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Research On Planning Of County Distribution Network Based On Stratified Zoning

Posted on:2019-05-10Degree:MasterType:Thesis
Country:ChinaCandidate:Y WangFull Text:PDF
GTID:2382330572956571Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
County distribution network is an important part of the connection between power grid enterprises and users.With the rapid development of the economy,the demand for electricity has grown rapidly.The planning and construction of distribution networks must firstly consider the user’s demand,and the issue of new power access.Recently with the distributed power supply connected to the network,high-energy enterprises are gradually replaced by clean energy ones.The new demand for electricity is showing a new situation.It is necessary to continuously improve the power grid planning method and update the traditional planning concept.The planning and construction of distribution networks must adapt to the new situation,comprehensively consider urban and rural planning and economic development trends,and meet the power supply and higher power quality requirements under the new situation.Based on the principle of hierarchical zoning management of distribution network,this paper focuses on the analysis of distribution network zoning load demand analysis and substation and grid planning,and focuses on the analysis of distribution network 35-110kV planning in county areas.This paper improves the grey prediction method to predict the load of various voltage grades and various power supply areas.According to the forecast results,the design scheme of the distribution network substation layout points and network frame structures is put forward,and scientific and reasonable methods are used to verify it.This paper mainly studies and applies from the following three aspects1.The improved grey forecasting method is used to predict the distribution network in county districts by stratifying the load,and take into account the impact of old and new kinetic energy conversion,economic development and distributed power access on the load of the distribution network,and to revise the basic data and forecast results of the traditional grey prediction model.It improves the accuracy of predictions.The improved grey forecasting method is verified with a concrete example,which lays the foundation for the next research on the location of substation capacity determination.2.1n view of the problems existing in the current substation planning and site selection methods,the improved radar map principle method is proposed for the first time to quantify the factors affecting substation site selection.The concept of radar map weight value is introduced innovatively,and the location is accurately selected through area comparison.Based on the load forecast and the overall urban planning and county economic development of government departments,the capacity analysis of subdistrict substations is carried out according to the concrete examples,and the optimal scheme for the location of substations is reasonably determined.3.The optimal model of hierarchical partition expansion of grid structure in distribution network is constructed.By using improved genetic algorithm to solve the model,the proposed scheme has better economy,and the calculation speed and precision have been improved obviously.With concrete examples,combined with the actual characteristics of county distribution network planning,the improved genetic algorithm is used to solve the horizontal annual power grid planning model,and the planning scheme has better reliability and economy.The improved grey prediction method,radar diagram principle and genetic algorithm are packaged,and the distribution network planning program is developed.It realizes the fast and accurate calculation of load prediction,substation fixed capacity location and high voltage grid design to effectively guide the distribution power grid planning work.
Keywords/Search Tags:distribution network, layered partition, load forecasting, substation lation, network structure expansion
PDF Full Text Request
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