Impact Analysis Of Human Factors On Power System Operation-PDF Free Download

Impact analysis of human factors on power system operation
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28 Yingkai BAO et al, Through analyzing major incidents of power systems in dispatchers failed to take measures after a large number of. last decades it can be seen that human factors made sig tripping which caused the accident to expand 7 On May. nificant contributions to these failures 2 Human errors 7 2004 Golmud power grid split from main grid due to. are identified as one of the main causes of the blackout in substation personnel s fault action on protection device On. North American in August 2003 3 and the Italian April 1 2005 operation personal s misoperation resulted in. blackout in September 2003 4 Human errors could occur power outage of 220 kV Lingyuan substation. in any situations involving people such as power system Some of these accidents are attributed to human errors. operation electrical equipment maintenance and power however we seldom try to investigate the cause of human. system dispatching 5 Although we gradually realize the errors Human error is not a cause but a consequence. importance of human factors in power systems there are which is shaped and provoked by the upstream factors 8. few researches in this area Operators actions in power systems can be affected by. For better analysis of human factors impact on power various factors like external environment complexity of. system reliability we should figure out human error operation task operators knowledge and experience and. mechanism and recognize how human errors occur Proper so on We consider all these factors that may cause human. analysis methods are necessary especially for quantitative errors as human factors In some researches performance. assessment Furthermore we need to demonstrate the influencing factors PIFs and performance shaping factors. influence of human factors on power system from several PSFs 9 are used to describe human factors PIFs and. main aspects After this we could obtain some measures to PSFs are usually classified according to various standards. improve human operational reliability and purposes Reference 10 proposed a data informed. In this paper we make a comprehensive introduction of PIF hierarchy for human reliability analysis which consists. human errors and some common accidents resulting from of five categories organization related time related person. human factors According to specific operation scenarios related situation related and machine related factors. we establish several models of human factors and propose Through investigation we can see that human operation. corresponding methods for human reliability analysis could be affected by many factors in power systems such. HRA These methods are verified by some power system as task complexity operation period experience physical. practical cases On this basis we establish a modified state and so on In different situations the dominating. maintenance model considering imperfect maintenance factors that have the greatest influence on human reliability. caused by human errors Furthermore the influence of may be different Therefore it is important to determine. human factors on dispatching operation and power system the exact PIFs according to actual situations. cascading failure are analyzed through IEEE 24 bus test. system Finally a novel Dispatcher Training Evaluation. Simulation System based on information decision and 3 Human factors modeling and HRA methods. action in crew IDAC is established which can consider in power systems. all the influencing factors Once fully developed it can be. used for dispatcher dynamic assessment in order to find out It is widely recognized that human errors could not be. operators shortcomings and improve power system dis avoided completely However we can take measures to. patching reliability reduce human error probability Human reliability is the. opposite concept of human error As an essential part of. probabilistic safety assessment PSA HRA has been, 2 Human errors and human factors in power widely researched in many fields which have higher. systems requirement on reliability as in nuclear power plant and. aerospace 11 Qualitative and quantitative HRA could be. Human errors can be defined as any human actions both used in system design operation and optimization in order. cognitive and physical that potentially or actually result in to improve human reliability Nevertheless in the aspect of. negative effects on system s normal functions 6 As power systems there are very few studies about HRA. power systems become more complex human operators With the development of HRA many methodologies are. are supposed to work in various situations and they may established to analyze human errors such technique for. encounter all kinds of emergencies If human behaviors human error rate prediction THERP 12 cognitive reli. exceed an acceptable limit it could lead to a disaster ability and error analysis method CREAM 13 human. The final report on August 14 2003 blackout in the error assessment and reduction technique HEART 14 a. United States and Canada shows dispatchers lack of technique for human error analysis ATHEANA 15. monitoring of grid state is an important cause leading to Moreover in some references human reliability is assessed. cascading failure 3 In the 5 25 Moscow blackout using a Markov model with a constant transition rate for. Impact analysis of human factors on power system operation reliability 29. human error 16 17 In order to recognize personals the link function which could be used to indicate the. cognitive process when dealing with system failures sev influence of covariates Z on human reliability In. eral dynamic HRA methods are proposed and IDAC is a TCHRA five main covariates are considered task. typical dynamic HRA method 18 Reference 19 iden complexity z1 environment factors z2 human knowledge. tified requirements for human reliability model to be and experience z3 human psychology z4 and physical state. integrated into system dynamic probabilistic risk analysis z5 Therefore it could be defined as. Reference 20 described the existing dynamic HRA sim Z z1 z2 z3 z4 z5 2. ulations and gave a prospect about next work to increase. the fidelity of simulated accident scenarios Lack of w Z exp cZ 3. appropriate and sufficient performance data has been We suppose the influence coefficient of each covariate. identified as a key factor affecting HRA quality especially could be 0 1 or 2 When influence coefficient is lager this. in the estimation of human error probability Therefore factor has more effect on human reliability and human. U S Nuclear Regulation Commission NRC tried to errors are more likely to occur c is the weight value of. develop a HRA database SACADA to satisfy this data each covariate Since available data is limited we cannot. need 21 obtain the weight value through fitting process by far In. We should notice that most of these methods originated this paper the weight value of covariate is obtained via. in other industries and they not specified for power sys analytic hierarchy process AHP 24 Through expert. tems So it is necessary to propose several HRA methods assessment the five covariates are compared in pairs with. suitable for power system specific situations As we know respect to their relative importance to human error. the primary cause of human errors differs a lot in different probability Then their value weight could be calculated. operation scenes Thus it is significant to make proper Assuming the operation begins at time t 0 then. classification of power system operation scenarios for human reliability function could be expressed as. human reliability analysis According to the investigation Z t. power system operation scenarios are classified into 3 Rhp t P T t exp h s Z ds 4. categories time centered scenarios process centered sce 0. narios and emergency centered scenarios Then three HRA where Rhp t is the probability that human error has not. methods suitable for the above three scenarios are proposed occurred before the moment t According to 25 Weibull. respectively distribution function could be adopted as baseline function. as shown in 5, 3 1 Time centered HRA TCHRA, Time centered scenario refers to situations where oper ab. ators should continue to work for a long time without The parameters can be estimated through careful. interruptions such as system state monitoring and new statistical analysis According to 25 b 3 a 200. equipment debugging Operators will become fatigue and hours. the probability of human error to occur will increase In order to illustrate the relation between human relia. accordingly Statistics show that many accidents are caused bility and continuous working hours we suppose there are. by people s fatigue 22 It is obvious that continuous three irrelevant scenes Through expert assessment the. working time CWT is the primary factor that affects influence coefficient and weight value in different scenes. human reliability in this scenario Besides some other are obtained shown in Table 1. human factors may also influence this process such as task Then human reliability function could be expressed as. complexity environment factors human knowledge and. experience, Proportional hazard model PHM 23 could be used Table 1 Influence coefficient and weight value in each scene. for quantitative analysis of time centered scenario PHM Covariate Influence coefficient c. has been wildly used in the field of engineering biology. Scene 1 Scene 2 Scene 3, and mechanics The hazard function in PHM consists of.
two parts baseline function and link function The hazard z1 1 1 1 0 27. function can be expressed as z2 0 1 2 0 18, h t Z h0 t w Z t 0 1 z3 0 1 2 0 22. z4 1 1 2 0 15, where h0 t is the baseline function which could be used to z5 0 1 2 0 18. indicate the change of human reliability with CWT w Z is. 30 Yingkai BAO et al, bs Table 2 Nominal values for cognitive function failures. Rhp t exp exp cZ ds 6, 0 ab Cognitive function Generic failure type Basic value. The probability of human error could be expressed as Observation O1 Wrong object observed 0 001. Fhp t 1 Rhp t 7 O2 Wrong identification 0 007, O3 Observation not made 0 007.
With the increase of CWT human error probability Interpretation I1 Faulty diagnosis 0 02. changes as shown in Fig 1 I2 Decision error 0 01, In Fig 1 when CWT is less than 10 hours the human I3 Delayed interpretation 0 01. error probability is extremely low less than 7 9 10 4 Planning P1 Priority error 0 01. When CWT increases human error probability increases P2 Inadequate plan 0 01. accordingly Although the staffs work less than 10 hours a Execution E1 Action of wrong type 0 003. day under normal conditions long time lasting work still E2 Action of wrong time 0 003. exists such as annual inspection of main transformer while E3 Action of wrong object 0 0005. the whole substation is out of power and new equipment E4 Action out of sequence 0 003. debugging before operation Through investigation we find. E5 Missed action 0 003, that human errors are more likely to happen in these. situations, Thus in order to ensure operational reliability we. should limit continuous work within reasonable time generalized as three levels reduced not significant and. Besides we could take some measures to improve human improved shown in Table 3. reliability such as improving operator s skill and experi The CREAM standard method divided the control. ence by training improving operator s mental and physical model into four classes Strategic Tactical Opportunistic. state and making work condition more suitable and Scrambled Each control model has a corresponding. error probability interval 13 Although CREAM method. 3 2 Process centered HRA PCHRA has been widely accepted and used in many fields some. aspects require improvement Since the CPCs are not. Process centered scenario refers to situations where specially introduced for power systems we should con. operation task consists of many steps and operators should cretize CPCs according to regulations and actual conditions. follow certain procedures to finish the work We should in power systems 26 For example working conditions. pay attention to the process to avoid human errors Modi could be divided into sub CPCs personal security. fied CREAM could be used to analyze this kind of sce requirement equipment security requirement and envi. nario CREAM 13 proposed by Hollnagel E hold the ronment requirement. idea that cognitive functions contain several generic failure We could assess each sub CPCs firstly then we can. types CREAM concluded the basic probability value of obtain the score of CPCs with analytic hierarchy process. each generic failure type which is called cognitive failure The score of CPC varies from 0 to 100 according to the. probability CFP The nominal values of cognitive func concrete conditions except Time of day which varies from. tion failures are shown in Table 2 0 to 24 Since human reliability analysis is still at the. In CREAM all human factors are divided into 9 cate starting stage in power systems and related data statistics. gories called common performance conditions CPC The is still very scarce The use of expert systems such as fuzzy. expected influence of CPCs on human reliability could be expert systems can be helpful to improve the assessments. with limited data available 27 In this paper triangular. fuzzy model is used to lower subjectivity of judgment. 0 12 The process of quantifying human error in process. are veri ed by some power system practical cases On this base this paper illustrates how human factors affect power system operation reliability from 2 typical aspects imperfect maintenance caused by human errors and impact of human factors on emergency dispatch operation and power system cascading failure Finally based on infor

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