system. Notice that a small pocket state estimation has to be carried out for each
Fig. 4. Case II without small pocket calculations.
Fig. 5. Case II with small pocket calculations.
M. Muslu et al. / Electric Power Systems Research 50 (1999) 17–21
pocket in a power system before the observable part of the system can be solved. Experience from the Wisconsin Power and Light Company system indicates that the number of such pockets at any time may be as high as 50 and the number of unobservable buses in each pocket ranges from 2 to 18 buses.
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[5] M. Assadian, R. Goddard, H.W. Hong, D. French, Field operational experience with on line state estimator, IEEE Trans. Power Syst. 9 (1) (1994) 50 – 56. [6] R.D. Shultz, M. Churchill, D. Ellestad, Experience with small unobservable pocket calculations in state estimation solutions, Proc. American Power Conf., Chicago, IL, April 1995.
Biographies
5. Conclusions The manner in which state estimators handle small unobservable pockets in a power system may make a significant difference in the results, particularly around the barely observable buses of the system. When the error from estimating the state of the fully observable part first is dumped on the unobservable part, the SE may come up with ‘unreasonable’ flows and injects that may influence the confidence of the operator in the system, or may impact the losses in the system. Carrying out a small pocket calculation for each unobservable pocket and using the results in estimating the state of the full observable system alleviates most of the problems of meaningless injects and flows associated with these pockets. Performing small state estimations prior to the full observable system state estimation introduces some error into the observable system solution. However, this error is relatively small compared to erroneous flows and injects experienced with other approaches. The results of this approach give reasonable input data for various optimization techniques.
References [1] A. Bose, K. Clements, Real time modeling of power networks, Proc. IEEE 75 (1987). [2] F.F. Wu, Power system state estimation—a survey, Electr. Power Energy Syst. 12 (1990) 80–97. [3] L. Holten, A. Gjelsvik, S. Aam, F.F. Wu, Comparison of different methods in state estimation, IEEE Trans. Power Syst. 3 (4) (1988) 1798 – 1806. [4] A. Monticelli, F.F. Wu, Network observability: theory, IEEE Trans. Power Appar. Syst. PAS-104 (5) (1985) 1042–1048.
.
Mesut Muslu (M) received his B.S. degree in electrical engineering from the Middle East Technical University, Ankara, Turkey in 1979. He received both his M.S. degree in engineering management and Ph.D. degree in electrical engineering from the University of Missouri-Rolla in 1980 and 1986, respectively. He is currently Professor of electrical engineering at the University of Wisconsin-Platteville. His research interest is in computer applications to power systems, state estimation and expert systems. Dr Muslu is a member of the IEEE Power Engineering society, Tau Beta PI and Sigma Xi. He is a registered professional engineer in the state of Wisconsin. Richard D. Shultz (SM) received his B.S.E.E. and M.S.E.E degrees from the University of Illinois Urbana-Champaign in 1973 and 1976, respectively. He received his Ph.D. in electrical engineering from Iowa State University in 1979. Dr Shultz has been associated with several utilities and universities during his career. He is presently chair of the Electrical Engineering Department at the University of Wisconsin-Platteville. His area of interest is computer application to power systems. Mary Churchill Received her B.S. degree in electrical engineering from the University of WisconsinMadison. For the past 7 years, she has worked at the System Operations Center of Wisconsin Power and Light Company. Her duties include the support and development of advanced applications for Wisconsin Power and Light Company’s energy management system.