Dissertation
Dissertation > Industrial Technology > Electrotechnical > Transmission and distribution engineering, power network and power system > Power system scheduling, management, communication > The operation of the power system

Research on Measures to Improve the Reliability of Power Grid in Shanghai

Author LiTianKang
Tutor JiangChuanWen
School Shanghai Jiaotong University
Course Electrical Engineering
Keywords Grid Reliability Assessment Maintenance optimization genetic algorithm
CLC TM732
Type Master's thesis
Year 2011
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At present, more limited studies for the reliability of the network structure and equipment levels, namely, by replacing and upgrading equipment to reduce the probability of failure by optimizing the network structure to improve the capability of load transfer when failure occurred in order to improve power supply reliability. But with the development of economy, the category and capacity of load has been changed constantly. It is not practical to plan and change the mode of operation frequently on power supply network. We are urgent to know the main factors, which highly affect on the reliability of power supply network, to propose practical effective improvement and concrete measure for increasing the reliability of power supply.According to the status and characteristics of reliability management of the Urban Power Supply Company, by in-depth analysis of existing problems and research on the basis of the urban area for power supply reliability, combined with the field of power supply reliability on advanced international management and production technology, the author proposed a model for improving the reliability of grid, reducing operation cost, reducing breakdown time, reducing the failure rate of power supply system by the optimization of maintenance programs. In this paper, transmission and distribution network optimal production plan to do a thorough research. The optimization model used the equipment availability factor for objective function, considering the system operating constraints, maintenance time constraints and repair resource constraints. Maintenance optimization model used genetic algorithms to solve the model. Compared with traditional optimization algorithms, this algorithm does not rely on gradient information, but through the simulation of natural evolutionary process to search for the optimal solution of the system. Of the IEEE-RTS system and downtown of Shanghai’s system is simulated, the results show that the optimized device can reduce the average outage expect about 5%.

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