The Study On Distribution System State Estimation And Robustness Of Measurement System Placement

Nowadays, the advances in monitoring equipment technologies have promoted the development of smart distribution system. From smart grid point of view, system state monitoring is important. Smart grid presents a future grid prospect, characterized as penetration, distribution, cooperative and self-healing. In the near future, The distribution system can supply electric power to customers in a more flexible way. An active distribution network needs to use communication and information technologies to achieve smart grid concept. Power system needs to enhance the state estimation theory and the measurement infrastructure.Distribution system state estimation is becoming an essential part of distribution management systems. Distribution system state estimation faces the challenge of the lack of available real-time measurements. The infrastructure of distribution system is not sufficient for smart grid applications. The construction of a measurement system is essential for smart grid. Most existing distribution measurement placement algorithms only consider the normal operation condition, neglecting the variety of distribution system structure. The study of a robust measurement placement algorithm and state estimation algorithm is important.This paper makes a study on the distribution system state estimation and robustness of measurement placement algorithm. This study will provide a new development of smart grid.A fast distribution system state estimation model needs to be built in order to realize on-line distribution state estimation. This paper studied the established distribution system state estimation algorithms and measurement transformation technique, and derived a decoupled three-phase linear state estimation model, which simplified distribution system state estimation. MATLAB simulation compared the results between linear state estimation and the branch-current-based state estimation, in which the linear state estimation showed an effective performance.Self-healing is an important characteristic of smart distribution grid. Self-healing allows power system to make quick simulation and decision through monitoring system, avoiding large area power outage and recovering from emergency condition. The basis of self-healing is distribution reconfiguration. This paper mainly studied distribution reconfiguration for fault recovery using genetic algorithm. The method determined the outage area and operational branch by topology analysis, and transformed the infeasible solution, which improved the computing time effectively.The possible variation of distribution system topology is uncertainty sources very often not considered in distribution measurement placement problem. This paper presented a robust measurement placement algorithm aimed to estimate distribution system accurately in all cases. Furthermore this paper analyzed the relation between distribution system state estimation accuracy and measurement quantity and proposed measurement saturation. The robust measurement placement is solved by determining the number and location of measurement separately. Simulation results showed that the method is effective and feasible.