Modeling Simulation And Operational Optimization Control Of Smart City Heating System

In the context of energy production and consumption transformation,the technology of city heating system need to be further improved for multi-source networking and multi-energy complement.At the level of system engineering integration,the scale,complexity and diversity are further increased,and the scientific and the accurate of decision-making in the production process arc significantly required.This paper aims to establish a "source-network-load-storage" simulation model for the whole process of thermal energy production,distribution and consumption of the smart city heating system in computer system.Aiming at the safety,economy,balance and environmental protection of the heating system,the key technology research and software development of the operational optimization control of the heating system based on the simulation model is carried out to support the intelligent upgrading of the heating system.The main work of this paper is as follows:1)On the network side of the heating system,the "mechanism modeling +identification correction" heating system modeling and simulation method was proposed.Based on the graph theory,the mechanism model of the complex heating system with multi-source and complementary operation is established.The real-time data collected by the heating system are used to correct the resistance coefficient of the heating pipe so that the simulation model can match and map the operation characteristics of the physical heating network.2)On the load side of the heating system,based on the meteorological information and the historical data of heating load,several machine learning algorithms are comparative analysed for load forecasting.An online machine learning method for load forecasting of heating station was proposed.3)Based on the simulation of the whole process of "source-network-load-storage" in the heating system,a prediction method of heating system modeling based on MILP is proposed.Furthermore,a multi-level operational control technology architecture for heating system based on real-time optimization and model predictive control is proposed.4)Developed the software for modeling simulation and Operational optimization of heating system,and set up the hardware environment for the software.The practical application for the intelligent heating demonstration area of a large heating company in our country shows that the technology and method proposed in this paper are effective and feasible,and it can be used to meet the system requirements of the supply and demand balance with multiple constraints.Operational costs and environmental benefits can be optimized.