Study On Approaches Of Power System Fault Diagnosis

Reliability is one of the basic requirements of power system, but faults are inevitable, because of weather, human factors, and so on. Dispatchers must estimate the cause of the fault, insulate the elements of fault and restore the normal operation of the system quickly, in order to reduce the damage to the electrical elements, and guarantee secure and reliable electricity supply to users.When power system fault happens, the protection relays and the circuit breakers may misoperation or disoperation, alarms information may loss or distortion in the process of transmission, faults may happen in several components. All these make the actual fault complex, which makes it difficult for individuals to make decision correctly in a short period of time. Fault Diagnosis System can help dispatchers find fault components quickly.Genetic algorithm (GA) transforms fault diagnosis problem into 0, 1 integer programming problem, and then solves it using optimization algorithms. It is a mature power system fault diagnosis method, and has been applied to the actual system. In this paper, based on the work of our predecessors, a number of improvements - single point of fault completely initialized, retaining 10% of the fine, three cross points - are used in the genetic algorithm. These improvements enhance the convergence performance of the genetic algorithm. Considering the large amount of incomplete information in actual systems, the state of absent information is estimated in the iterative process. Experimentation achieves good diagnosis results.Bayesian network (BN) and subjective Bayesian (SB) approach are two commonly used methods of uncertain reasoning (UR). BN is clear, easy to understand and easy to express causal relationship between data. But its parameters are often difficult to obtain. The SB approach transforms the knowledge of importation into evaluation of two parameters - LS and LN, which avoids a lot of data statistic work. Taking into account both benefits, the paper explored using SB approach to the BN parameter settings and reasoning calculation, thus realizing a combination of the two.On this basis, BN and SB approach are introduced synchronously into power system fault diagnosis. BN is used in system modeling; and SB approach is used in parameter settings and reasoning. The BN is rationally simplified before inferring with the SB approach, which makes the approach more efficient. Two more approaches, i. e. inference with uncertainty reasoning and comparison of the number of abnormal events, are proposed to deal with the uncertain and lost information. The two approaches can be used in conjunction; however, their computing speed will be too low when too much information gets lost. A group of rules are thus adopted to infer the most likely state of lost information and ignore the unimportant information so as to improve the computing efficiency. Finally, the result s of several tests show the scheme proposed is rational and practical.GA and SB approach are completely different methods of fault diagnosis. The former gradually approaches optimal solution through iteration. And the latter doesn't have iterative process. It can give the fault probability of the components directly, so it has a higher diagnosis speed. Examples show that the two approaches both have good ability to handle complex fault condition, and have good application prospects.