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A Mini-objective Coordinated Planning Method Of Distribution Network With Renewable Energy DG

Posted on:2016-10-27Degree:MasterType:Thesis
Country:ChinaCandidate:X B LuFull Text:PDF
GTID:2272330470472217Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Under the background of the energy crisis, environmental pollution and sustained growth in electricity demand, renewable energy distributed generation is widely used with its advantages of energy-saving, environmental protection, flexible. However, wind power, photovoltaic and other renewable energy DG output is random and intermittent, high permeability DG connected to the grid wouid greatly increase the uncertainty and complexity of distribution network,and would have significant impact on distribution network loss, power quality, reliability, protection, etc.. In addition, on the one hand,the development of economy and technology increase the user demand for power supply quality and reliability, etc.; on the other hand, modern intelligent distribution network, want to be able to fine active management power users, including load, DG, etc. Therefore, it is necessary to research a new scientific method for DG and distribution network frame coordinated plan.By doing so,it can give full play to the DG to improve the distribution network operation, energy conservation and environmental protection, also can improve the quality of distribution network power supply and distribution network security and the economy.This paper, based on coordinated planning of network frame with renewable energy DG as the research object, do the following work:(1) Summarize the basic characteristic of the renewable energy DG, and its influence on the distribution network. (2) According to the following problem:according to random probability model, the use of sampling methods simulate DG’s output, has resulted in a distribution network planning model of each index calculated value and actual value error greatly. In this paper, according to the temporal features using multiple scenarios, simulate the renewable energy DG output and distribution network load requirements. (3) According to the following problem: economic indicators such as distribution network investmentcost for a single goal programming model was constructed, is not conducive to give full play to the positive role of DG. Considering renewable energy DG energy conservation, environmental protection and improve the distribution network power supply quality and other aspects of benefits, from the perspective of society as a whole, the multiobjective coordinated planning model of network frame with renewable energy DG is established,with distribution network in social and economic costs, power network loss and voltage deviation rate of comprehensive minimum as objective function, the main consideration of inequality constraints such as power balance and inequality constraints such as total installed capacity of DG. (4) Due to the different physical significance between multiple targets and dimension, it is difficult to adopt a scientific method to transform multi-objective problem into single objective problem. To solve the multi-objective coordinated planning model, a solving method of multi-objective hybrid particle swarm optimization algorithm combining the entropy weight modified AHP-TOPSIS multiple attribute decision making theory has be put forward. (5) With the improved IEEE33 node distribution network as an example, this paper, compared and analysised the simulation results from several aspects, verifid the rationality and validity of the multi-objective coordinated planning model of renewable energy DG and distribution network frame and its solving method.The proposed multi-objective coordinated planning method of renewable energy DG and distribution network frame in this paper, can be used to provide theoretical support for the active power distribution network planning considering new power users, etc.,and has a certain reference significance.
Keywords/Search Tags:optimal allocation of DG, distribution network frame planning, coordinated planning, multi-objective optimization, hybrid particle swarm optimization algorithm
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