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Research On Incremental Distribution Network Optimization Planning Method Considering Multi-agent Benefits

Posted on:2021-05-07Degree:MasterType:Thesis
Country:ChinaCandidate:Y ZhangFull Text:PDF
GTID:2392330629986868Subject:Electric power system and its automation
Abstract/Summary:PDF Full Text Request
In recent years,the Chinese government has issued a series of policies to encourage social capital to invest in and operate incremental distribution network businesses,speeding up the development of the distribution network.A large amount of social capital is incorporated into the incremental distribution network to compete for market interests.However,due to factors such as the market management structure and power quality of the incremental distribution network,uncertainties such as investment,pre-construction,and operation and maintenance cannot be ignored.The traditional method of uniformly planning the distribution network by the grid company is no longer applicable to the problem of distribution network planning in the case of new power reform.How to make the incremental distribution network fully consider multi-agent market behavior and multi-operation mode on the spot and realize the optimal planning of distributed generations and configuration of the incremental distribution network is a scientific problem that needs to be solved urgently.In this paper,the power load forecast of incremental distribution network,the modeling of power and energy balance,and the modeling and solving of distributed generations optimization planning problems are studied.The specific content is as follows:Firstly,in view of the future power consumption mainly in the industrial and commercial sectors,supplemented by residential,tourism,cultural,exhibition and other industries,that is,the rapid growth and diversification of consumer power demand,according to the nature of land use within the planning area of the pilot area,The land area is based on the energy consumption characteristics of the end-users of the incremental distribution network,and the linear and non-linear correlation between the power load and various related factors is considered to establish a power load prediction model.By processing the characteristics of historical load data and referring to the selected relevant load density indicators,further forecasting of the saturated load of the prospects in each block is carried out.Secondly,considering the uncertainty,intermittent and multi-energy complementary characteristics of distributed power sources such as photovoltaic generators and wind turbines,the balance factor and peak-cutting effect of energy storage equipment are considered,and the demand side response is combined to minimize the scheduling cost.With the minimum contract energy deviation and the maximum profit and profit as the objective function,the power and energy balance model under the incremental distribution network is established,and the power balance and energy balance analysis methods of the incremental distribution network are studied.Finally,in order to address the issues of multi-investment entities joining the incremental distribution network construction management and different interest targets,the incremental coverage of each entity is constructed based on the relationships between multi-stakeholders such as DG operators,distribution network investment companies,and power users.Distribution network planning model.Jointly consider the issues of incremental distribution network multiple income entities and increased uncertainties after the DG is connected to the grid.By considering the losses caused by fluctuations in the distribution network investment company’s objective function,it is proposed to take into account the increase of multi-agent benefits DG optimization planning method for quantity distribution network.Compared with scenarios that do not consider overall benefits,and only take their own revenue as the optimization goal.Formulate an optimized planning plan for a typical regional incremental distribution network,and carry out strategic verification research based on the regional typical incremental distribution network.
Keywords/Search Tags:Incremental distribution network, Multi-agent, Power load forecasting, Electric power balance, DG Optimized planning
PDF Full Text Request
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