Risk and Reliability Analysis of Substation Automation Systems using Importance Measures

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1 Risk and Reliability Analysis of Substation Automation Systems using Importance Measures RamaKoteswara Rao Alla 1, G.L.Pahuja 2, J.S.Lather 3 1 Research Scholar, Electrical Engineering Department 2,3 Professor, Electrical Engineering Department, National Institute of Technology Kurukshetra, India ramnitkkr@gmail.com 1, pahuja.gl@gmail.com 2, jslather@gmail.com 3 Abstract Risk is the possibility that an undesirable event might occur in the future that will result in some negative consequences. Risk analysis of a system is required to protect the system from risky (more failure prone) components. Reliability Importance measures play an important role in ranking the components according to the impact on the system adequate performance. Risk based measures are useful in identifying the weak components and help in improving the reliability of the overall system efficiently. Risk and Reliability of Substation Automation System (SAS) are most important and desirable design considerations. SAS consists of different components and its applications require real time performance. Three substation automation system architectures are considered in this paper. Two important measures Improvement Potential (IP) and Risk Achievement Worth (RAW) are used to prioritize the components in two types of architectures of SAS. System reliability expressions for all architectures are computed with their reliability block diagrams. On the basis of these two IP and RAW measures the components, and are most important, BCU and are least important components from both maintenance and risk point of view. Keywords Reliability, Importance Measures, Substation Automation system, Improvement Potential, Risk Achievement Worth NOMENCLATURE SAS Substation Automation System DC power supply BCU Bay control unit Ethernet switch Ethernet interface IED Intelligent electronic device Industrial personal computer Human machine interface NCC Network control center Network control center server RBD Reliability block diagram MTTF Mean time to failure /14/$ IEEE HL IM RAW Hierarchical level Important measure Reliability achievement worth I. INTRODUCTION A substation is a part of an electrical power system generation, transmission and distribution system. The automation of any system reduces ill effects caused due to human involvement and increases the efficiency. Automation is a step ahead of mechanization, in the extent of industrialization. By considering protection issues and proper working of the substation every component has a specific important role. Substation System automation provides the control of power system apparatus operations and monitoring automatically. Intelligent electronic devices (IED) data is used to communicate remote users and to control the power system devices within the SAS [3]. The reliability of a SAS not only depends on the reliability of the basic components but also on the arrangement of these components in the architecture/system structure of automation system. Important measures can be used to rank and get the information about the risk of the events, components, and system structures [1-3]. An approach to develop and quantitatively asses the reliability for different configurations of SAS based on event tree and reliability block diagrams is presented in [5]. Reliability evaluation of SAS for different architectures and component importance with Birnbaum s, criticality importance measure has been analyzed in [4]. The reliability and availability analysis of IEC based SAS using RBD is given in [6]. In [7] Fault tree analysis (FTA) based reliability evaluation of substation control networks is given. However the risk based importance analysis of SAS has not considered in the literature to the best of knowledge of the authors. In this paper two suitable risk based important measures Improvement Potential (IP) and advanced Risk Achievement Worth (RAW) are implemented/used to rank the components of given SAS. Advanced RAW is proposed in terms of Birnbaum s measure. The results of different measures are also discussed. The remaining paper is organised as: Section II presents the architectures, respective RBD s of the architectures of the substation automation system and their reliability evaluation. In Section III different important measures are described. Section IV presents evaluation/

2 computation of the component importance measures and observations/findings of these. Section V concludes the paper. II. ARCHITECTURES AND RBD S OF SUBSTATION AUTOMATION SYSTEMS System architecture in general gives an idea about system structure, system components and their relationships. A typical SAS consists set of various components at different levels and these are DC power supply (), Bay control unit (BCU), Ethernet switch (), Ethernet interface (), Intelligent electronic device (IED), Human machine interface (), Industrial personal computer (), Network control center (NCC) server. Every component has its specific function. Three hierarchical levels (HLs) that exist: Remote control point HL1, station control point HL2, bay control point HL3.The function of bay control level is normally ignored. The control command actuated from HL1 and HL2 will be considered. The details of these may be studied in [5].Three SAS architectures that have been considered are: simple cascading, redundant cascading, and ring architectures. In simple cascading structure, all the switches are connected to the next or previous switch as shown in fig.1. This architecture is cost effective, simple and requires less wiring. If one of the cascade connections is defective all the IEDs under that connection are lost. This can be overcome in case of redundant cascading case illustrated in fig.2. Availability of the system can also be increased compared to simple cascading architecture. This structure can tolerate one fault. By forming the closed loop in the simple cascading architecture leads to ring architecture shown in fig. 3. This can also provide some redundancy to the system but latency of the ring structure is to be considered in case sensitive applications. Fig2. Redundant cascading architecture (Architecture2) Fig3. Ring architecture (Architecture 3) Reliability Block Diagram (RBD) is a logical/functional relationship of components of the system. The components in RBD are connected either in series, parallel, mesh or a combination of them. A series configuration in RBD indicates that all of the components must operate for the system to operate; a parallel configuration indicates that system works if at least one of the components operates. Fig.4 gives the RBDs of different architectures considered. The reliability expressions of architectures are derived from their respective RBDs. Fig1. Simple cascading architecture (Architecture 1) BCU+ a. RBD of Cascading Architecture BCU+ b. RBD of Redundant cascading architecture

3 1 BCU++ ser.3 2 c. RBD of Ring architecture Fig.4. Reliability Block Diagrams of various SAS architectures A. Reliability Evaluation of RBDs The reliability, R (t), of an item (a component or a system) is defined as the probability that, when operating under stated environmental conditions, it will perform its required function adequately in the specified interval of time [0, t]. Reliability of any component can be expressed as (1) where λ is failure rate. Mean Time To Failure (MTTF) =1/ The reliabilities of DC power system, Bay control units, Ethernet interface, Ethernet switches, Human Machine Interface, NCC server and industrial personal computer can be designated as P, P BCU, P, P, P, P and P respectively. Let the reliability of architecture i as R i sys (t) The generalized formula for k-out-of-n-g system is:, ; 1 (2) The reliability of block BCU+ may be expressed as: The reliability of block n of n: 6 can be expressed as: By combining all the blocks expressions and simplifying by ignoring much higher powers the system reliability of architecture 1 is (3) Similarly, system reliability of architecture 2 is (4) The system reliability of architecture 3 is (5) The system reliability can be calculated by using the MTTF data given in Table 1. [8] And the architectures reliability is given in table 2. Table.1 MTTF of different components Component MTTF(yr) Reliability (%) BCU Table2. Reliability of architectures Architecture Reliability (%) The reliability of the Architecture 1 (simple cascading) is minimum and ring architecture is the highest. Since architecture 1 has lowest reliability it is not considered further for component importance analysis. III. COMPONENT IMPORTANT MEASURES In system Reliability theory, component importance measures place important role. The importance measures evaluate the role of the components or basic events to the considered measure of system performance [9]. The importance measures may be used to grade the components, that is, to organize the components in order of increasing or decreasing manner. Thus Importance analysis is performed to numerically quantify the importance of each individual component in the system. These measures are helpful to identify the weak components so that efforts can be made to improve the system reliability [10].Various IM s exist in the literature [1-3]. The Birnbaum s measure, Improvement potential (IP) and Risk Achievement Worth (RAW) are used in this paper to carry out the component importance analysis of substation automation system. A. Birnbaum s Measure of Reliability Importance: The Birnbaum s importance measure (Birnbaum, 1969) of a component or basic event is defined as the partial derivative of system reliability with respect to component reliability [2].Birnbaum s measure of Reliability importance of component i at time t is I B i t= R where i 1,2,, n (6) P

4 Birnbaum importance of component i at time t can also be expressed as I B i t= =h (1 P i, p(t))-h(0 i, p(t)) (7) If I B i t is large, a small change in the reliability of component i will result in comparatively large in the system reliability at time t. It depends on the structure of the system. B. Improvement Potential (IP) In some cases it may be of interest to know how much system reliability increases if component i is replaced by a perfect component [11]. IP measure gives idea about the same. It is denoted by I IP (i/t). It can be defined as / 1, (8) where i= 1,2,.n h(p(t)) is the system reliability. The improvement potential in terms of Birnbaum s measure can be defined as / /1 (9) C. Risk Achievement worth (RAW) RAW is commonly used to identify the role of basic event in relation to the risk.raw is a risk importance measure which is based on the best estimate values of probability of basic events[12]. The importance of the basic event is evaluated by changing its probability from the normal value to the extreme value (0). RAW presents a measure of the worth of component i in achieving the present level of system reliability and indicates the importance of maintaining the current level of reliability for the component. The importance measure RAW of a component i at time t is defined as /, 1,2,. (10) Risk Achievement worth in terms of Birnbaum measure proposed is / I B (i;p) where h(p(t)) is the reliability of the system. (11) IV. RESULTS & DISCUSSION OF DIFFERENT MEASURES Table 3: Component Importance Measure for architecture2 Measure BCU I B [4] I IP I RAW Order: I B > > > > (==BCU) I IP > > > > > > BCU I RAW > > > > > (BCU=) Table 4: Component Importance Measure for architecture3 Measure BCU 1 2 ser.3 I B [4] I IP I RAW Order: I B > > ( ser.3 = BCU) > (2=) > (==1) I IP > ser.3 > 2 > > > 1> > BCU > I RAW > ser.3 > 2 > > > 1> > BCU > A. Discussion Table 3 and Table 4 show the result of different measures for architecture2 and architecture 3. This is observed that the ranking of different components are not same for the all the measures in these architectures. But has ranked first in all since breakdown of cause shutdown of most of the functions. is also important next to because failure of cause loss of information from the downstream BCUs connected to that. In case of architecture 2 Birnbaum measure gives preference to component as compared to. But Improvement potential measure shows that is to be ranked high than. In maintenance point of view also has least importance since it has high MTTF. Hence its low rank is justified.,, are in parallel configuration so they are ranked next to the and because the importance of the components not only depends on the reliability of the component but also on place of the component in the structure of the system. In case of architecture 3 also I B measure ranks higher than where as I IP measure ranks as the least ranked one. Ethernet switches have more importance compared to and too. So it can be observed that I IP measure gives logical results compared to I B measure by giving suitable ranking. In this architecture after, ser3 is ranked high since s connected to BCUs are most important than the

5 connected to servers. The remaining components has similar ranking as in architecture 2. However the system designer should make the objective as if the reliability of a component can be increased by considering a perfect component I IP measure is useful, if the reliability of a component need to be increased by specific amount I B measure can be considered. Risk achievement worth for a basic event shows increase in the accident sequence frequency that would be obtained if the lower level event, the failure of a component modelled in the basic event would occur. An advanced RAW measure proposed is computed for different architectures. From the table 3 and table 4 it can be seen that the RAW ranking of different components for architecture 2 and architecture 3. has first preference than other components and has least preference. In architecture 2 BCU and have same rank where as in architecture 3 BCU is ranked prior to. RAW gives information about the increase in risk if the component is not to be there or failed. So it can be observed that, have more important from risk point of view compared to other components since the remaining components are in parallel configuration. [6] U. B. Anombem, H. Li, P. Crossley, R. Zhang, and C. McTaggart, Flexible IEC process bus architecture designs to support life-time maintenance strategy of substation automation systems, in CIGRE Study Committee B5 Colloq., Jeju, Korea, Oct [7] R. E. Cosse, Jr. et al., Smart industrial substations A modern integrated approach, in Proc. IEEE Conf. Rec. Annu. Pulp Paper Ind. Tech. Conf., 2004, pp [8] Scheer GW. Answering substation automation questions through fault tree analysis. In: Proceedings of the 4th annual texas A&M substation automation conference, College Station Texas; April 8 9, [9] Enrico Zio, Computational Methods For Reliability And Risk Analysis, Series On Quality, Reliability And Engineering Statistics, World Scientific Publishing Co. Pvt. Ltd., vol 14, 2009, pp [10] Elsayed EA. Reliability engineering. New York: Addison Wesley/Longman; [11] Rausand M, Hoyland A. System reliability theory: models, statistical methods, and applications. 2nd ed. John Wiley Sons; [12] G.J. Anders, Ontario Hydro, Evaluation of Importance and Related Reliability Measures for Electric Power Systems, IEEE Transactions on Power Apparatus and Systems, vol. PAS-102, No. 3, March 1983, pp V. CONCLUSION In design and maintenance processes of systems risk analysis of components is an important input to be considered in decision making. The results of risk based importance measures provide concrete ways to compare relative risks and to inform the design decision makers about the component risk consequences of their decisions. Risk based measures for different SAS architectures are evaluated in this paper. RAW measure in terms of I B is proposed. With the help of ranking of system components obtained from these measures, performance of SAS can effectively and optimally be improved. IM in general depend on system structure and reliability. Only component reliability/failure rate or its place in system structure does not give correct IM in general. However the different important measures consider these two measures along with system reliability and reliability of other components. On the basis of IP and RAW measures it may be concluded that, and are most important components from risk and IP point of view. REFERENCES [1] F. C. Meng, Comparing the importance of system elements by some structural characteristics, IEEE Trans. on Reliability, vol. 45, pp , [2] Z. W. Birnbaum, On the importance of different components in a multi component system, in Multivariate Analysis, P. R. Krishnaiah, Ed. New York: Academic Press, pp , [3] Dolezilek Dj. Choosing between communication processors, RTUs, and PLCs as substation automation controllers (internet): October, [4] H. Hajian-Hoseinabadi, Reliability and component importance analysis of substation automation systems, Int. J. Elect. Power Energy Syst.,vol. 49, pp , [5] H. Hajian-Hoseinabadi, Impacts of automated control systems on substation reliability, IEEE Trans. Power Del., vol. 26, no. 3, pp , Jul