Research On Probabilistic Optimal Energy Flow Analysis Of Integrated Electricity And Natural Gas Systems Based On Decoupling Technology

Integrated electricity and natural gas system(IEGS)is considered to be a promising energy supply mode because of its high efficiency and flexibility.With the widespread use of gas-fired units and power to gas(P2G)devices,the coupling between the power system and the natural gas system has become increasingly stronger,which enables uncertain factors such as power/natural gas load and output of intermittent energy to have an impact on the subsystem.It can be transmitted to the other subsystem through the coupling devices,which in turn brings huge challenges to the planning and optimized operation of the interconnected system.Therefore,it is necessary to conduct research on the probabilistic optimal energy flow analysis of IEGS,so as to quantify the impact of uncertain factors on the operating characteristics,and to provide scientific reference information for planning and optimal operation of IEGS.The dissertation is supported by the national key R&D plan “Wind/PV Power Forecasting Technology and Application to Promote Renewable Energy Consumption,No.2018YFB0904200” and the supporting project of State Grid Co.,Ltd.,No.SGLNDKOOKJJS1800266.The following researches are carried out on three aspects of deterministic energy flow analysis,probabilistic energy flow analysis,and probabilistic optimal energy flow analysis:(1)Propose a deterministic energy flow analysis method with decoupling for IEGS.The existing research rarely considers the thermodynamic process in the natural gas system,which makes it difficult to accurately simulate the operating state of IEGS.Therefore,a deterministic energy flow analysis method with decoupling for IEGS considering the thermodynamic process is proposed.Based on the differential model of the natural gas pipeline,a lumped parameter model of the pipeline that takes into account the temperature distribution characteristics of natural gas is established,and the mathematical model of the compressor pressurization process is constructed according to the basic theory of thermodynamics,and then the energy flow model considering the thermodynamic process is built.Aiming at the problems of the sensitivity and convergence of the Newton-Raphson method,an energy flow calculation method based on topology decoupling is proposed.The topology decoupling algorithm is used to decompose the natural gas system into radial networks and a non-radial network.For radial networks,forward-flow calculation method and forward-backward iteration method are proposed.Finally,the case studies are carried out through three IEGS of different scales.The results show that the proposed model can simulate the operating state of the system more accurately,and the proposed solution method has better adaptability and convergence.(2)Propose a probabilistic energy flow analysis method based on stochastic response surface method(SRSM)improved by decoupling cross-terms.For IEGS with large-scale input random variables,the existing probability analysis methods are difficult to balance calculation accuracy and efficiency.Combining the deterministic energy flow calculation method in(1),a probabilistic energy flow analysis method based on SRSM improved by decoupling cross-terms is proposed.First,use Wiener polynomial chaos to establish the functional relationship between output random variables(node voltage/pressure,etc.)and input random variables.Then the Taylor series expansion is used to decouple and simplify the cross terms in Wiener polynomial chaos,so as to overcome the shortcomings of SRSM that it is difficult to deal with high-dimensional input random variables.Based on the principle of linear independence,the optimal collocation point combination is selected to calculate the statistical information and probability distributions of the output random variables.Finally,the simulation is carried out by two IEGS.The results show that the proposed method has high accuracy,high efficiency and good applicability.(3)Propose an probabilistic optimal energy flow analysis method for IEGS considering the power-to-hydrogen coupling mode.The existing research has not directly used power to hydrogen as a way of energy conversion from electricity to natural gas in IEGS,which makes it impossible to fully tap the potential of P2 G devices to reduce system operating costs and accommodate renewable energy.A probabilistic optimal energy flow analysis method considering the power-to-hydrogen coupling mode is proposed.First,power-to-hydrogen model is considered as a new electricity-to-gas coupling mode for P2 G devices,and a conversion model of hydrogen and natural gas based on the principle of calorific value equivalence is established,which quantifies the hydrogen injected into IEGS from the perspective of natural gas.The uncertainties of power/natural gas load and wind power output are taken into account and the operation constraints of the electricity-gas interconnection system are considered.Then a probabilistic optimal energy flow model is established with taking the minimum sum of power generation cost,gas purchase cost and carbon emission cost as the objective function.Combining SRSM improved by cross-term decoupling in(2)and interior point method,a probabilistic optimal energy flow solution method is proposed.Finally,case studies verify the accuracy and efficiency of the proposed method,and analyzes the impact of the power-to-hydrogen coupling mode on the total operating cost of IEGS and the consumption of renewable energy.