IEEE Transactions on Power Systems, Vol. 12, No. 2, May 1997

Genco Contracts

533

- Area Dlsco - Controller Contracts

AGC SIMULATOR FOR PRICE-BASED OPERATION- PART 11: CASE STUDY RESULTS

Genco Con tracts

Jayant Kumar Kah-Hoe Ng Gerald Shebli Student Member Student member Senior Member

Department of Electrical and Computer Engineering Iowa State University

Ames, IA 50011

- Dlsco - Controller Contracts

A b s t r a c t : This is p a r t 11 of a two p a p e r set dealing wi th au tomat ic genera t ion con t ro l ( A G C ) problem in a deregula ted industry. T h r o u g h the passage of new public uti l i ty regula tory policies, the Federal Energy Regulatory Commission (FERC) encourages an open marke t system for pr ice based operation. Recently, the FERC has issued a notice of proposed ru lemaking [I] seeking comments on various anc i l la ry services. One of these anc i l l a ry services is load following. T h e companion p a p e r ( P a r t I) [Z] describes the s imula t ion models a n d s o f t w a r e i m p l e m e n t a t i o n of l o a d f o l l o w i n g contracts in the new environment. The p a r t I also developed a framework for new marke t s t ruc tu re to understand AGC implementat ion in the price-based operation. This pape r reviews the case s tud ies t o show the modifications r equ i r ed of convent iona l AGC software for the new environment. Three sets of case study results a r e reported. T h e f i rs t a n d second case s tud ie s i l l u s t r a t e how to s imula t e b i l a t e r a l a n d p o o l c o b a s e d t r a n s a c t i o n s respectively in the new marke t place. T h e t h i r d case s tudy considers various (bi la teral a n d poolco based) c o n t r a c t s existing s imul t aneous ly in the system. The simulation results i l lustrate t ha t the tie-line flows due to increased number of various contracts will tend to cancel among each other.

K e y w o r d s : Brokerage system, Automatic generation control, Load following, Price-based operation.

I. INTRODUCTION

Through the passage of new public utility regulatory policies. the Federal Energy Regulatory Commission (FERC) encourages an open market system. The basic premise of the regulatory policies is to create a competitive environment where generation and transmission services are bought and sold under demand and supply market conditions. The open market system will consist of generation companies (gencos), distribution companies (discosj. transmission companies (transcos j and an independent contract administrator (ICA). The interconnection between these proups is shown in figure 1. The ICX is an independent and disassociated agent for market participants. A thorough discussion of price-based operation in an open marker system is presented in reference [ 3 ] .

96 S M 373-1 PWRS A paper recommended and approved by the IEEE Power Engineering Education Committee of t he IEEE Power Engineering Society for presentation at the 1996 IEEElPES Summer Meeting, July 28 - August 1, 1996, in Denver, Colorado. Manuscript submitted January 2, 1996; made available for printing July 17, 1996.

I 1 I I C A

(Broker)

I I I I"--I Figure 1

7 1 . New business environment

Part I of this two-paper set [ 2 ] reports a framework for new market structure to understand AGC implementation in price-based operation. It is assumed that all transactions are coordinated and implemented by the ICA. The ICA verifies that the system can remain in operation with all contracts in place. The market consists of three types of transactions - bilateral contract, poolco based contract, and area regulation contracts. The need for area regulation contracts arises because of inconsequential frequency oscillations due to unscheduled generation and load changes and inconsistent frequency bias existing in the system [4.5,6]. All governors respond to this frequency change in the system instantaneously, whether or not they are on AGC. This governor response is defined as area regulation contracts.

A schematic of the proposed AGC simulator in reference [2] is shown in figure 2. Implementation of the AGC schemes consists of a central location where information pertaining to the system. such as unit megawatt output, megawatt flow over tie lines, and system frequency are monitored to compute the control error.

Power System

I 1 I J

T 1 1

J

Figure 3. Schematic of 3 3-area AGC slmuiator

0885-8950/97/$10.00 0 1996 IEEE

534

This paper reviews the case studies to show the modifications required of conventional AGC software for the new environment. Three sets of case study results are reported. The first and second case studies illustrate how to sirnulate bilateral and poolco based transactions respectively in the new marketplace. The third case study considers various (bilateral and poolco based) contracts existing simultaneously in the system. The simulation results illustrate that the tie-line flows due to increased number of various contracts will tend to cancel among each other.

The details of contract implementation can be used to teach students the issues involved in load following in a price-based operation. More case studies can be presented to encourage thinking about required technical regulations to ensure secure system operation and a fair marketplace. A number of interesting discussions can be motivated by asking questions such as those described below:

(a) What are the possible ways in which people can breach the contract?

(b) How should one detect if somebody is violating the contract?

(c) What kind of penalty should be designed to prevent such contract violations?

(d) What should the ICA do to minimize the requirement of area regulation contracts?

(e) What kind of modifications should the ICA do to reduce the tie-line oscillations? (0 How should one use the enhanced AGC algorithms [6,7] to

reduce the operational overheads (such as filtering, processing RACE [2]) to meet the increased demand of transactions?

(g) What modifications should one need to make in control steps for an efficient implementation of contracts?

(h) What trends should be monitored for technical scrutiny and what kind of correction logic should be applied?

This paper proceeds as follows. Section I1 describes the test system. Section I11 describes the case study for bilateral and poolco based transactions. The simulation results of genco outputs, tie line deviations, and area control errors are reported for each of the case studies. Section IV concludes the paper.

II. THETESTSYSTEM

We have developed an AGC simulator for a 3 area test system using state transition matrix approach [8]. The test system has been developed by using the network topology of 30 bus New England test system as shown in figure 3.

co 5 Genco 4 Gent I I

Figure 3. A 3-area test system for AGC simulation

Table 1. Control areas in 30 bus New England System

1 Bus-No. 1 Owner Control I

Area 3

I 19.23 I Genco 6 I The correspondence of the test system with 30-bus new

England test system is described in table 1. Note that genco 6 has one unit in area 1 and two units in area 3 and disco 3 has load buses in two areas, namely, area 1 and 2. Other gencos and discos do not cross control area boundaries. The data for the plant models of various gencos have been taken from reference [9]. Recognizing the complexities involved, we emphasize clarity over exhaustiveness. Our main goal is to describe the implementation of AGC for various types of transactions in the new marketplace.

III. SIMULATION RESULTS

We have simulated a bilateral contract, a poolco based contract, and a combination of both. Unless otherwise stated, all the gencos participate in area regulation. Load changes of all discos have been modeled as an exponential curve given by equation (1). The other models are easily added.

P L = a (I-e-Pt) (1) where a and /? are constants.

In this work, the value of a and /? for all the discos are chosen as 0.1 and 20 respectively. However, the parameters a and can be assigned any real or imaginary value. Hence, the proposed exponential model can be used to construct any other load model, such as sine. cosine, step function, etc. This makes the AGC simulator capable of simulating events where the system load and frequency may not be constant.

In all the simulations, ACE participation factors were kept at the same values as shown in table 2. The contract participation factors for generating units were computed with respect to specific contracts described later in this paper.

Table 2. ACE participation factor

A . Transaction 1 (A single Bilateral transaction)

Disco 1 (area 1) contracts with genco 2 (area 2). The contract is simulated and simulation results of genco outputs are shown in figures 4 through 6. Both the units of genco 2 participate in the contract by equal share (figure 4). Note that all gencos other than genco 2 have transitory response that dies down finally.

a.

Oumut of Pencos

"."-I

a -0.05

0 5 10 15 20 Genco 2, Unit 1

0.1 1 I

a nY I "

0 5 10 15 20 Genco 2, Unit 2

0.1 + 6 a 0.05 1 1

" 0 5 10 15 20

0.02 r 1

Genco 3

-0.02 ' 1 0 5 10 15 20

Genco 4 0.02 r 1

-0.02 ' I

> 1

0 5 10 15 20 Genco 5

0.02 1

-0.02 ' J 0 5 10 15 20

535

Genco 6, unit 1 0.02 I 1

>

-0.02 0 5 10 15 20

Genco 6, Unit 3 0.05 r

a -0.05

0 5 10 15 20 Figure 4. Genco response

Simulation results of the changes in tie-line flows are shown in figure 5. Note that there is a steady state change in the tie-line flow from area 2 to 1 only (fig. 5) as desired. The ACE in each of the areas goes to zero at steady state (fig. 6).

Tie line flows and Area control error

Tie Flow Dev from Area 2 to Area 1

0 5 10 15 20 Tie Flow Dev from Area 3 to Area 2

0.05 I 1

-0.05 ' 1 0 5 10 15 20

Tie Flow Dev from Area 3 to Area 1 0.05

-0.05 ' 0 5 10 15 20

t/sec Figure 5. Tie line flows

ACE 111 Area 1

.J. A

0 5 10 15 20 ACE in Area 2

0 5 10 15 20

ACE in Area 3

< 0 J 10 15 t/sec

Figure 6. Area control errors

536

> & c

B. Transaction 2 (Pooico based transaction)

0 0 - -

Disco 3 (area 1 and 2), genco 1 (area l), genco 2 (area 2), and genco 3 (area 3) submit bids to the ICA. As a result of bid matching, genco 1, 2 and 3 gets 60%, 20% and 20% of the total load following contracts respectively. Both the units of genco 1 participate with equal share. Genco 2 has only unit 1 on AGC. The load of disco 3 in area 1 and 2 are assumed to be the same. The results of genco outputs are shown in figure 7.

z 3 -

Output of cencos

0;

Genco 1, Unit 1

. . . . ' 0 5 10 15 20

Genco 1, Unit 2

" 0 5 10 15 20

Genco 6. Unit 3

-0.02 I 0 5 10 15 20

Genco 2, Unit 1 0.05 I 1

2 a I&

Genco 6, unit 1

0 5 10 15 20

x io-' Genco 6, unit 2 5 ,

-5 ' I 0 5 10 15 20

t/sec Figure 7. Genco response

The changes in the tie-line flows are shown in figures 8. As a result of load distribution, we observe changes in the tie-line flow from area 1 to 2, and area 3 to 2 respectively. The ACE of each area finally settles down to zero (fig. 9).

Tie line flows and Area control error

Tie Flow Dev from Area 1 to k e a 2

0 5 10 15 20 Tie Flow Dev from Area 3 to Area 2

& a 0.02 O'" 0

0 5 10 15 20

0.01 I , Tie Flow Dev from Area 3 to Area 1

-0.01 ' 0 5 10 15 20

tlsec Figure 8. Tie line flows

ACE in Area 1 0.05 1

0 5 10 15 20 ACE in Area 2

0 02

a -0.02

0 5 10 15 20 ACE In Area 3

0 02

0 5 10 15 20 tlsec

Figure 9. Area control errors

537

Trans. Disco Type Bilateral Disco 5 Bilateral Disco 2 Bilateral Disco 4 Poolco Disco 3

Genco(cpf)

Genco 4 Genco 2 Genco 6 Genco 1(60%) Genco 2(20%)

Poolco

I I I Genco 6(35%) 1

Genco 3(20%) Disco 1 Genco 3(50%) Disco 3 G e n a 5(15%)

Output of gencos

Genco 1, Unit 1

. . . . . . . . . . I . . . . . . . . . . .

" 0 5 10 15 20

Genco 1, Unit 2 0.1 I . I

. .: . . . . . . . . . . .f . . . . . . . . . . -

0 5 10 15 20

Genco 6, Unit 3 0.2 1 I

d & 0.1 tn/.y-- i I

0 5 10 15 20

Genco 2, Unit 1

O r

0 5 10 15 20 Genco 2, Unit 2

0.1 I 1

u

0 5 10 15 20 Genco 3

0.2 1 1

Genco 4 0.2 1

>

0 5 10 15 20 Genco 5

".*

a -0.1

0 5 10 15 20

Genco 6, unit 1 0.1 I

a

0 5 10 15 20

Genco 6, unit 2 0.2 I I

0 5 10 15 20 tfsec

Figure 10. Genco response

The changes in the tie-line flows between different areas are shown in figure 11. Note that the tie-line flows due to various contracts tend to cancel each other. The ACE of all the areas settle to zero steady state values as shown in figure 12.

Tie line flows and Area control error

Tie Flow Dev from Area 1 to Area 2

-0.2 I I 0 5 10 15 20

Tie Flow Dev from Area 3 to Area 2

a 0 8

-0.1 0 5 10 15 20

Tie Flow Dev from Area 3 to Area 1 0.1 1 i

d a 0- I -0.1 ' I

0 5 10 15 20 t/sec

Figure 11. Tie line flows

W

0 5 10 15 20

538

> d 0 6 . . . . . . . L

ACE in Area 1 0.2 1 1

0 5 10 15 20

-0.2 ‘ I

0 5 10 15 20 t/sec

Figure 12. Tie line flows

VI CONCLUSION

We have proposed a new framework for analyzing load following contracts in price based operation. The modified AGC scheme includes the contract data and measurements, which are continuous, regular and quiescent. Thus, they greatly improve control signals to unit dispatch and controllers. The proposed simulator is generic enough to simulate various possible types of contracts (bilateral, poolco, multilateral, etc.). We have identified the need of area regulation contract in the new market place. In real time operation, a contract violation is reflected in higher requirement of area regulation. This should be interpreted as higher (penalty) costs. The proposed scheme satisfies the NERC performance criteria. The NERC performance criteria should be expanded to include all of the future contract types.

The new framework requires establishment of standards for the electronic communication of contract data as well as measurements among the ICA and the market players. Increased magnitude of computerized accounting needed by the explosion in :he number of transactions is an another technical issue to be solved. In general, a variety of technical scrutiny will be needed to ensure secure system operation and a fair market place.

The tool described should enable the analysis of proposed rules for the new environment. The strength of the approach is the segregation of the competitive market tools from the control emulation tool. Three detailed examples are included in this paper. Part I paper shows an interesting case to determine if any of the connacts are violated.

VII. REEERENCZS 1. E E E Power Engineering Review. “NERC NEWS”. voi. 15,

2.1. Kumar. K.X. Ng. and G.B. Sheble’. “AGC Simulator For PTIW Based Operation Part 11: Case Study Resuits”, to be presented at t h e IEEE PES summer meerinp, Denver. Colorado. L t’9 6 .

3 . G.B. Shebie’, .‘Price Based Operation In An Auction Market Structure”. presented at the IEEE PES winrer /neering, 96 WM i9L-7 PWRS. Baltimore. Maryland, 1996.

no.6. pp. 20-21. 1995.

4. N. Jaleeli, L. VanSlyck, D.Ewart, L.Fink and A. Hoffman, “Understanding Automatic Generation Control”. IEEE trans. on Power Systems. vol. 7 , pp. 1106-1122, 1992.

5. L. VanSlyck. N.Jaleeli. and W.R. Kelley, “Implications O f Frequency Bias settings On Interconnected System Operation And Inadvertent Energy Accounting“, IEEE Trunsuciions on Power Systems, pp. 712-723. 1989.

6. R. P. Schulte. “An Automatic Generation Control Modification For Present Demands On Interconnected Power Systems, presented at IEEE PES Summer Meeting, 95 SM 523-1 PWRS, 1995.

“Automatic Generation Control With A Fuzzy Logic Controller”, submitted to the IEEE PES summer meeting, Denver, Colorado, 1996.

8. Chen, C. “Linear System Theory And Design”. New York: Holt Renihart and Winsten Inc., 1984.

9. IEEE Committee Report, “Dynamic Models For Steam And Hydro Turbines In Power System Studies”, IEEE Trans. on PAS, vol. PAS-92, November/December 1973, pp. 1904-1915.

7. CW. Richter, and G.B. Sheble’,

Jayant Kumar received his B.E. i n Electrical and Electronics Engineering from Birla Institute of Technology, Ranchi, (India) and MSEE from Iowa State University. He is currently working towards his Ph.D. degree in Iowa State Un iv ersi ty .

Kah Hoe Ng received his BSEE from Iowa State University. He is currently working towards a MS degree.

Gerald B . Sheble (M 71, SM 85 ) is a Professor of Electricai Engineering, Iowa State University, Ames. Iowa. Dr. Sheble’ received his B.S. and M.S. degrees in Electrical Engineering from Purdue University and his Ph.D. in Electrical Engineering from Virginia Tech. His industrial experience includes over fifteen years with a public utility, with a research and development firm, with a computer vendor and with a consulting firm. His research interests include power system optimization, scheduling and control.