Abstract-- In recent years, growth of load demand increases day by day, but this growth does not happen the same in equipments of power systems and therefore operators have to use maximum available capacity of systems to satisfy load demands. These actions make power systems so unreliable. One of best ways to improve reliability of systems, is using FACTS devices.

This paper proposes an optimization model to be use in composite power system reliability evaluation method when employing a Static Synchronous Compensator (STATCOM). Some probabilistic load point indices and system indices have been calculated in this approach. At last some comparisons has been done between the results achieved for STATCOM and UPFC when used in grid and original systems. The effectiveness of the proposed method is demonstrated by applying to the 24 bus - IEEE Reliability Test System (IEEE-RTS).

Index Terms-- Reliability, Static Synchronous Compensator,

Flexible AC Transmission Systems, Load Shedding, System indices, Load Point indices.

1. INTRODUCTION

A major requirement in the application of FACTS devices in power systems is to develop techniques which enable system planners to manage the uncertainty associated with these devices with great confidence [1].

The ability to control power flow without generation rescheduling or topology changes in an electric power system is the most useful benefit of FACTS devices. A fundamental requirement in power system planning is the determination of how much generating capacity is required to meet the system requirements at an acceptable level of reliability and also that’s just customer’s respect. This is a brief definition of reliability from one view point [2]. There is relatively very little literature that considers a FACTS device as a component in composite system reliability evaluation. Reliability assessment of a power system is performed in the two distinct domains of adequacy and security [3]. System adequacy relates to the existence of sufficient generation,

H. R. Bay is M.S student of Power Electrical Engineering, Iran University

of Science and Technology, Iran (e-mail: hamidrezabay@gmail.com). A. Kazemi is with Dept. of Electrical Engineering, Iran University of

Science and Technology, Iran (e-mail: kazemi@iust.ac.ir).

transmission and distribution facilities within the system to satisfy the customer load demand. System security, on the other hand, relates to the ability of the system to respond to disturbances arising within the system [3]. The present study is concerned with adequacy assessment of composite generation.

A wide range of reliability indices are used in bulk power system planning. There is a strong interest in the calculation of frequency and duration indices in composite power systems [4].

In reliability evaluation of generating units and transmission lines together (known by a composite power system) computation of accurate estimates of actual frequency, duration and frequency related indices is a difficult problem as it involves recognition of all the load curtailment states that can be reached from a failure state in one transition.

In contingency enumeration approach, the basic procedure for a composite power system adequacy evaluation can be generally classified into the three steps of contingency enumeration, analysis of each contingency and then calculate adequacy indices. In contingency enumeration, all possible outage contingencies are defined and selected for analysis one at a time. Load flow techniques are normally used to solve the power network for each system contingency and to determine the degree of difficulty at each load point and on the overall system. Adequacy indices are obtained after all the defined contingencies have been analyzed [5].

Two sets of indices, load point indices and system indices are determined for the system load buses and the overall system, respectively. These indices give an assessment of indicating the adequacy at individual buses and overall adequacy.

In this approach Static Synchronous Compensator (STATCOM) has been used to verify if this type of FACTS improves reliability indices.

STATCOM is a prevailing static var generator, whose output is varied so as to maintain or control specific parameters of the electric power system [6].

Also this paper presents a network reliability equivalent technique for evaluating the reliability of an entire power system. The procedure is illustrated by implementing in IEEE-RTS [7].

Reliability Evaluation of Composite Electric Power Systems Incorporating STATCOM & UPFC

Hamid. R. Bay, and Ahad. Kazemi

978-1-4244-2487-0/09/$25.00 ©2009 IEEE

2. STATIC SYNCHRONOUS COMPENSATOR Convertible Static Compensators (CSC) is a kind of FACTS devices that can function as shunt and/or series compensating devices providing various control modes as a STATCOM, SSSC, UPFC or IPFC. The CSC, through appropriate arrangement of disconnect switches and circuit-switchers, can have 11 configurations [8]. These devices are in two types: Voltage Source Converter (VSC) and Current Source Converter (CSC). Each of these has its individual merits that has described extensively in Refs [8,9].

The STATCOM based VSC has been used in this approach to evaluate reliability indices. Since the first 20 MVar STATCOM was developed and putted into service at Japanese power gird in 1980, application of STATCOM devices was increasing year by year, but effect of this type of FACTS devices on reliability of power systems was not considered so much and properly [6].

3. METHODOLOGY The first step in reliability evaluation of a composite system is modeling all equipments used in generating units and transmission facilities.

The model of each component is based on the state space approach and the concept of Markov processes. The analytical techniques represent the system by a mathematical model and evaluate the needed reliability indices from this model using mathematical solutions.

Each generating unit and each transmission line are represented by two state model. After modeling of generation and transmission facilities, the second step is enumeration of all possible system contingencies; and the third one is determination of load curtailment under each contingency and the calculation of the reliability indices at each load point is the last step in general reliability evaluation procedure. The first and third steps have been extended in order to incorporate FACTS devices in the overall evaluation [10]. 3.1 Reliability Modeling of Facts Devices:

The STATCOM based VSC is made up of three phase cascade multilevel inverters, coupling reactors, high voltage switchboard, step-up transformer, control units, monitor units, protecting units, cooling water system, center console and remote console, etc [6].

Each of these equipments is represented by a two-state Markov’s model. Up state when each component is in service mode and Down state when it is out of service. We know that if each of these components fails, STATCOM will go out of service altogether. Therefore we can adjust our multistate model resulted from gathering all models of equipments into a two state one. The Up state is when all equipments are in service and STATCOM capable of providing load flow control and maximum transmission capacity. In the Down state each component is out of service and therefore STATCOM is bypassed by a fully reliable circuit breaker and the system operates as a normal transmission line (derated mode in Fig 1).

The probability and frequency values associated with each state can be obtained using the following equations: ⁄ ⁄ ⁄

µ

µ Where,

µ . µ µ . µ .

, µ , and µ are the failure and repair rates of the transmission line and STATCOM respectively [10]. These equations has obtained by F&D method.

Fig 1. Three-State model of the transmission element with FACTS devices

The calculation of load curtailment resulting from network contingencies is a key factor in composite system reliability evaluation.

In this paper AC load flow based on Newton Raphson method has been applied for each contingency.

The results of load flow achieves the weak points of system as over load in some transmission lines or lack of power generated by units. Load shedding is the last option we should do to prevent the other major problems in the system. Before load shedding we can do some remedial and corrective actions to adjust some of problems occurred. If some problems did not change or reduce properly, load shedding is applied to solve problem. 3.2. Mathematical Mode:

The most important target is to minimize the load curtailment of customers. For this purpose the calculation and minimization of the expected cost of customer interruptions (ECOST), or expected customer damage cost, at a specified system service area or at a load bus will be necessary.

Generally, an optimization problem may be formulated as below: min Here assumed ECOST function.

For calculating this function Genetic Algorithm approach has been developed, therefore this general function can be used:

min where x is the vector of variables; Z(x) is the objective

function; g(x) and w(x) are equality and inequality constraints respectively and consist of operational constraint like magnitude and angel of voltages and power flows in lines and active and reactive powers produced by plants that should be in their allowable determined limitations. and are also penalty coefficients and are huge numbers to prevent encountering undesirable answers.

4. RELIABILITY INDICES All load point indices and system indices that used in this

approach have calculated by equations as below: 4.1. Load Point Indices: Probability of Failure (POF) = ∑ . Expected Load Curtailed (ELC)=∑ . Expected Energy Not Supply(EENS)= ∑ . . Expected Duration of Load Curtailment (EDLC)= ∑ . j: an outage condition in the network, : the state probability of the outage event j,

: frequency of occurrence of the outage event j, : probability of load curtailment at bus k, : load curtailment at bus k during outage, : duration in hours of load curtailment at bus k, during outage event j [11]. 4.2. System Indices: 4.2.1 . System Basic Indices: EENS= ∑ p . L . 8760 MWh/year ECOST= ∑ p . L . C d . λ µ k$/year Bulk Power Interruption Index (BPII) = ∑ ∑ F L⁄ Bulk Power Supply Average MW curtailment/disturbance = ∑ ∑ Lkj . Fjj k ∑ Fjj⁄ Bulk Power Energy Curtailment Index (Severity Index or S.M) = ∑ ∑ 60 . . ⁄ Modified Bulk Power Energy Curtailment Index= MBPECI ∑ ∑ . . 8760 ⁄ where Ls is the total system load [11], C d is calculable by CCDF method [12]. 4.2.2 . System Average Indices: Average Number of Curtailments/Load Point= ∑ ∑ . ⁄ ⁄

Average Energy Curtailed/Load Point= ∑ . . ⁄ / Average Duration of Load Curtailed/Load Point= ∑ . ⁄ /

5. RELIABILITY ASSESSMENT STUDY RESULTS Reliability studies were conducted using the IEEE-RTS (Fig 2), which has 24 buses, 38 lines / transformers and 32 generating units. All data about lines and generators are given in [7]. Transfer rates of equipments in STATCOM is also represented in appendix 1.

A number of studies have been conducted to evaluate the impact of FACTS devices on the composite system reliability. Therefore we assumed that STATCOM device provides the ability to double the related transmission line load carrying capability.

By F&D1 method that used for adjust general state model of STATCOM, availability of this device is determined 0.997, with the failure rate and repair time of 0.44 f/yr and 60 hours respectively.

Fig. 2. single line diagram of IEEE-RTS

In this study, the transmission line 25 in the IEEE-RTS was

replaced by STATCOM transmission unit and the transmission line 26 is eliminated of the grid. Tables 1-4 show the load point and system indices for the original and modified systems.

Table 1. System Average indices for IEEE-RTS

Indices Without STATCOM

With STATCOM

ANC/L 91.23996675 89.34777 ALC/L (MW/ Yr) 15433.84826 15246.69 AEC/L (MWh/Yr) 234977.1746 234566.8 ADLC/L (h/Yr) 4629.476371 4621.34

Table 2. System indices for IEEE-RTS

With STATCOM

Without STATCOM Indices

415746.6 416786.2 ECOST (K$/Year)

234566.8 234977.2 EENS(MWh/Year) 90.94514 92.06155 BPII (MW/MW-Yr)

170.6443 169.1567 BPSAC/D (MW/Disturbance)

83950.21 84097.09 S.M (MW-min/MW-yr)

0.159723 0.16000208 MBPECI

1 Frequency and Duration Method [11]

Table 3. Maximum Load Point indices

Indices Without STATCOM

With STATCOM

MDLC MEC MLC

24.386343 9819.923 620.29014

24.326 9802.054 588.6686

This is not to say that FACTS devices may have no significant benefit on composite system reliability. In this case, it is due to the fact that the IEEE-RTS have strong transmission systems compared with generation capacity and load demand. Further improvement in the transmission system does not provide much benefit in terms of the overall system reliability indices.

Another study was conducted involving system load growth. In this case generation capacity is assumed constant

and peak load demand grows 2.5 % each year. Load demands were increased in proportion to their base values. By assuming constant generation capacity and load growth, we are sure that reliability indices will increase but we want to know if the STATCOM improves indices.

In this case we select some less important buses that achieved by CCDF method to show changing reliability indices. This is a fact that quota of these buses for load curtailment is more than the others. The probability of having difficulties in transferring the required energy from the generating stations to the load points increases as the demand increases. Tables 5-7 show the variations in the system and load point indices. The reliability indices increase, as the load demand increases, and the transmission system becomes more heavily utilized.

Also we do not see any improvement on the values except ECOST index, table 7 shows that this index after fourth year will increase immediately in original system but in modified one with STATCOM this index adjusts properly.

In the last study, we will model UPFC with the same way as modeling STATCOM. The unified power flow controller (UPFC) is the most versatile FACTS device that has emerged for the control and optimization of power flow in electrical power transmission systems [13]. UPFC is made of a STATCOM and a SSSC. Therefore model of UPFC is the same as STATCOM with considering that we should insert SSSC’s equipments that are almost as the same as STATCOM and dc link between SSSC and STATCOM in our model. Tables 8 & 9 show that there is not any tangible difference between results of UPFC & STATCOM, even a little better performance can be seen by STATCOM. There are some reasons for it. First we can mention that number of equipments of UPFC is more than STATCOM, therefore transfer rates for UPFC is a little bigger. Second and main reason for this phenomena relates to where UPFC has been used, because the line 25 is between two major plants of system and therefore series inverter of UPFC in act can’t perform its function. So not substantial difference can be seen in performance of UPFC and STATCOM.

Tables 1-4 show that replacement of a particular transmission line 25 by STATCOM and elimination of the

parallel line 26, has almost no effect on the indices, and system reliability is only slightly improved after adding the

STATCOM to the IEEE-RTS.

Table 4. Load Point indices for IEEE-RTS EENS (MWh) ELC (MW)

Bus With STATCOM Without STATCOM

With STATCOM

Without STATCOM

578.98 590.74 34.49 37.88 1 97381.4 96625.5 6578.31 6610.92 2 671.98 687.6 39.70 43.6 3

2285.08 2204.69 139.39 168.351 4 554.564 571.98 32.85 36.204 5 419.072 451.472 25.19 28.586 6 651.672 656.73 38.714 41.958 7 945.456 1028.96 56.518 66.26 8 4199.52 4133.4 254.65 255.993 9 847.89 884.193 51.1875 56.9197 10 340.92 352.99 20.43 22.434 13 914.83 1002.34 55.031 63.64 14 161.49 155.95 9.84 9.96 15

1580.35 1507.2 96.932 96.498 16 100.51 100.41 6.0846 6.4205 18

50783.6 51486.5 3035.7 3069.5 19 72149.52 72536.6 4771.72 4818.72 20

Table 5. Load point Index EENS

EENS (MWh) 2.5 % assumed for growth peak load Buses

5th Year 4th Year 3th Year 2nd Year 1st Year 488593.8 388409.6 291546.7 233160 161344.8 Without STATCOM

2 487815.4 381780.1 289348.5 238797.4 162841 With STATCOM 106541.6 63373.13 40378.38 23999.12 10857.48 Without STATCOM

9 104825.4 64423.43 40120.77 23837.98 11916.42 With STATCOM 475053.1 319843 191823.6 120455.2 76898.94 Without STATCOM

19 466546.2 312899.9 201008.9 123033.3 74265.29 With STATCOM 466868.9 351457.9 290230.5 179385.6 117237.4 Without STATCOM

20 472025.5 362310.9 282826.4 170723.3 117753.5 With STATCOM

Table 7. System indicesSystem indices

2.5 % assumed for growth peak load Indices 5th

Year 4th

Year 3th

Year 2nd

Year 1st

Year 20672029 10146877 2579545 1163160 692426 Without STATCOM

ECOST (K$/Year) 4270255 2542723 1774819 1060664 690616.1 With STATCOM

1716653 1229600 874614.7 592478.4 387504.7 Without STATCOM EENS (MWh/Year) 1713353 1227225 872738.9 591392.6 386989.9 With STATCOM

12.04206 8.25218 2.94935 1.96321 1.786884 Without STATCOM IEAR ($/kW h) 2.492338 2.071929 2.033619 1.793502 1.784585 With STATCOM

574.0041 419.8096 312.9613 214.1986 165.4581 Without STATCOM BPII (MW/MW-Yr) 564.3011 412.7866 300.3485 207.3253 141.9218 With STATCOM

313.711 263.544 240.662 220.159 169.16 Without STATCOM BPSAC/D (MW/Disturbance) 305.0559 267.8642 234.9608 214.3386 165.9075 With STATCOM

543023.2 398679.2 290670.2 201827.4 135303.3 Without STATCOM S.M (MW-min/MW-yr) 541979.6 397909.2 290046.8 201457.5 135123.5 With STATCOM

1.033149 0.758522 0.553025 0.383994 0.257426 Without STATCOM MBPECI 1.03116 0.75706 0.5519 0.3833 0.25708 With STATCOM

Table 6. Load point Index ELC

ELC (MW) 2.5 % assumed for growth peak load Buses

5th Year 4th Year 3th Year 2nd Year 1st Year 31063.3 24591.5 18414.7 14211.9 10296.3 Without STATCOM

2 30518.6 23832.5 18002.6 14205.9 10215.6 With STATCOM 7050.13 3998.74 2411.42 1382.6 647.49 Without STATCOM

9 6912.92 4016.35 2392.51 1376 683.475 With STATCOM 28829.8 19858.9 12685.7 7869.64 4837.39 Without STATCOM

19 28327.6 19782.7 12991.3 7912.45 4711.68 With STATCOM 29614.94 21880.9 17386.5 11264.6 7587.9 Without STATCOM

20 29578.1 21998.05 17079.75 10921.1 7561.7 With STATCOM

Table 8. Load point indices

EENS (MWh) ELC (MW) Buses With

STATCOM With

UPFC With

STATCOM With

UPFC 578.98 532.3183 34.49 32.15491 1

97381.4 96326.38 6578.31 6521.262 2 671.98 597.0825 39.70 36.36419 3

2285.08 2183.592 139.39 136.1835 4 554.564 522.2143 32.85 31.30945 5 419.072 411.9499 25.19 24.91621 6 651.672 586.273 38.714 35.53622 7 945.456 943.2227 56.518 57.54286 8 4199.52 4679.163 254.65 276.1059 9 847.89 838.2056 51.1875 51.25615 10 340.92 322.751 20.43 19.72421 13 914.83 893.4547 55.031 55.25869 14 161.49 154.2367 9.84 9.437872 15

1580.35 1504.084 96.932 91.83093 16 100.51 103.046 6.0846 6.230789 18

50783.6 52024.65 3035.7 3114.01 19 72149.52 72415.43 4771.72 4782.641 20

Table 9. System indices for IEEE

STATCOM UPFC Indices

415746.6 416165.1 ECOST (K$/Year)

234566.8 235038.1 EENS(MWh/Year) 90.94514 91.15439 BPII (MW/MW-Yr)

170.6443 156.3783 BPSAC/D (MW/Disturbance)

83950.21 84118.88 S.M (MW-min/MW-yr)

0.159723 0.160044 MBPECI

6. CONCLUSIONS Reliability analysis of composite power systems should

consider different impacts, effects and policies that influence the system and load point indices. The utilization of FACTS devices to enhance transmission system capability is increasing due to their technical and economic advantages. An optimization model is proposed to be used in composite power system reliability evaluation incorporating the impact of STATCOM. The conventional AC load flow based Newton Raphson method is used to investigate the status of system for each contingency.

The study results show that the STATCOM has almost no effect on reliability of the IEEE-RTS.

The system itself has sufficient capacity and reserves to transmit power from the generating sources to the load centers under various line outage conditions. Further improvement in the transmission system does not provide much benefit in terms of the system reliability indices. At last a comparison has been done between performance of UPFC and STATCOM and showed that there is not any tangible different between results.

7. APPENDIX

Information about transfer rates of CSC has been presented in table 11.

Table 11. Failure and Repair rates for equipments of CSCRepair rate

(r/Yr)Failure rate

(f/Yr) Equipments

8760.13 DC Link 7300.004 Capacitors Banks

21900.1 GTO package 110.750.12 Step-Up Transformer 43.80.02 Intermediate Transformer 7300.2 Power Supplies 7300.2 Inverter Poles

3.3330.0005 Control System 8760.5 Cooling System

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[6] Zongxiang Lu and Wenhua Liu ”Reliability Evaluation of STATCOM Based on the k-out-of-n: G Model”, 2006 International Conference on Power System Technology [7] “ The IEEE Reliability Test System – 1996” ,IEEE Transactions on Power Systems, Vol. 14, NO. 3, August 1999 [8] E. Uzunovic , B. Fardanesh ,L. Hopkins , B. Shperling ,S. Zelingher , A. Schuff , ” NYPA Convertible Static Compensator (CSC) Application Phase I: STATCOM” , (c) 2001 IEEE [9] Bingsen Wang , Jimmie J.Cathey ,” DSP-controlled , space-vector PWM , current source converter for STATCOM application “ , Electric Power Systems Research 67(2003)123/131 [10] Roy Billinton , Yu cui “ Reliability Evaluation Of Composite Electric Power Systems Incorporating Facts”, Proceedings of the 2002 IEEE Canadian Conference [11] R. Billinton , R.N. Allan, “Reliability evaluation of Electric Power System”, 2nd edition, Plenum Press, New York, 1996. [12] Roy Billinton , Wei Zhang ,” Cost related reliability evaluation of bulk power systems “ , Electric Power and Energy Systems 23 (2001) 99-112 [13] Roy Billinton , Mahmud Fotuhi-Firuzabad, Sherif Omar Faried , and Saleh Aboreshaid “ Impact of Unified Power Flow Controllers on Power System Reliability “ , IEEE Transactions On Power Systems, Vol. 15 . No. 1, February 2000