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Dynamic State Estimation Of Electric-gas-heating Integrated Energy Network

Posted on:2021-09-01Degree:MasterType:Thesis
Country:ChinaCandidate:Y L PanFull Text:PDF
GTID:2532306917483914Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Integrated energy system (IES) is an important part of current energy revolution.In order to achieve the coordinated control and unified scheduling of the integrated energy system,it is necessary to build a new smart grid energy management system (EMS) for the integrated energy system.As the foundation and core of EMS system,state estimation provides essential data base for dispatcher power flow,security and stability analysis and other subsequent operations.However,the traditional state estimation method based on power system is not suitable for the energy development trend of multi energy flow coupling.Electricity,gas and district heating networks are the most widely developed energy networks in the current integrated energy system,therefore,it is of great significance for integrated energy system to construct the state estimation method of electric-gas-heating coupling network.Based on the above background,this thesis develops some research works as follows:(1) Considering the characteristics of different networks,the state estimation method based on electric network is extended to natural gas network and district heating network.This thesis gives the calculation methods of the state equation and measurement equation in the state estimation of these two networks,proposes the quasi-dynamic state estimation method of district heating network.This method not only guarantees the dynamic state estimation results,but also improves the efficiency of the algorithm,which lays a foundation for the construction of the state estimation method of electric-gas-heating coupling network.(2) Taking power system as an example,the optimization of energy system state estimation algorithm is studied.Firstly,the similar day algorithm and data preprocessing algorithm are used to optimize the power system daily load forecasting method based on XGBoost algorithm,and a power system state prediction method based on adaptive hybrid prediction is proposed by combining Holt two-parameter exponential smoothing method.At the same time,sage-husa adaptive noise simulator was introduced to construct the noise of predicted state values.An improved Kalman filter power system state estimation method based on adaptive mixed prediction is proposed.The research results can be directly extended to the state estimation of natural gas network and district heating network.(3) The coupling relationship and interaction between different network in the integrated energy network are studied.According to the different dynamic characteristics of different networks,a distributed state estimation method based on multi-time scale for the electric-gas-heating coupling network is proposed.At the same time,considering the coupling constraints between different sub-networks,a global consistent algorithm for state estimation is constructed to ensure that the state estimation results of coupled networks meet the boundary coupling constraints in different cases.Based on the above research,a combinational state estimation method of electric-gas-heat coupling network is constructed.
Keywords/Search Tags:integrated energy system, electric-gas-heat coupling network, state estimation, Kalman filtering
PDF Full Text Request
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