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Research On Reconfiguration Of Distribution Network With Distributed Generation

Posted on:2017-02-08Degree:MasterType:Thesis
Country:ChinaCandidate:Z Z SunFull Text:PDF
GTID:2272330509454977Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
In recent years, with the exploitation and utilization of fossil fuels, the ecological environment continues to be destroyed, and the global energy is in severe shortage.The new energy development, energy saving and environmental protection problem has become particularly prominent. Distributed generation has received extensive attention and deeply studied by many scholars at home and abroad because of its unique environmental protection, diversity, economics and renewability.DG connecting electric grid can realize the supplement of large power grid, improve the stability of the system, provide reliable and high quality power for users. DG inter-connection simultaneously put forward higher requirements for the distribution network reconfiguration, the optimization operation and coordinated control of the distribution network. Therefore, how to use the network reconstruction has important theoretical value and practical significance to realize the safe and economic operation of distribution power system. This paper mainly discusses the power flow algorithm of distribution network with DG and the effect of DG grid-connected position, size,quantity and type on network loss and voltage. Static reconfiguration algorithm of distribution network with DG is further studied and its performance is analyzed. The main research contents and achievements are as follows:Firstly, this paper briefly introduces the basic knowledge of graph theory, the simplification method of network structure, radial judgment, the method of power flow calculation and so on. The back/forward sweep algorithm based on node layer matrix is presented in detail, and a numerical example is carried out. The power flow calculation program has been repeatedly called in the process of distribution network reconfiguration, a fast and effective power flow calculation can greatly shorten the time of the whole network structural optimization. Secondly, the improved back/forward sweep method based on node layer matrix is studied in this paper to reliably calculate the power flow of distribution network with DG. The algorithm can effectively handle the influence of PQ, PI, PV, PQ(V) type nodes on the original power flow algorithm, and improve the efficiency and accuracy of the power flow calculation. The IEEE 33-bus example is simulated to illustrate the effect of distributed power grid-connected number, location, size and type on the distribution power flow. The simulation results show that the proposed algorithm is efficient, rapid and practical.To further optimize the operation structure of the distribution network with DG and searching network switch optimal combination, this paper gives a distribution network reconfiguration strategy based on double hybrid particle swarm algorithm combining with the network structure simplification and branches grouping. The network loss is selected as the objective function in the method. There are two steps to improve particle search efficiency and avoid prematurity. Firstly, the network structure is simplified and decomposed into subsystems, then, the dimensions of coding are reduced. Secondly, the improved binary particle swarm optimization algorithm is used in searching between groups, and the proposed group binary particle swarm search algorithm is used in searching within the group. The proposed algorithm is respectively tested on the IEEE 33-bus and IEEE 69-bus distribution power system, and compared with other existing literature method, the simulation results illustrate that the proposed algorithm can get the optimal configuration results,significantly reduce system energy losses with fast convergence rate, and thus lay the foundation for the optimal operation of distribution network.
Keywords/Search Tags:distributed generation, distribution network reconfiguration, improved back/forward sweep algorithm, double hybrid particle swarm algorithm
PDF Full Text Request
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