Coordinated Modelling And Optimal Operation Of Integrated Power And Natural Gas Systems

The increasingly severe resource shortage and environmental pollution have brought great challenges to the sustainable development of energy.As a vital fuel source for power generation in the power system,natural gas has the advantages of convenient storage and low carbon emission,which makes the development of natural gas more and more important for the clean transformation of energy systems.It is reported that the global natural gas power generation has reached 625 billion k Wh in 2020,accounting for about 23% of the total global power generation.Especially in the USA and UK,gas-fired power generation has reached 39% and 34.5%respectively.Therefore,coordinated operation of the integrated power-gas systems is a feasible way to improve the economy and security of the global energy system.However,the studies on the coordinated operation of the integrated power-gas systems are still in its infancy: 1)the transient response time of the power system and the natural gas system is quite different.The dynamic modelling of natural gas systems needs to consider not only the slow dynamics of natural gas but also the energy storage characteristics of pipelines;2)most of the traditional studies adopt the isothermal assumption on the natural gas system and ignore the intense heat conduction between the natural gas system and its surroundings,which greatly affects the solution accuracy of the optimal power and gas flow;3)most of the existing stochastic optimization models of integrated power-gas system utilize parametric models to quantify the uncertainty of wind power,which seriously affects the modelling accuracy.Therefore,this dissertation investigates topics including the modelling and stochastic optimization of integrated power-gas systems,as well as non-isothermal optimal power-gas flow and its convex relaxation technology,to provide theoretical basis for the optimal operation of integrated power-gas systems.The main innovations are summarized as follows:1.This dissertation proposes a novel mixed-integer linear programming based dynamic modelling method of integrated power and gas systems.Firstly,the governing equations of gas flow in partial differential form are transformed into a set of algebraic equations by the fully implicit finite difference method with second-order accuracy in both time and space.Secondly,the nonconvex quadratic constraints are reformulated into bilinear constraints based on the basic equations of gas flow,and convex envelopes are implemented to relax these bilinear constraints into a set of linear constraints.Then,a bound tightening algorithm based on variable partition is proposed to improve the accuracy of the integrated power and gas system model.The bound tightening algorithm introduces disaggregated variables and binary variables to guarantee the tightness of the relaxation in each partition.Finally,the dynamic optimal power and gas flow model can be obtained by coupling the established dynamic natural gas flow model and DC power flow model.The established dynamic optimal power-gas flow model can well describe the dynamic process of the natural gas system and can be efficiently solved by optimization software.2.This dissertation presents a non-isothermal optimal power and gas flow model.On the basis of the quantitative analyses of the energy conservation equation,the partial differential terms,which account for less than 1% of the weight,are neglected to further simplify the energy conservation equation with complex partial differential form.With the aid of the fully implicit finite difference method and the laws of thermodynamics,an algebraic non-isothermal gas flow model is established to account for natural gas temperature change in the natural gas transmission system.Coupling the DC power flow model with the non-isothermal gas flow model,the optimal power and gas flow model is formulated as a nonlinear programming problem which can be solved by the interior point method.To speed up the convergence and improve the solution quality of the interior point method,a Newton-Raphson method-based start point initialization scheme is developed to generate a set of initial points as a warm start,which is close to the optimal solution of optimal power and gas flow problem and strictly satisfies the operation constraints of integrated power and gas systems,improving the computational efficiency and solution quality of the model.3.This dissertation proposes a novel convex non-isothermal optimal power and gas flow model based on model simplification and convex relaxation techniques.Firstly,a simplified pipeline thermal model consisting of only bilinear constraints is established to capture temperature changes of natural gas,which avoids the mathematical complexity of energy conservation equation.By introducing the fully implicit finite difference method,the basic equations of gas flow in partial differential form are discretized to establish an algebraic non-isothermal gas flow model.Secondly,convex envelopes are employed to relax the cubic and bilinear constraints into a set of linear constraints.Then,a sequential bound tightening algorithm is developed to progressively shrink the variable bounds of mass flow rate,which significantly improve the tightness of the relaxation.The proposed bound tightening algorithm performs superior performance in terms of computational efficiency since all optimal power and gas flow models are linear in each iteration.4.This dissertation develops a N-1 security-constrained stochastic scheduling model of integrated power and gas system.The wind power uncertainty is modelled by a representative scenario set based on Monte Carlo simulation and scenario reduction method.To address the nonconvexity and nonlinearity of the momentum equation,Mc Cormick envelopes is utilized to transform the constraints with bilinear terms to a set of linear constraints.The fully implicit finite difference method with high accuracy even for large time step and limited pipeline subdivision is adopted to discretize the partial difference equations in time and space.Finally,the proposed stochastic model for N-1 security-constrained scheduling problem is formulated as a mixed-integer linear programming problem.The established coordinated scheduling model can assist integrated gas and electricity network operators such as grid operators to minimize the expected operation cost in the presence of wind power uncertainty.