Modelling, Simulation,and Energy Management For Terminal Integrated Energy System

The necessity to alleviate the contradictions between energy supply and demand,and increase energy efficiency of terminal integrated energy system requires more effective and efficient energy management methods.In this paper,based on simulating the model of CCHP and intelligent building,the hierarchical framework with distributed and predictive dynamic thermal model control algorithm is used to optimize the operational efficiency of source-side and the load-side.Therefore,modeling,simulation and energy management of the terminal integrated energy system has launched thorough research in this article,the main work is as follows:(1)An identification algorithm based approach was proposed to provide a simplified model for IES with microturbine,with respect to system order estimation and key parameter acquisition and model verification.According to the measurable input and output signals of IES,a black-box model is established to characterize the interaction among different energy subsystems.The developed method was tested by using numerical simulations of IES and hardware experiments in Capstone C30 microturbine.(2)A dynamic model to simulate heating/cooling energy consumption for a building was proposed.The model consists of several transient energy balance equations for external walls and internal air,in which the convective heat transfer,conductive heat transfer and heat storage in the heat transfer process are considered.The proposed model has been implemented utilizing the Simulink/MATLAB platform.Then,a MPC based scheduling method for the building microgrid considering the dynamic thermal characteristics of the building was proposed.The MPC method aims to minimize the total energy consumption of the building microgrid by combining the model predictive and the short-term control,and guarantees the customer temperature comfort level at the same time.(3)Based on the dynamic model,a hierarchical framework with distributed and predictive dynamic thermal model control algorithm for each building is proposed.Two objectives,namely minimizing the operating cost and reducing the peak-valley demand difference,are integrated into the framework.At the client level,the predicted results in each rolling prediction horizon,i.e.,the electricity cost with penalty factor,the electric power of each individual building and the active power output of photovoltaic station,are uploaded to the master level.At the master level,an online optimization algorithm is further presented in each rolling control horizon to reduce the peak-valley demand difference and minimize the operating cost of the urban complex.With rolling optimization in each control horizon at the master level,optimal schedules are obtained for each controllable electrical load of each building in the urban complex.