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Research and Application on Optimization Method of Power Network Maintenance Scheduling

Author: XieZuo
Tutor: LiuWenYing
School: North China Electric Power University
Course: Proceedings of the
Keywords: power network maintenance scheduling multi-objective optimization multi-objective particle swarm optimization multiple data sources day-aheadforecast power flow security correction visualization and intelligent analysis
CLC: TM732
Type: PhD thesis
Year: 2013
Downloads: 55
Quote: 0
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As an important work in the day-to-day running of the power supply enterprise, planned maintenance of electrical equipment is a necessary measure to improve the health level of equipment, and ensure the safe operation of power grid and a continuous and reliable power supply. Maintenance scheduling of network is mainly completed by manually, and affected by the man-made factors such as professional and technical ability, working experience and so on greatly, and lack of consideration on the economic efficiency and reliability of power supply. At present, the research of power system maintenance scheduling mainly focuses on the unit maintenance scheduling, and the theoretical research and practical application of network maintenance scheduling are at a preliminary stage. Therefore, based on the theoretical study of the unit maintenance scheduling, this paper analysis and summarize the general process and characteristics of the compilation of network maintenance scheduling, and introduce the multi-objective optimization theory to solve network maintenance plan optimization, and study the day-ahead security correction and develop a system which carry out the maintenance scheduling planning optimization and compilation, the innovative achievements are as follow:From the different point of view which grid maintenance scheduling optimization focus on, this paper proposes practical optimization method, multi-objective optimization method and interactive optimization method for maintenance scheduling, which can coordinate the economic and reliability objectives of maintenance scheduling optimization problem. The multi-objective optimization method of maintenance scheduling took the minimum maintenance cost and expected energy not supplied (EENS) as objective functions, and built a multi-objective optimization model for maintenance scheduling of transmission network and proposed an improved multi-objective particle swarm optimization algorithm based on niche technology for the built model, which used the niche sharing mechanism to update particle’s position so as to keep the diversity of solution and the uniformity of distribution, and led in the chaotic mutation to part of non-dominated particles in order to enhance the global searching ability and avoid the local optimum. The interactive optimization method of maintenance scheduling introduced the preference of decision-makers into the multi-objective optimization model, and constructed an interactive decision-making model based on the satisfaction degree of objective and the nearness degree of objective, and decomposed the multi-objective optimization model into three single-objective decision-making models to solve the multi-objective optimization problem. In order to make the algorithm apply to maintenance scheduling optimization problem better, the model constraints handling and optimal solution selected were improved. This paper processed the constraints by using a penalty function, and selected the best compromise solution from the Pareto optimal solution set according to fuzzy membership degree, and provided the scientific decision basis for maintenance plan makers.The traditional method of security correction of power grid dispatching planning exists some problems such as rough calculations, larger error of the results and so on. Using day-head forecast power flow for security correction in power grid dispatching planning can solve these problems. This paper presents an auto-generated method of day-ahead forecast power flow based on multiple sources, which can generate the day-head forecast power flow automatically and improve the precision and accuracy of security correction work in power grid dispatching planning. Firstly, this method analysis the parameters constitute of normal operation mode of day-head power grid from the view of day-ahead forecast power flow calculation model. Secondly, it generate the parameters which used for day-head forecast power flow calculation automatically by getting data from multiple data sources and fitting these data, and set up the model of day-ahead forecast power flow calculation. Finally, it adjust the model of power flow according to the combined dynamic power flow algorithm, and generate the day-head forecast power flow which is converged automatically. The results of the security correction system in some an area power grid dispatching planning using this method verify its convergence and effectiveness.According to the actual planning process of maintenance scheduling of Power network, this paper designs a visualization supporting system for power network maintenance scheduling optimization. The main function of the system include: firstly, generates an optimized maintenance scheme automatically according to the practical maintenance scheduling optimization algorithm presented in the paper; secondly, achieves the day-ahead security check of maintenance scheduling based on multiple data sources by the automatic generation method of forecast power flow presented in this paper; thirdly, builds the visual simulation platform of maintenance scheduling by the figure module integration technology, which can display the outage range and the rules knowledge of equipment maintenance, and provides the intelligent and visualization maintenance planning tools for the users.

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