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Network Reconfiguration And Island Partition For Distribution Network In Regional Integrated Electricity And Gas System

Posted on:2021-02-06Degree:MasterType:Thesis
Country:ChinaCandidate:B D ChenFull Text:PDF
GTID:2392330611467274Subject:Power system and its automation
Abstract/Summary:PDF Full Text Request
With improvement of terminal energy efficiency goals and increased demand for distributed energy consumption,the traditional distribution network is now gradually transforming into a multi-energy coupling,coordinated and efficient integrated energy system.The integrated electricity and gas system(IEGS)has drawn lots of attentions given physical properties of electrical energy and natural gas presents complementary.The development of IEGS has brought many opportunities and also challenges to all aspects of the active distribution network.This paper focuses on the distribution network reconfiguration and island partition in the regional integrated electricity and gas system.Main contents of the work are as follows:Firstly,a basic overview and the mathematical modeling of regional IEGS are provided which lays a theoretical foundation for the subsequent study on the network reconfiguration and island partition research of the distribution network.It introduces basic structure and composition of IEGS,as well as complementary and dependent characteristics.Mathematical modeling of common energy production,conversion and storage equipment within IEGS are established.From mathematical modeling perspective,IEGS are divided into three sub-modules of power network subsystem,natural gas network subsystem and energy hub for modeling separately.Secondly,aiming at regional IEGS distribution network reconfiguration,the conditional value-at-risk theory(CVaR)is introduced and used to describe the potential risks to dispatch operation due to source and load uncertainty of regional IEGS.Based on this,a distribution network reconfiguration model with considering multi-energy flow constraints is established.It uses branch flow model to build up distribution network modeling,then linearizes the voltage drop constraint by relaxing the node v oltage variable.It adopts radial constraint linear expression of virtual power flow,relaxes the strongly non-convex natural gas network model into a mixed integer second-order cone programming model by using second-order cone relaxation.Most importantly,the improved sequential cone programming method is used to ensure tightnessof the relaxation.Results of the simulation show that the proposed model takes risks brought by the fluctuation of source and load into account,reduces total cost of system operation,and the proposed algorithm can effectively improve the solution efficiency.Finally,to solve island partition in regional IEGS distribution network,considering uncertainty of renewable energy and electricity,gas and heat load,with the goal of optimizing the island partitioning scheme,this paper discusses the island partition of integrated energy micro-grid and establishes a robust island partition model based on continuous operation of island.In this model,the shortest notification time constraint against the blackout is taken as the target penalty term,so that a certain response time is reserved for the load to the greatest extent.Meanwhile,it avoids repeated access and removal to island load caused by source power and load fluctuation.The robust discrete optimization model transforms uncertain constraints into certain constraints,therefore,a mixed integer linear programming model is constructed.This uses global robust tuning coefficient to improve the conservativeness of robust optimization.The economics and operability of the islanding scheme are well balanced to meet different decision-making needs.Simulation results validates the effectiveness of proposed island partition,as well as the necessity and effectiveness of robust island partition.
Keywords/Search Tags:integrated energy system, distribution network, network reconfiguration, island partition, conditional value at risk(CVaR), robust discrete optimization
PDF Full Text Request
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