Research On Multi-objective Energy-saving And Low-carbon Operation Optimization Of Multi-source Coordinated Heating System In An Airport

Under the background of the “dual carbon” goal and “four-type airport”,the multi-source coordinated heating system provides a feasible direction for the energy saving and carbon reduction development of airports.However,the structure of multi-source coordinated heating system is complex and the existing system operation and control strategies fail to fully exploit their energy saving and carbon reduction potential,resulting in low system performance.To this end,this paper takes the multi-source coordinated heating system of an airport as the research object,and develops the research from three aspects: system demand-side heat load prediction,system carbon emission and energy consumption modeling,and system multi-objective energy-saving and low-carbon operation optimization,which are mainly as follows:Firstly,the heating load prediction model of the heating area of the heating system is developed;For the characteristics of the building heating load with strong uncertainty and complex influencing factors,the heating area is zoned,the heating load is decomposed using complete ensemble empirical mode decomposition with adaptive noise algorithm combined with fuzzy entropy,and maximal information coefficient combined with distance correlation coefficient is used for feature selection;The heap-based optimizer algorithm is used to optimize the radial basis function neural network and the gate recurrent unit neural network respectively,and the two are combined to develop a hybrid heating load prediction model.The results show that the proposed model has better results than other prediction models on five performance evaluation metrics,ant its mean absolute percentage error reaches 1.06% with high prediction accuracy and strong robustness and generalization ability,which can provide accurate data support for matching supply and demand in heating system operation optimization.Secondly,the equipment energy consumption model and carbon emission model of the heating system are developed.The energy-consuming equipments of the system mainly include heat pump units,gas boilers,blowers and pumps;Based on the mechanism model of each kind of equipment,the energy consumption of each kind of equipment is modeled by radial basis function neural network optimized with heap-based optimizer algorithm,and the operational carbon emission of the heating system is modeled by carbon emission factor method.The results show that the developed system equipment models have high accuracy and robustness,and can provide an effective theoretical and data basis for the establishment of the heating system optimization model.Finally,a multi-objective energy-saving and low-carbon operation optimization of the multi-source coordinated heating system is conducted.With the highest operational energy efficiency,lowest operational carbon emission and lowest operational cost as the optimization objectives,the system optimization model is developed with the system heat balance constraints,equipment operation constraints and energy consumption and carbon emission constraints as the associated constraints;And an improved parallel multi-objective artificial immune algorithm is proposed for the model solution according to the model characteristics.The results show that the proposed optimization algorithm can effectively realize the energy-saving,low-carbon and economically coordinated optimization of the heating system,and the energy efficiency of the system is improved by 26.55%,the carbon emission is reduced by12.12% and the operation cost is reduced by 12.33% after the optimization.Moreover,compared with other multi-objective optimization algorithms,the proposed algorithm has better optimization effect and lower computational complexity.In summary,the demand-side heating load prediction model and multi-objective operation optimization method of the multi-source coordinated heating system proposed in this paper can provide valuable theoretical guidance and application reference for the energy-saving,low-carbon,economic and efficient optimized operation of the airport energy system,and help promote the construction of the“four-type airport” and the realization of the “dual carbon” goal.