Optimization And Scheduling Of Integrated Energy System Based On Neural Network Terminal Sliding Mode Control Research

With the increasing global climate change and environmental problems,the re-search and application of renewable energy and clean energy technologies have become the focus of attention.In this context,integrated energy systems with sustainable en-ergy sources such as wind,solar and green methanol have received a lot of attention.However,such integrated energy systems may face many challenges in actual opera-tion.There are system frequency fluctuations,energy utilization problems,and there are safety problems of gas storage in traditional new energy to hydrogen integrated en-ergy systems,so this paper proposes an adaptive neural network terminal sliding mode control frequency regulation strategy in the scenery-fuel cell green methanol integrated energy system.Firstly,the basic principle and structure of the scenery-solid fuel cell green inte-grated energy system for methanol production are introduced,including wind and so-lar power generation system,electric hydrogen production technology,solid fuel cell technology,and methanol production technology.And the principle of adaptive neural network terminal sliding mode control strategy and its application in regulating system frequency are elaborated,and the feasibility of this control strategy is demonstrated by Liapunov function.Secondly,in the capacity optimization configuration of the integrated energy sys-tem,in order to verify the advantages of the scenery-solid fuel cell green methanol system,the wind speed,sunshine radiation,and load are used as the case inputs,and the total system cost is minimized as the objective function,and the proposed hybrid op-timization algorithm of krill swarm algorithm and improved genetic algorithm is used to optimize the configuration of the green methanol integrated energy system,and the results are analyzed and found by:The green methanol production using scenery-solid fuel cell has the lowest annual investment construction cost The results were analyzed and found that the green methanol system using scenery-solid fuel cells has the low-est annual investment and construction cost,and improves the energy utilization rate.Further,we analyzed and compared the daily operation of the green methanol system with the green hydrogen system under a typical day in Northwest China,and although the green methanol system cost more to operate,the revenue from selling materials increased and absorbed 116.4m³of CO₂.Finally,this paper introduces an adaptive neural network terminal sliding mode control strategy to address the traditional scheduling control strategy that shows low adaptability when facing different operating conditions and demands,which can show high flexibility in power allocation and scheduling of the integrated energy system and help improve the operating efficiency and reliability of the system.The experimental results comparing with the traditional control strategy show that the integrated energy system of scenery-fuel cell green methanol production increases the daily methanol production and reduces the amount of abandoned scenery at the same time.