Research On Methods Of Self-healing In Distribution Network With Distributed Generation

With the increasing of global energy demand and the users’ requirements forpower quality improved, under the background of the increasing pressure onresources environment and the rapid development in electricity market, the concept ofSmart Grid is constantly being mentioned, as one of the most important features ofSmart Grid, related researches on self-healing control are more and more takenseriously. Self-healing control consists of two parts: self-prevention and self-controlin normal state; insulate quickly and self-recovery in fault state, to avoid widespreadpower outage. This thesis studies on the second part: the fault location and failurerecovery of distribution network, design to achieve uninterrupted supply of electricity.Firstly, a brief introduction of the concept of self-healing is given in this paper.Then it is analyzed that the current status of fault location in distribution network andfailure recovery in distribution systems with distributed generation (DG). In thispaper the common models of DG and its effect on distribution network are alsodescribed. The basic theory of Petri nets is also introduced, a model of Petri net andrule of inference are established on the theory used to find the point (or the area) offault. Finally, genetic simulated annealing algorithm is proposed to solve failurerecovery in distribution systems with DG. On the basis of algorithms of genetic andsimulated annealing, combined with the advantages of both, using binary encoding,crossover and mutation operation is set up according to the value of individual fitness,then the new individuals is generated and accepted by using simulated annealingalgorithm to keep the diversity of the population, avoid falling into local optimumand improve the global optimization capability of genetic algorithm. The objectivefunction is minimum active network loss and then as much as possible to restorepower area. At the end THE IEEE-16node system is used to validate the algorithmeffectiveness. The results show that the algorithm is effective for failure recovery.