Optimal Dispatch Of Integrated Energy Campus Microgrids Considering The Time-delay Of Pipelines

The technology of Integrated Energy Campus Microgrids(IECM)is an important aspect of the practical application of multi-energy complementary and coordinated utilization technology.The power,natural gas,and cooling/heating sub-energy systems in the IECM have significantly different dynamics,which makes the operation of the IECM have the characteristics of multiple time scales.Therefore,Coordinated and optimized energy management decisions of IECMs need to consider the time-delay in multiple sub-energy systems.At the same time,At the same time,natural gas and cooling/heating systems have greater inertia than power systems,which can convert electricity that cannot be stored for a long time into other forms of energy storage,thereby improving the flexibility of IECM operation and the utilization of new energy.In view of this,this paper studies the dynamic models of the natural gas system and the cooling/heating system,as well as the coupling characteristics between the sub-energy systems,modeling the integrated energy system considering the time-delay of pipelines,and solving for various optimal energy flows,Finally,The State Space Approximate Dynamic Programming(SSADP)method is used to solve the uncertain optimal dispatch problem of IECM considering the timedelay of pipelines.An optimal dispatch model for IECMs is proposed,which considered the time-delay of energy transmission in cooling/heating and gas pipelines.In this model,the electricity and natural gas purchase cost of the IECM was made into an objective function,Partial differential equations(PDEs)were used to describe the time-delay in pipelines.Orthogonal collocation on finite elements(OCFE)in the two-dimensional domain was used to transform PDEs into algebraic equations(AEs).Several linearization methods,including piecewise linearization and the big M method,were used to transform the initial mixed-integer nonlinear programming(MINLP)model into a mixed-integer linear programming(MILP)model to reduce computational complexity.A IECM is taken as an example,OCFE was compared with the firstorder finite difference method,and simulation results were used to demonstrate the accuracy and efficiency of the proposed algorithm.The impact of the time-delay of pipelines on IECM was analyzed through comparison with a steady-state model.New energy source is the main component of distributed energy in the IECM.Due to the uncontrollability of light in nature,the typical new energy photovoltaic and solar thermal output has strong intermittent and randomness,which puts forward higher requirements for the optimal dispatch.Therefore,based on the original optimal dispatch model of IECM considering the time-delay of pipelines,considering the stochastic fluctuation of the output of Photovoltaic stations and solar thermal stations,the IECM uncertain optimal dispatch model was established,and the state-space approximate dynamic programming algorithm was adopted.First,a series of random scenes are generated according to the predicted scenes,and the deterministic optimization dispatch problems corresponding to these scenes are solved one by one to generate a typical state space,then,based on the similarity index and Markov chain,the approximate value function of the typical state space is obtained through traversal,Finally,we solved each period’s decoupled model successively.Test results on an IECM demonstrate that the proposed model and algorithm are correct and efficient,the obtained optimal dispatch scheme can meet the operation requirements of the IECM under the stochastic fluctuation of new energy.