Research On Self-healing Control Key Technologies And Methods Of Smart Distribution Systems

Distribution systems are linked with the consumers. Its operating states directly concern the power quality of consumers and the economic benefits of the power supply companies. Recently, plently of renewable energy distributed generat ors(DGs), such as wind and photovoltaic generators, have been integrated in the distribution systems owing to their environmental and economic considerations. Meanwhile, the impacts of integration of DGs should be considered on the safety and economic operation of distribution system s. Smart distribution systems self-healing control technologies, which are coordination and optimization of various control strategies, are more likely to play a major role in solving the long existed problem of domestic distribution systems, which contains low utilization of equipments, low reliability and high line loss rating of the system.Consequently, in order to reseach the demand in self-healing control of smart distribution systems, the framework of self-healing control has been established. The thesis focuses on the method of operating states classification, the applications of network reconfiguration on optimization control based day-ahead scheduling, alert control and recovery control of fault, as follows:A fast network reconfiguration method of avoiding infeasible solutions for distribution system is proposed. Fundmental loop and automatically generating fundmental loop matrix are proposed based on the topological feature of distribution systems which is designed as closed-loop systems, but operated in radial arrangement. Then, four encoding rules applied in intelligent optimization algorithms are presented for avoiding infeasible solutions during the network reconfiguration by analysis the drawbacks of exiting methods. The accuracy, feasibility and engineering practicality of the proposed method to avoid infeasible solutions is proved by the combination of the proposed rules with harmony search algorithm.A novel interval optimization based day-ahead scheduling model co nsidering renewable energy generation uncertainties is proposed for distribution system s. In this approach, the forecasting errors of wind speed, solar radiation intensity and loads are formulated as interval numbers so as to avoid any need for accurate probability distribution. In this model, the total nodal voltage deviation and network power losses are optimized for the economic operation of distribution systems with improved power quality. Consequently, the order relation of interval numbers is used to transform the proposed interval optimal scheduling model into a deterministic optimization problem which can then be solved using the harmony search algorithm. Based on the exploitation of various optimization controllable means, s imulation results showed that considerable improvements on system nodal voltage profile and power losses can be achieved with multiple interval sources of uncertain renewable energy generation and loads.A multi-stage optimization based index decision for alert control is proposed. A multi-stage decision of optimization model, which is organic integration of regulation of output for DGs and reactive power compensation device, network reconfiguration, and load shedding, is presented in this paper to achieve the best benefit with the minimum cost. Based on analysizing the impact of installation of DGs with high penetration in smart distribution systems, a sensitivity analysis method is presented to control the DGs and reactive power compensation device orderly for improving the nodal voltage and capacity of branches. The variation of load and DGs output within a day is simulated to generate the corresponding control measures of nodal voltage and line loading rate over the limit. The effectiveness of the propose approach is demonstrated by simulations results.A fast and effective service restoration method is proposed for medium-voltage distribution systems by combining intentional islanding of distributed generators with network reconfiguration. In order to consider the remote load control switches are partially controllable, a depth-first search algorithm, as many as possible critical loads, to which the power supply should be ensured, is presented for islanding partition to quickly form intentional islanding schemes and satisfy all co nstraints. Compared to the existing intelligent algorithms, this method can effectively reduce the time-consuming and obtain an optimal solution. The whole process of restoration is regarded as a multi-stages decision problem, which is divided into four stages: matching islanding schemes, restoration of network connectivity, network reconfiguration and load shedding. Under the condition of safety limits, the out of service areas are achieved maximization of restoration, making full use of DGs. Moreover, heuristic rules have been applied to lead a better balance between speed and efficient global optimization for network reconfiguration.