The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of ...The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of low-carbon building design.Therefore,the use of intelligent energy management system is very necessary.The purpose of this paper is to explore the design optimization of low-carbon buildings based on intelligent energy management systems.Based on the proposed quantitative method of building carbon emission,this paper establishes the quota theoretical system of building carbon emission analysis,and develops the quota based carbon emission calculation software.Smart energy management system is a low-carbon energy-saving system based on the reference of large-scale building energy-saving system and combined with energy consumption.It provides a fast and effective calculation tool for the quantitative evaluation of carbon emission of construction projects,so as to realize the carbon emission control and optimization in the early stage of architectural design and construction.On this basis,the evaluation,analysis and calculation method of building structure based on carbon reduction target is proposed,combined with the carbon emission quota management standard proposed in this paper.Taking small high-rise residential buildings as an example,this paper compares and analyzes different building structural systems from the perspectives of structural performance,economy and carbon emission level.It provides a reference for the design and evaluation of low-carbon building structures.The smart energy management system collects user energy use parameters.It uses time period and time sequence to obtain a large amount of data for analysis and integration,which provides users with intuitive energy consumption data.Compared with the traditional architectural design method,the industrialized construction method can save 589.22 megajoules(MJ)per square meter.Based on 29270 megajoules(MJ)per ton of standard coal,the construction area of the case is about 8000 m2,and the energy saving of residential buildings is 161.04 tons of standard coal.This research is of great significance in reducing the carbon emission intensity of buildings.展开更多
Steering control for an autonomous underwater glider (AUG) is very challenging due to its changing dynamic char- acteristics such as payload and shape. A good choice to solve this problem is online system identifica...Steering control for an autonomous underwater glider (AUG) is very challenging due to its changing dynamic char- acteristics such as payload and shape. A good choice to solve this problem is online system identification via in-field trials to capture current dynamic characteristics for control law reconfiguration. Hence, an online polynomial estimator is designed to update the yaw dynamic model of the AUG, and an adaptive model predictive control (MPC) controller is used to calculate the optimal control command based on updated estimated parameters. The MPC controller uses a quadratic program (QP) to compute the optimal control command based on a user-defined cost function. The cost function has two terms, focusing on output reference tracking and move suppression of input, respectively. Move-suppression performance can, at some level, represent energy-saving performance of the MPC controller. Users can balance these two competitive control performances by tuning weights. We have compared the control performance using the second-order polynomial model to that using the filth-order polynomial model, and found that the tbrmer cannot capture the main characteristics of yaw dynamics and may result in vibration during the flight. Both processor-in-loop (PIL) simulations and in-lake tests are presented to validate our steering control performance.展开更多
基金supported by“Key Technology Research on Operational Performance Improvement of the Green Building”(2020YFS0060)Key Project of Science and Technology Department of Sichuan Province+2 种基金supported by“Creative VR Teaching and Learning Research Based on‘PBL+’and Multidimensional Collaboration”(JG2021-721)“Reform in the Mode and Practice of Architecture Education with the Characteristics of Geology”(JG2021-672)Education Quality and Teaching Reform Project of Higher Education in Sichuan Province in 2021–2023.
文摘The construction of relevant standards for building carbon emission assessment in China has just started,and the quantitative analysis method and evaluation system are still imperfect,which hinders the development of low-carbon building design.Therefore,the use of intelligent energy management system is very necessary.The purpose of this paper is to explore the design optimization of low-carbon buildings based on intelligent energy management systems.Based on the proposed quantitative method of building carbon emission,this paper establishes the quota theoretical system of building carbon emission analysis,and develops the quota based carbon emission calculation software.Smart energy management system is a low-carbon energy-saving system based on the reference of large-scale building energy-saving system and combined with energy consumption.It provides a fast and effective calculation tool for the quantitative evaluation of carbon emission of construction projects,so as to realize the carbon emission control and optimization in the early stage of architectural design and construction.On this basis,the evaluation,analysis and calculation method of building structure based on carbon reduction target is proposed,combined with the carbon emission quota management standard proposed in this paper.Taking small high-rise residential buildings as an example,this paper compares and analyzes different building structural systems from the perspectives of structural performance,economy and carbon emission level.It provides a reference for the design and evaluation of low-carbon building structures.The smart energy management system collects user energy use parameters.It uses time period and time sequence to obtain a large amount of data for analysis and integration,which provides users with intuitive energy consumption data.Compared with the traditional architectural design method,the industrialized construction method can save 589.22 megajoules(MJ)per square meter.Based on 29270 megajoules(MJ)per ton of standard coal,the construction area of the case is about 8000 m2,and the energy saving of residential buildings is 161.04 tons of standard coal.This research is of great significance in reducing the carbon emission intensity of buildings.
基金supported by Beihang University and Institution of China Academy of Aerospace Aerodynamics
文摘Steering control for an autonomous underwater glider (AUG) is very challenging due to its changing dynamic char- acteristics such as payload and shape. A good choice to solve this problem is online system identification via in-field trials to capture current dynamic characteristics for control law reconfiguration. Hence, an online polynomial estimator is designed to update the yaw dynamic model of the AUG, and an adaptive model predictive control (MPC) controller is used to calculate the optimal control command based on updated estimated parameters. The MPC controller uses a quadratic program (QP) to compute the optimal control command based on a user-defined cost function. The cost function has two terms, focusing on output reference tracking and move suppression of input, respectively. Move-suppression performance can, at some level, represent energy-saving performance of the MPC controller. Users can balance these two competitive control performances by tuning weights. We have compared the control performance using the second-order polynomial model to that using the filth-order polynomial model, and found that the tbrmer cannot capture the main characteristics of yaw dynamics and may result in vibration during the flight. Both processor-in-loop (PIL) simulations and in-lake tests are presented to validate our steering control performance.