Electric Generator Modeling and Automatic Generation Controller

Sponsors	Avista
Team Name	SNWMG
Duration	Spring 2017 - Fall 2017
Advisors	Dr. Herb Hess Dr. Brian Johnson Dr. Yacine Chakhchoukh Dr. Feng Li Mr. Jordan Scott
Students	Suliman Alrashidi Geoffrey Vonbargen Mohanned Almoneef Nathan Bliesner Waleed Almotairi

Avista Utilities is building a microgrid within the downtown area of Spokane, Washington. In the event of a natural or manmade disaster, Avista wants to build a self-sustaining and self-contained small power system using the two hydroelectric generators downtown in Spokane, some renewable energy sources, large batteries, and a control system to make the microgrid work in a stable and reliable fashion.

Project Introduction

Problem Statement

A Microgrid system is needed to keep the power, for important parts of the city, going in the event of a natural or manmade disaster.

This Microgrid will allow the city to have a self sustaining power system using various elements around the city; including two hydro-generation synchronous generators.

The hydro-generation for the city is the main power source for the Microgrid system and is currently incapable of sustaining power for the city in an island state

Deliverables

PowerWorld Models:

• Generator Models
• Governor Models
• Automatic Generator Control

System Models

Introduction

There are many models that are available to use for simulation and modeling of hydroelectric generators. This is complicated further as there is more than just the AC machine involved in generation. In addition to the AC Synchronous machine there is a governor, exciter, and an over excitation limiter. As there are many models for each of these parts we must decide on one model for each part and successfully use it in simulation to get an accurate representation of the generators.

Synchronous Machine

A synchronous machine is a popular choice for generating electric power. They come in several types. First there are the round rotor and the salient variety. As the name implies the round rotor variety has a round rotor while the salient is not round as it has protrusions where the magnetic poles are. The salient type is often used with larger, slower machines. Here in the Northwest these are a very common choice for hydroelectric generators. While a round rotor machine is more often used in high speed generation applications such as steam turbines. As such the motors that we want to model are salient.

There are many models of synchronous machines, several that we looked into are the GENROU, GENSAL, GENTPF and GENTPJ. Each of these models has their own advantages and disadvantages. The GENROU is for modeling a round rotor machine; ours being a salient machine this isn't a good option. GENSAL is an older model for a salient machine, it has the advantage in requiring less computation to simulate. The GENTPF and GENTPJ are rather similar, both may be used to model round rotor or salient rotor synchronous machines. We had the parameters for a GENTPJ from testing Avista had completed on one of the generators so looked into this model in depth.

Block diagram of the GENTPJ model of a Salient Pole Synchronous Machine

The GENTPJ differs from the GENTPF in it's handling of saturation, in this aspect it is more accurate. It also has the most parameters of any of the generators. Luckily these parameters should be the same between models and as such we can use any of the other models as well.

In the end we ended up going with a MatLab-Simulink model that is likely based on the GENSAL model.

Simulink

This MatLab Simulink model is to find a generator model for the two machines. Originally, GENROU, GENSAL, GENTPF, and GENTPJ generator models were considered. GENROU and GENSAL were considered because they were available in Matlab Simulink. GENTPF and GENTPJ were considered because values for one of the generators was available in GENTPJ, and GENTPF is extremely similar to GENTPJ. Because the generators were salient, GENROU was not acceptable to use. When using Matlab Simulink the GENSAL was the model to use. This works because most of the parameters are the same as seen in Figure below. Also, GENTPJ model was not available in MatLab Simulink, so GENSAL model was similar to GENTPJ in MatLab Simulink. However, after going back to work on PowerWorld the GENTPJ model was available to use.

PowerWorld

When moving into power world GENTPJ was an option. So we were able to use the GENTPJ model for the final implementation.

Governor

Introduction

The Governor is a mechanical and or electrical device that uses a feedback control to change the rate of rotation of the machine to get the desired output. This allows for the control of the output frequency of the machine. For the Synchronous Machine water turbine this is done by controlling the flow of water through the turbine and measuring the rate of rotation of the machine.

Block Diagram of an Exciter

Exciter

Main functions of excitation system are to provide variable DC current with short time overload capability, controlling terminal voltage with suitable accuracy, ensure stable operation with network and/ or other machines, contribution to transient stability subsequent to a fault, communicate with the power plant control system and to keep machine within permissible operating range.

Block diagram of an Exciter

First part of the MatLab Simulink modeling was the excitation system. The excitation system model given from tests on the machine in Generator 2 was EXST4B. However, EXST4B was not available in MatLab Simulink, but by looking for the system they are close to each other.

AGC

Introduction

The AGC is a tool in the power systems that checks that the actual MW output of an area is equal to the scheduled MW output of an area [13]. By calculating the Area Control Error (ACE) which is defined in Equation 1

                             ACE = Pactual - Pscheduled                               Equation [1]

The AGC has two levels of control, the master and slave controls. The microgrid master controller provides an interface between the system controller and the individual loads, generators, storage, and power conditioning equipment within the microgrid [14]. Normally, the load varies with the frequencies at play. If there is a general increase in power supply than the actual power needed, the equilibrium is affected and frequency increases. This affects the normal functioning of the grid which may have adverse effects on the entire system. Hence, autonomous generators help regulate system frequency by keeping it in check. This is done using the proportional integral control system in the governor. Whenever the load frequency tends to go high, the AGC sends signals to the cyber component (computers). When this happens, signals are sent to the autonomous generators which pick and act as per the signal received. Simply, the AGC provide a control scheme for the system’s frequency/speed. When the loads increase the AGC adjusts the generators output to restore the nominal value of the frequency. In other words, without an AGC the frequency would decrease when the load increases but the AGC compensates for that by sending a signal to increase to the generators. The AGC is an important tool in the powers systems, because with the automated generation control the frequency can be adjusted without changing the MW output of the system.

PowerWorld

The master control level of the AGC is the Area AGC which controls all the slaves’ controllers in the system. The Figure below shows the interaction between the master and slave controllers in the system.

The interaction between the Area AGC and slave controllers [15]

The master controller has three modes for its operation which are normal operation connected the supply grid, emergency operation connected to the supply grid and an operation in island mode. In Simulation the master controller has the following parameters:

   •	Bus: Bus at which frequency measurement is taken
   •	Bias: Frequency bias [MW/0.1Hz]
   •	Dead band [MW]
   •	Panic High On, Off [Hz]
   •	Panic Low On, Off [Hz]
   •	Update Time: AGC signals are updated at this interval [Sec]

The values for the Area AGC model are chosen accordingly. For the bias parameter a value of 5 MW per 0.1 Hz was chosen after a trial and error testing. The ACE dead band parameter which has the unit of MW needs to be a small value, but not too small because it will cause an unstable frequency with a noise in the simulation. Moreover, using a large value for the ACE dead band will not bring back the frequency to its nominal value. The Panic High On and Panic High Off are given the values of 62 and 61 Hz, respectively. Where the Panic Low On and Panic Low Off are 58 and 59 Hz, respectively. There will be an update every 10 seconds to check the status of the frequency.

The second level of control in the AGC system is the slave controller which is a control scheme implemented in each machine. There are two schemes for the slave controller in PowerWorld which are Set Point and Pulse Rate schemes. The Figure below shows the difference between the two schemes.

The difference between set point and pulse rate schemes [15]

The set point scheme will set the MW reference immediately which means there will be a change by stepping up or down in a specified time. Where the pulse rate will ramp the MW reference up or down with a slope. The scheme was chosen for the AGC system is the pulse rate scheme because its slope will have a smoother transition from one value to another. The pulse rate scheme has the following parameters:

   •	Participation Factor 
   •	Maximum and Minimum Power [MW]
   •	Pulse Rate: Rate at which the MW reference signal changes [Sec]
   •	Pulse Length: Length of time that the pulse up or down occurs [Sec]
   •	Pulse Length Panic [Sec]

The values for the pulse rate scheme are chosen to meet the actual requirements for the system. After calculation, the participation factor parameter is set to be 60\% for the large machine and 40\% for the smaller one. The maximum and minimum powers for each machine are obtained from the rated values of each individual machine. The pulse rate value is set to be 0.15 MW per second, which means that the slope will increase 0.15 MW every second. The pulse length is set to 5 seconds which is the length of time the pulse up or down occurs.

Generator 1

Introduction

Generator 1 was installed in the early 1920s on the river through the city. This generator utilizes a Francis Turbine and outputs up to 10MW. Today it utilizes a solid state exciter and governor controller.

Generator 1 will be one of our greatest modeling challenges. This is due to the lack of known information. In order to model this generator parameters from generators of similar age and style are used and modified to fit the expected values for Generator 1.

PowerWorld

For Generator 1 the generator parameters were taken from tests done on a nearby generator that is similar in age, so it’s per unit values should be very similar. The Governor model was also adapted from these other similar age generators, with the addition of the correct water time constant, calculated from the dimensions of the inlet pipes into the turbine. For the Exciter the same parameters were used as on Generator two.

Generator 2

Introduction

Generator 2's Dam was built in 1890 and at it's peak consisted of five generators. Eventually reconstruction of Generator 2 dam started in 1974 and was finished in 1992. This reconstruction removed the 5 generators from the 1900-era and replaced them with 1 generator utilizing a Kaplan turbine. In the process the generation was moved underground.

Simulink

The first step of the model process for this project is to model the generators in Matlab Simulink. Tests have been done for generator 2 giving us usable parameters. The values from the GENTPJ model were given and can be used with Simulink models from the Sim Power library. The values for the exciter were also in the testing report for the machine. With this information the Simulink model of the generator could be built using a generic exciter model that should be close to the actual model. Below is the final model for generator 2 in Matlab Simulink with per unit values.

Matlab Simulink Model of Generator 2

This Simulink model uses a fault system on the line to trigger a transient response. With this response in the system we can verify that this model is correct for Generator 2. The three main blocks of the diagram are the Govern the Exciter and the Synchronous Machine itself. With these models generator 2 model is complete.

Output Voltage from Generator.

Armature Current from Generator

Rate of Rotation of Generator Rotor

The figures above show the current results of the forced fault in the system and the generator models transient recover from this fault. From the voltage it clearly can be seen that the fault is doing its job forcing the voltage to zero. This forces the rotor to slow and the current to spike.

PowerWorld

For Generator 2 the generator parameters were taken from tests done on this generator. The Governor model was adapted from another generator with the same “Kaplan” turbine, with the addition of the correct water time constant, calculated from the dimensions of the inlet pipes into the turbine. For the Exciter model the parameters were obtained from the same test that was done on this generator.

Results

This PowerWorld model was ran under several conditions to show its effectiveness. First it was ran starting with a load of 5.6MW then increasing the load in 0.5-3MW steps.

Below is shown the results with the AGC:

Frequency with increasing load and AGC.

Generator power output with increasing load and AGC. Note how the generators switch power when one generator exceeded its rated output power.

AGC output to governors with increasing load. Note how the reference changes as one generator exceeded it's rated output to bring the generator back to safe operation

Here are the results without the AGC:

Frequency with increasing load and NO AGC

Generator power output with increasing load and NO AGC. Note that the output of generator 1 exceeds its rated value.

The next and final test was with a decreasing load on the system.

First with the AGC:

Frequency with decreasing load and AGC.

Generator power output with decreasing load and AGC

AGC output to governors with decreasing load

Then without the AGC:

Frequency with decreasing load and NO AGC

Generator power output with decreasing load and NO AGC

The final test was with a randomly varying load.

First with the AGC:

Frequency with randomly changing and AGC.

Generator power output with randomly changing and AGC. Note the generators switching power outputs when one's rated power is exceeded.

AGC output to governors with randomly changing load

Then without the AGC:

Frequency with randomly changing and NO AGC

Generator power output with randomly changing and NO AGC. Note that when one generator exceeds it's rated values it does not return to a safe operating condition.

Overall there was improvement on the system with the added AGC. The AGC almost entirely eliminates any offset from the droop of the governor. It is very easy to see in most of these by comparing the difference between the starting frequency and the ending frequency. The one that it's not is in the random load test, this is due to the load being very close at the end as it is at the beginning. Even in the random load test it can be seen that the AGC still gives us a significant improvement. Though the AGC may not have actually been needed for frequency control. From IEEE 1547 [21] we can see that the frequency should be between 57Hz and 60.5Hz, even without the AGC the system meets these goals, at least for steady state. But with the AGC the the largest steady state deviation was approximately 0.02Hz, compared to without the AGC a difference of up to 0.26Hz. This would be even larger with a more extreme change in load. But either way the AGC definitely improves the frequency deviation. Another advantage we can see that the AGC gives us is that it keeps the generators running within their rated power.

References

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[2] International Conference Electric Power Quality and Supply Reliability, Tallinna Tehnikaulikool., IEEE Power & Energy Society, & Institute of Electrical and Electronics Engineers. PQ2016: The 10th International Conference: 2016 Electric Power Quality and Supply Reliability (PQ): Proceedings, August 29-31, 2016, Tallinn, Estonia, 2016.

[3] L. Wang, Modeling and control of sustainable power systems: Towards smarter and greener electric grids. Berlin: Springer, 2012.

[4] R. S. Vedam, and M. Sarma,Power quality: VAR compensation in power systems. Boca Raton: CRC Press, 2009.

[5] Power Quality Conference, Danishgah-i Sanati-i Amir Kabir., Iran., & Institute of Electrical and Electronics Engineers. (2010). 2010 First Power Quality Conference: PQC 2010, Tehran, Iran, Sept. 14th and 15th, 2010. Piscataway, N.J.: IEEE

[6] F. Saccomanno,Electric Power Systems: Analysis and Control. Hoboken: Wiley-IEEE Press, 2005.

[7] J. Northcote-Green, and R. Wilson,Control, and automation of electric power distribution systems. Boca Raton: CRC Press, 2007.

[8] S. Chattopadhyay, M. Mitra, and S. Sengupta,Electric power quality. Dordrecht: Springer, 2011.

[9] International Conference Electric Power Quality and Supply Reliability, & IEEE Power & Energy Society,8th International Conference 2012 Electric Power Quality and Supply Reliability: June 11-13, 2012 Tartu, Estonia: conference proceedings. Piscataway: IEEE, 2012.

[10] Y. Pei, G. Jiang, X. Yang, z. Wang, Auto-master-slave control technique of parallel inverters in distributed AC power systems and UPS. Power Electronics Specialists Conference, 2004. PESC 04. 2004 IEEE 35th Annual.

[11] Penkey, P. (2016). Critical Load Serving Capability by Microgrid Operation, ProQuest Dissertations and Theses.

[12] (2016).The Recommended Synchronous Generator Model: GENTPJ (Tech. No. 1). Salt Lake, Utah.

[13] Area Control. [Online]. Available: https://www.powerworld.com/ WebHelp/Content/MainDocumentation HTML/Area Control.htm. [Accessed: 21-Sep-2017].

[14] Master Controller Requirements Specification for Perfect Power Systems. Galvin Electricity Initiative, Palo Alto, 16-Feb-2007.

[15] J. Weber, Incorporation of Automatic Generation Control in Transient Stability Simulation. PowerWorld, Champaign, 20-Nov-2014.

[16] Kundur, P. (1994). Power system stability and control. Estados Unidos de America: McGraw Hill, pp.377-400.

[17] Koritav, V. Guzowski, L. (2013) Review of Existing Hydroelectric Turbine-Governor Simulation Models. U.S. Department of Energy - Wind and Water Power Technologies Office.

[18] Wecc.biz. (2017). Approved Dynamic Model Library. [online] Available at: https://www.wecc.biz/Reliability/Approved/ 20Dynamic20Models20November202016.pdf

[19] Governor HYG3, PowerWorld. [Online]. Available: https: //www.powerworld.com/WebHelp/Content/TransientModels HTML/ Governor20HYG3.htm. [Accessed: 19-Nov-2017].

[20] M. R. G. Zoby and J. I. Yanagihara, Analysis of the primary control system of a hydropower plant in isolated model, J. of the Braz. Soc. of Mech. Sci. & Eng., Vol. XXXI, no. 1, pp. 5-7, Mar. 2009

[21] Standards Coordinating Committee 21. (2008). IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems. IEEE.

Document Archive

• Group Minutes

Team Information

		Biography	Discipline
Suliman Alrashidi		Suliman Alrashidi is an Electrical Engineering student. His emphasis is in Electromagnetic and power systems, so he is interested in the combination of EM and Power Systems. During his free time he enjoys reading and drinking a hot coffee.	Electrical Engineering.
Mohanned Almoneef		Mohanned Almoneef is a senior in electrical engineering from Saudi Arabia,His emphasis has been in power systems and microlectronics. When not studying, Mohanned enjoys Playing and watching sports a lot, and traveling around the world.	Electrical Engineering
Nathan Bliesner		Nathan Bliesner is an Electrical Engineering student with interest in Power and Control Systems. When not focused on academics he likes to spend time with his family.	Electrical Engineering
Waleed Almotairi		Waleed Almotairi is interested in the Power Field. His career goals are to work in a Power Company and to obtain a Master's Degree in Engineering Project Management.	Electrical Engineering
Geoffrey VonBargen		Geoffrey started at UIdaho in 2015 with a transfer from Lewis Clark State College in Lewiston Id. He is interested in AC and DC machines as well as power systems and hopes to work with them in the future. In the next year he hopes to use experiences from internship and schooling to decide on whether to pursue a Master’s degree or enter the workforce.	Electrical Engineering