Research On The Model And Algorithm Of Collaborative Operation Optimization For Integrated Electric Power And Natural Gas System

With the improvement of energy production cleanliness and the use of high efficiency requirements,traditional power grids face bottlenecks in renewable energy consumption and terminal energy efficiency improvement.The integrated electric power and natural gas system(IEGS)has become an important carrier for energy clean,low-carbon and high-efficiency with its multi-energy complementary and mutual benefit advantages.In this multi-energy coupling background,synergistic heterogeneous energy flow to achieve its safe and economical optimal scheduling has become the focus of technical attention in the energy field.This paper is aimed at two main bodies of IEGS,i.e.,the cross-region integrated electric power and natural gas network(IEGN)and the electricity-gas coupled energy centre(EGC-EC),from electric power network and natural gas network interaction mechanism,heterogeneous energy flow collaborative optimization operation model and solving algorithm,and then to start the research,the specific work is as follows:(1)In view of the shortcomings of existing research on energy flow algorithm and interaction mechanism analysis of the electric power network and the natural gas network,an energy flow improvement algorithm and an interaction mechanism research method based on sensitivity analysis are proposed.Using the variable substitution as a means to simplify the unified power flow model of the grid-gas network.It is proposed to use Newton’s downhill method to solve the unified power flow,which can avoid the sensitivity to the initial value selection.Based on the coupled node pressure-injection power sensitivity,the coupling mechanism analysis index of comprehensive sensitivity is proposed.Case studies shows the effectiveness of the proposed method in improving the power flow efficiency and mutual mechanism analysis.(2)Aiming at the shortcomings of the existing research on the efficient treatment of natural gas network nonlinear constraints and heterogeneous energy flow analysis,an improved IEGN day-ahead optimization scheduling method based on improved successive linearization method is proposed.Based on the energy flow power balance equation,the characteristics of different time scales of power flow and natural gas flow in energy flow scheduling are derived.In the iterative process of traditional successive linearization method,the optimal step damping factor is added,and the damping successive linearization method is proposed to solve the scheduling model.Case studies analyze the necessity of electric power scheduling considering the natural gas network’s constraints.Compared with the incremental linearization method,the proposed algorithm has the advantages of simple model and high efficiency(3)For the IEGN day-ahead optimized scheduling problem under high-scale wind power access,the wind power grid-connected power scale factor is proposed,which enables wind power modeling to reflect the correlation between wind power uncertainty and its grid-connected power.The mechanism and characteristics of wind power accommodation based on power to gas(P2G)technology under high proportion of wind power are derived,and the factors affecting P2G’s ability to enhance wind power accommodation are clearly defined.Combining the alternating direction method of multipliers(ADMM)and the stepwise acceleration penalty factor strategy proposed in this paper,a distributed collaborative solution mechanism based on the stepwise acceleration of the penalty-alternating direction method of multipliers(SAP-ADMM)is proposed.Case studies analyzes the ability of P2 G on wind power accommodation and the natural gas network’s storage characteristics in response to wind power uncertainty.It also verifies that the advantage of SAP-ADMM algorithm in avoid blindness selection of penalty factors.(4)Aiming at the deficiencies of EGC-EC versatility modeling and demand side control,the device topology relation matrix is taken as the key characterization,and the generalized steady-state power balance equation description is formed,which is convenient for computer programming.Then,based on the price elasticity and discrete selection theory,the model of energy-loaded time-space transfer characteristics under price control is established,which are considered in the EGC-EC scheduling model.In order to efficiently process the mixed integer nonlinear optimization model,a solution method based on generalized benders theory is proposed.Case studies show that the proposed model effectively reflects the multi-energy interaction characteristics on the demand side,and deeply explores the demand side optimization potential.Compared with the centralized algorithm,the efficiency of the generalized benders algorithm is verified.(5)Facing the background of market regulation relaxation,the IEGS collaborative operation and interest game framework is proposed.Based on the decomposition cooperation mechanism,the method of unifying the EGC-EC to IEGN optimization scheduling modeling is proposed.The concept of "slack energy flow" is proposed as a synergistic variable,and the cooperative operation and market game model of the electric power network and the natural gas network in IEGN is established.Based on the Nikaido-Isoda function theory,the market equilibrium state is solved,and the effectiveness of the market mechanism in mobilizing the enthusiasm of participating participants and promoting energy conservation and emission reduction is analyzed.The research results of this paper enrich the theory and method of multi-energy coupling optimization modeling and solving of electric-natural gas network,and have broad application prospects in the field of electric-natural gas collaborative optimization operation.The work was supported by the National Natural Science Foundation of China(51777077)and the Natural Science Foundation of Guangdong Province(2017A030313304).