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Distribution Network Planning Based On Improved Minimum-Cost Spanning Tree Algorihm

Posted on:2006-12-23Degree:DoctorType:Dissertation
Country:ChinaCandidate:W Y YangFull Text:PDF
GTID:1102360155977432Subject:Power electronics and electric drive
Abstract/Summary:PDF Full Text Request
Improved Minimum-Cost Spanning Tree (MCST) based algorithms for distribution network planning, expansion planning, planning considering uncertainty and multistage planning are investigated. The main achievements are as follows:.An improved MCST based algorithm is put forward. The load points are regarded as vertexes. The routes, along which, feeder lines might be implanted are regarded as edges. The summation of construction cost and operational cost of each feeder is defined as the weight of the corresponding edge. Based on the preliminary planning results of basic MCST algorithm, by adjusting the weights of each edge dynamically and implanting an iteration method, the optimal planning result of the minimum total cost is obtained. Cross points are well dealed with. The proposed method is extended into meshed network planning. Based on the improved MCST based algorithm, an algorithm for expansion planning is proposed. The investment limitation is used as constraint condition. The residual value and costs of removed feeders are also considered in the expanding planning.A Monte-Carlo simulation based approach to comparing various algorithms for expansion planning of distribution networks is presented. Various scenarios are formed on a given grid by randomly setting main position, loads and other parameters. Planning result of each algorithm is obtained on each scenario, respectively. The variance ratio test, mean value test and interval estimations are introduced in analysis of the results. A group of indices are defined to evaluate the algorithms, such as Superior, Inferior, Equivalent and Equal. Comparisons of basic, MCST algorithms, Branch Exchange algorithm (BE) and Genetic Algorithm (GA) are carried out. The results show that the improved MCST based algorithm is of the best performance.Approaches to further simplifying the improved MCST are also obtained.An improved MCST based algorithms for distribution network planning considering uncertainty is put forward. The loads with uncertainty are divided into two classes, i.e., the single condition loads and the multi-condition loads. As for single condition loads, the weights of the edges are determined by the second order moments of the corresponding currents. The improved MSCT based algorithm is adopted to obtain the optimal planning. In case of the multi-condition loads existing, multi-scenario is established by making up the various possibilities of the multi-condition loads. As for each scenario, method for single condition loads planning is adopted to obtain an initial grid and the initial cost. Compensating costs under different scenarios are calculated as well. The optimal plan is the one with the minimum expectation of summation of initial cost and compensating cost. Besides, an algorithm of distribution network flexible planning based on risk assessment is also proposed.A multi-stage planning approach considering uncertainty is put forward based on improved MCST algorithm. The index of each scenario is to minimize the total cost in all stages. The number of schemes to be investigated in each stage is modified dynamically according to the convergence of the planning results. Expanding planning measures are made between the stages. The optimal plan is the one with the minimum expectation of total cost for all scenarios. Besides, the number of posibile scenarios is remarkably reduced and the efficiency is imcreased by considering the autocorrelation and cross correlation behaviour. According to the itial cost and compensating cost.The proposed approaches are tested on various example grids. The results shows the feasibility of the proposed methods.
Keywords/Search Tags:Distribution network planning, Expansion planning, Network planning considering uncertainty, Multistage network planning, Minimum-cost spanning tree algorithm, Monte-Carlo simulation, Multi-scenario
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