With the continuous development of Chinas national economy, urban heating develops rapidly, and heating companies continue to increase. How to realize the reasonable and efficient production of heating network has bec...With the continuous development of Chinas national economy, urban heating develops rapidly, and heating companies continue to increase. How to realize the reasonable and efficient production of heating network has become an urgent problem. In recent years, with the gradual development of comprehensive environmental management in the country, thermal power companies have used the internet information platform to carry out technical updates in order to improve system management, save energy and reduce consumption, reduce heating costs and pollution. How to make heating users enjoy heat energy most economically and appropriately has become the most prominent problem for current heating users and even social environmental protection requirements. Household heating and metering system has become the leading system of current heating system. If heating users want to control the room temperature through temperature control valves according to their own needs, they must make the whole indoor temperature reach the appropriate temperature. However, people often ignore the heat source of heat exchange station or heating station, and there are also many links that can be optimized by pipeline design and heat source reuse. Users can not only adjust the indoor temperature by adjusting the indoor regulating valve, but also adjust the function of the equipment in the station, thereby playing the role of energy saving and emission reduction. Based on this, this paper studies and analyzes the energy saving and emission reduction of urban heating for reference. Based on this, this paper will analyze the reduction of energy and emissions of urban smart warming.展开更多
The integration of solar greenhouses into smart energy systems(SESs)remains largely unexplored,despite their potential to enhance energy sharing and hydrogen production.This review investigates the role of solar green...The integration of solar greenhouses into smart energy systems(SESs)remains largely unexplored,despite their potential to enhance energy sharing and hydrogen production.This review investigates the role of solar greenhouses as active energy contributors within SESs,emphasizing their biomass waste gasification for hydrogen production and their integration into district heating and cooling(DHC)networks.A structured classification of machine learning(ML)and deep learning(DL)techniques applied in forecasting and optimizing these processes is provided.Additionally,the evolution of DHC systems is analyzed,with a focus on fifth-generation DHC(5GDHC)networks,which facilitate bidirectional energy exchange at near-ambient temperatures.The review highlights that existing studies have predominantly addressed SES advancements and ML-driven energy management without considering the contributions of solar greenhouses.A novel framework is proposed,illustrating their role as prosumers capable of exchanging electricity,hydrogen,and thermal energy within SESs.Key findings reveal that integrating solar greenhouses with SESs can enhance energy efficiency,reduce carbon emissions,and improve system resilience.Furthermore,ML-driven predictive control strategies,particularly model predictive control(MPC),are identified as essential for optimizing real-time energy flows and biomass gasification processes.This study provides a foundation for future research on the technical,economic,and environmental feasibility of integrating greenhouses into SESs.The insights presented offer a pathway toward more sustainable,AI-driven energy-sharing networks,supporting policymakers and industry stakeholders in the transition toward low-carbon energy solutions.展开更多
文摘With the continuous development of Chinas national economy, urban heating develops rapidly, and heating companies continue to increase. How to realize the reasonable and efficient production of heating network has become an urgent problem. In recent years, with the gradual development of comprehensive environmental management in the country, thermal power companies have used the internet information platform to carry out technical updates in order to improve system management, save energy and reduce consumption, reduce heating costs and pollution. How to make heating users enjoy heat energy most economically and appropriately has become the most prominent problem for current heating users and even social environmental protection requirements. Household heating and metering system has become the leading system of current heating system. If heating users want to control the room temperature through temperature control valves according to their own needs, they must make the whole indoor temperature reach the appropriate temperature. However, people often ignore the heat source of heat exchange station or heating station, and there are also many links that can be optimized by pipeline design and heat source reuse. Users can not only adjust the indoor temperature by adjusting the indoor regulating valve, but also adjust the function of the equipment in the station, thereby playing the role of energy saving and emission reduction. Based on this, this paper studies and analyzes the energy saving and emission reduction of urban heating for reference. Based on this, this paper will analyze the reduction of energy and emissions of urban smart warming.
文摘The integration of solar greenhouses into smart energy systems(SESs)remains largely unexplored,despite their potential to enhance energy sharing and hydrogen production.This review investigates the role of solar greenhouses as active energy contributors within SESs,emphasizing their biomass waste gasification for hydrogen production and their integration into district heating and cooling(DHC)networks.A structured classification of machine learning(ML)and deep learning(DL)techniques applied in forecasting and optimizing these processes is provided.Additionally,the evolution of DHC systems is analyzed,with a focus on fifth-generation DHC(5GDHC)networks,which facilitate bidirectional energy exchange at near-ambient temperatures.The review highlights that existing studies have predominantly addressed SES advancements and ML-driven energy management without considering the contributions of solar greenhouses.A novel framework is proposed,illustrating their role as prosumers capable of exchanging electricity,hydrogen,and thermal energy within SESs.Key findings reveal that integrating solar greenhouses with SESs can enhance energy efficiency,reduce carbon emissions,and improve system resilience.Furthermore,ML-driven predictive control strategies,particularly model predictive control(MPC),are identified as essential for optimizing real-time energy flows and biomass gasification processes.This study provides a foundation for future research on the technical,economic,and environmental feasibility of integrating greenhouses into SESs.The insights presented offer a pathway toward more sustainable,AI-driven energy-sharing networks,supporting policymakers and industry stakeholders in the transition toward low-carbon energy solutions.
