As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inve...As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inverter-based thermostatically controlled load(ITCL)clusters to provide virtual inertia support to the power grid.However,ITCL clusters exhibit significant discrete response characteristics,which precludes the direct integration of load-side inertia support into the synchronous unit side.To address this issue,this paper elaborates on the existing technical framework and analyzes the underlying causes of the problem.It proposes a timestamp allocation mechanism for ITCL cluster control instructions,ensuring that many ITCL terminals can be triggered at staggered times,thereby allowing the load cluster power to adhere to the inertia analog control law at any moment.Building on this foundation,the paper further examines the impact of the inertia response delay of ITCL clusters,which is based on centralized frequency regulation,on the stability of the power system.A design scheme for inertia analog control parameters is proposed,taking into account dual constraints,frequency stability and load cluster regulation capacity.Finally,the feasibility and applicability of the proposed mechanism and parameter design scheme are investigated through simulations conducted via MATLAB/Simulink.展开更多
Innovatively addressing the challenge of difficult winter starts for vehicles in northern regions,this study has developed a Thermally Controlled Preheating Engine Activation System.This system ingeniously integrates ...Innovatively addressing the challenge of difficult winter starts for vehicles in northern regions,this study has developed a Thermally Controlled Preheating Engine Activation System.This system ingeniously integrates a thermal insulation kettle,an efficient water pump,precision valves,and temperature sensors,all closely linked with the engine’s coolant circulation system.In cold environments,the system automatically initiates a preheating mechanism by circulating and heating the coolant,significantly enhancing engine startup efficiency and reducing wear caused by cold starts.The anticipated outcome of this research is to substantially improve the operational reliability of vehicles in cold climates,extend their lifespan,promote energy conservation and emissions reduction,and drive the automotive industry towards greener,more efficient,and intelligent technologies,thus laying a solid foundation for industry upgrades and transformation.展开更多
Accurate and efficient integration of the equations of motion is indispensable for molecular dynamics(MD)simulations.Despite the massive use of the conventional leapfrog(LF)integrator in modern computational tools wit...Accurate and efficient integration of the equations of motion is indispensable for molecular dynamics(MD)simulations.Despite the massive use of the conventional leapfrog(LF)integrator in modern computational tools within the framework of MD propagation,further development for better performance is still possible.The alternative version of LF in the middle thermostat scheme(LFmiddle)achieves a higher order of accuracy and efficiency and maintains stable dynamics even with the integration time stepsize extended by several folds.In this work,we perform a benchmark test of the two integrators(LF and LF-middle)in extensive conventional and enhanced sampling simulations,aiming at quantifying the time-stepsizeinduced variations of global properties(e.g.,detailed potential energy terms)as well as of local observables(e.g.,free energy changes or bondlengths)in practical simulations of complex systems.The test set is composed of six chemically and biologically relevant systems,including the conformational change of dihedral flipping in the N-methylacetamide and an AT(AdenineThymine)tract,the intra-molecular proton transfer inside malonaldehyde,the binding free energy calculations of benzene and phenol targeting T4 lysozyme L99A,the hydroxyl bond variations in ethaline deep eutectic solvent,and the potential energy of the blue-light using flavin photoreceptor.It is observed that the time-step-induced error is smaller for the LFmiddle scheme.The outperformance of LF-middle over the conventional LF integrator is much more significant for global properties than local observables.Overall,the current work demonstrates that the LF-middle scheme should be preferably applied to obtain accurate thermodynamics in the simulation of practical chemical and biological systems.展开更多
Molecular-dynamics(MD)simulations have been performed for the growth of a spherical methane-hydrate nano-crystallite,surrounded by a supersaturated water–methane liquid phase,using both a hybrid and globalsystem ther...Molecular-dynamics(MD)simulations have been performed for the growth of a spherical methane-hydrate nano-crystallite,surrounded by a supersaturated water–methane liquid phase,using both a hybrid and globalsystem thermostatting approach.It was found that hybrid thermostatting led to more sluggish growth and the establishment of a radial temperature profile about the spherical hydrate crystallite,in which the growing crystal phase is at a higher temperature than the surrounding liquid phase in the interfacial region,owing to latent-heat dissipation.In addition,Onsager’s-hypothesis fluctuation–dissipation analysis of fluctuations in the number of crystal-state water molecules at the interface shows slower growth.展开更多
In this paper, single-walled carbon nanotubes （SWCNTs） are studied through molecular dynamics （MD） simulation. The simulations are performed at temperatures of 1 and 300K separately, with atomic interactions chara...In this paper, single-walled carbon nanotubes （SWCNTs） are studied through molecular dynamics （MD） simulation. The simulations are performed at temperatures of 1 and 300K separately, with atomic interactions characterized by the second Reactive Empirical Bond Order （REBO） potential, and temperature controlled by a certain thermostat, i.e. by separately using the velocity scaling, the Berendsen scheme, the Nose-Hoover scheme, and the generalized Langevin scheme. Results for a （5,5） SWCNT with a length of 24.5 nm show apparent distortions in nanotube configuration, which can further enter into periodic vibrations, except in simulations using the generalized Langevin thermostat, which is ascribed to periodic boundary conditions used in simulation. The periodic boundary conditions may implicitly be applied in the form of an inconsistent constraint along the axis of the nanotube. The combination of the inconsistent constraint with the cumulative errors in calculation causes the distortions of nanotubes. When the generalized Langevin thermostat is applied, inconsistently distributed errors are dispersed by the random forces, and so the distortions and vibrations disappear. This speculation is confirmed by simulation in the case without periodic boundary conditions, where no apparent distortion and vibration occur. It is also revealed that numerically induced distortions and vibrations occur only in simulation of nanotubes with a small diameter and a large length-to-diameter ratio. When MD simulation is applied to a system with a particular geometry, attention should be paid to avoiding the numerical distortion and the result infidelity.展开更多
The designed thermostat is based on the microcontroller featuring intelligence, programmable, environmental protection and power saving. The thermostat design is mainly composed of hardware and software design, the ha...The designed thermostat is based on the microcontroller featuring intelligence, programmable, environmental protection and power saving. The thermostat design is mainly composed of hardware and software design, the hardware includes the power supply circuit, temperature measurement circuit, humidity measurement circuit and backlight circuit; while the software design includes temperature measurement and compensation algorithm, moreover software flowchart is given as well. Finally the power supply circuit is simulated by the software of Pspice and the creative power stealing mode is verified by the simulation results. A target board is stuffed by hand with Pb-free electronic components and used to test hardware and debug software. Since the Pb-free components were used, power stealing mode is designed in hardware and temperature compensation algorithm is accomplished in software, and the thermostat is outstanding with its features of "green" and "power saving".展开更多
The paper demonstrates deep unity of classic and quantum physics at the space thermostat (ST) presence, which fulfilled all space by the temperature T0 = 2.73 K. The ST presents itself the Cosmic Microwave Background ...The paper demonstrates deep unity of classic and quantum physics at the space thermostat (ST) presence, which fulfilled all space by the temperature T0 = 2.73 K. The ST presents itself the Cosmic Microwave Background (CMB). From the main quantum position we consider the ST/CMB as the wave function carrier (“quantum background”). The paper is devoted to ST/CMB medium the classic conservation laws of mass, momentum and energy. We show the soliton like solutions of our classic model correspond to Schrodinger’s quantum solutions, demonstrate the atom hydrogen specter and other quantum peculiarities. The paper contains typical technical examples classic/ quantum simulation at the ST presence.展开更多
In this paper, the impact of limiting thermostat on the rupture event occuring in Fuel-Oil burner fuel pre-heaters＇ resistant （heat generating） wires is inspected numerically. Gaseous fuel content in the pipeline h...In this paper, the impact of limiting thermostat on the rupture event occuring in Fuel-Oil burner fuel pre-heaters＇ resistant （heat generating） wires is inspected numerically. Gaseous fuel content in the pipeline has also been issued as a possibility. Heater＇s inner temperature distributions have been simulated by an in-house MATrix LABoratory （MATLAB） script in order to understand the resistant wire exposure to high temperatures by numerous scenarios. It is concluded that the effect of fuel flowrate is not a major effect on the wires＇ fate because of the limiting thermostat co-working. The main difference between the calculations is the effect of thermostat cut off function. The numerical simulations enlightened the dominant effect of thermostat sensing delay, so the overheating event. Intolerable delay results with a quick drop in the thermal efficiency and an increased possibility on wire rupture due to overheating which means a burner malfunction. Referring to the first numerical simulation results, a distributed and reduced heat flux was implemented with the same fluid and thermodynamic properties on a revised pre-heater model with an increased heater plate. The increment, thus the reduction on the heat flux of the ribbon wires has been noted as the key for safe operation.展开更多
Heating,ventilation,and air conditioning system runtime is a crucial metric for establishing the connection between system operation and energy performance.Similar homes in the same location can have varying runtime d...Heating,ventilation,and air conditioning system runtime is a crucial metric for establishing the connection between system operation and energy performance.Similar homes in the same location can have varying runtime due to different factors.To understand such heterogeneity,this study conducted an energy signature analysis of heating and cooling system runtime for 5,014 homes across the US>using data from ecobee smart thermostats.Two approaches were compared for the energy signature analysis:(1)using daily mean outdoor temperature and(2)using the difference between the daily mean outdoor temperature and the indoor thermostat setpoint(delta T)as the independent variable.The best-fitting energy signature parameters(balance temperatures and slopes)for each house were estimated and statistically analyzed.The results revealed significant differences in balance temperatures and slopes across various climates and individual homes.Additionally,we identified the impact of housing characteristics and weather conditions on the energy signature parameters using a long absolute shrinkage and selection operator(LASSO)regression.Incorporating delta T into the energy signature model significantly enhances its ability to detect hidden impacts of various features by minimizing the influence of setpoint preferences.Moreover,our cooling slope analysis highlights the significant impact of outdoor humidity levels,underscoring the need to include latent loads in building energy models.展开更多
Demand-side flexibility is crucial to balancing supply and demand,as renewable energy sources are increasingly integrated into the energy mix,and heating and transport systems are becoming more and more electrified.Hi...Demand-side flexibility is crucial to balancing supply and demand,as renewable energy sources are increasingly integrated into the energy mix,and heating and transport systems are becoming more and more electrified.Historically,this balancing has been managed from the supply side.However,the shift towards renewable energy sources limits the controllability of traditional fossil fuel plants,increasing the importance of demand response(DR)techniques to achieve the required flexibility.Aggregators participating in flexibility markets need to accurately forecast the adaptability they can offer,a task complicated by numerous influencing variables.Based on a top-down approach,this study addresses the problem of forecasting electricity demand in the presence of flexibility from thermostatically controlled loads.We propose a hybrid model that combines data-driven techniques for probabilistic estimation of electricity consumption with a disaggregation of electricity consumption to identify the fraction of thermal loads,subject to flexibility,which is simulated by a virtual battery model.The technique is applied to a synthetic dataset that simulates the response of a European neighborhood to demand response interventions.The results demonstrate the model’s ability to accurately predict both the reduction in electricity demand during DR events and the subsequent rebound in consumption.The model achieves a mean absolute percentage error(MAPE)lower than 17.0%,comparable to the accuracy without flexibility.The results obtained are compared with a direct data-driven approach,demonstrating the validity and effectiveness of our model.展开更多
Thermostatically controlled loads(TCLs)on the demand side have been a vital energy resource in smart grids.To efficiently utilize the large-scale TCLs and enhance the flexibility of micro-community systems,this paper ...Thermostatically controlled loads(TCLs)on the demand side have been a vital energy resource in smart grids.To efficiently utilize the large-scale TCLs and enhance the flexibility of micro-community systems,this paper proposes a distributed coordinated control strategy based on the distributed model predictive control(MPC).To achieve the adaptive coordinated control among TCLs and consider user comfort constraints,a distributed dual-layer internal control strategy based on MPC is established on a scalable communication network.This strategy achieves the efficient utilization of TCLs in a distributed manner and notably improves the convergence speed through sparse network communication between neighbors.For external resource utilization of TCLs,a multi-timescale scheduling framework is proposed to realize the pre-allocation of electricity.Furthermore,the feasibility of the proposed distributed coordinated control strategy is confirmed through comparative case analysis.展开更多
Thermostatic Radiator Valves(TRVs)are a widely used technology for regulating room heating in Europe countries.Smart TRVs can provide significant energy savings,often ranging from 20–40%compared to conventional heati...Thermostatic Radiator Valves(TRVs)are a widely used technology for regulating room heating in Europe countries.Smart TRVs can provide significant energy savings,often ranging from 20–40%compared to conventional heating systems.They use sensors and algorithms to learn user behavior and optimize heating schedules accordingly.They can often be easily retrofitted to existing heating systems,making them a practical option for enhancing energy efficiency in present buildings,especially in office buildings due to their highly dynamic operational patterns.This work presents a novel human-in-the-loop control strategy for Internet of Things(IoT)-based TRVs using Deep Reinforcement Learning(DRL).A key focus of this research is enhancing the adaptability of agents’behavior by implementing a more generic and flexible Markov Decision Process(MDP)to promote policy generalization across diverse scenarios.The study explores the challenges of transferring control behaviors from simulation environments to real-world settings,examining the performance across different thermal zones and evaluating the integration flexibility of the control strategy within building systems.Real-world occupant behavior is incorporated,including dynamic comfort preferences and occupancy predictions,to better align thermostat operation with user preferences.Furthermore,this paper discusses the practical challenges encountered during implementation,including battery consumption of IoT devices,integration of occupancy detection and prediction systems,and maintenance requirements.By addressing these issues,the proposed control strategy seeks to improve the scalability and feasibility of IoT-based TRVs,thereby providing a viable solution for their widespread deployment in buildings.展开更多
Occupant-centric controls(OcC)is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building energy systems.While OcC has been used in a wide range of building applica...Occupant-centric controls(OcC)is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building energy systems.While OcC has been used in a wide range of building applications,an OcC category that has received considerable research interest is learning occupants'thermal preferences through their thermostat interactions and adapting temperature setpoints accordingly.Many recent studies used reinforcement learning(RL)as an agent for OcC to optimize energy use and occupant comfort.These studies depended on predicted mean vote(PMV)models or constant comfort ranges to represent comfort,while only few of them used thermostat interactions.This paper addresses this gap by introducing a new off-policy reinforcement learning(RL)algorithm that imitates the occupant behaviour by utilizing unsolicited occupant thermostat overrides.The algorithm is tested with a number of synthetically generated occupant behaviour models implemented via the Python APl of EnergyPlus.The simulation results indicate that the RL algorithm could rapidly learn preferences for all tested occupant behaviour scenarios with minimal exploration events.While substantial energy savings were observed with most occupant scenarios,the impact on the energy savings varied depending on occupants'preferences and thermostat use behaviour stochasticity.展开更多
As the core components of fifth-generation(5G)communication technology,optical modules should be consistently miniaturized in size while improving their level of integration.This inevitably leads to a dramatic spike i...As the core components of fifth-generation(5G)communication technology,optical modules should be consistently miniaturized in size while improving their level of integration.This inevitably leads to a dramatic spike in power consumption and a consequent increase in heat flow density when operating in a confined space.To ensure a successful start-up and operation of 5G optical modules,active cooling and precise temperature control via the Peltier effect in confined space is essential yet challenging.In this work,p-type Bi_(0.5)Sb_(1.5)Te_(3)and n-type Bi_(2)Te_(2.7)Se_(0.3)bulk thermoelectric(TE)materials are used,and a micro thermoelectric thermostat(micro-TET)(device size,2×9.3×1.1mm^(3);leg size,0.4×0.4×0.5mm^(3);number of legs,44)is successfully integrated into a 5G optical module with Quad Small Form Pluggable 28 interface.As a result,the internal temperature of this kind of optical module is always maintained at 45.7℃ and the optical power is up to 7.4 dBm.Furthermore,a multifactor design roadmap is created based on a 3D numerical model using the ANSYS finite element method,taking into account the number of legs(N),leg width(W),leg length(L),filling atmosphere,electric contact resistance(Rec),thermal contact resistance(Rtc),ambient temperature(Ta),and the heat generated by the laser source(QL).It facilitates the integrated fabrication of micro-TET,and shows the way to enhance packaging and performance under different operating conditions.According to the roadmap,the micro-TET(2×9.3×1mm^(3),W=0.3 mm,L=0.4 mm,N=68 legs)is fabricated and consumes only 0.89W in cooling mode(Q_(L)=0.7W,T_(a)=80℃)and 0.36Win heating mode(T_(a)=0℃)to maintain the laser temperature of 50℃.This research will hopefully be applied to other microprocessors for precise temperature control and integrated manufacturing.展开更多
基金supported by the Key Scientific and Technological Projects(2024KJGG27)of Tianfu Yongxing Laboratorythe Experimental Platform Open Innovation Funding(209042025003)of Sichuan Energy Internet Research Institute,Tsinghua University.
文摘As the development of new power systems progresses,the inherent inertia of power systems continues to diminish.Centralized frequency regulation,which relies on rapid communication and real-time control,can enable inverter-based thermostatically controlled load(ITCL)clusters to provide virtual inertia support to the power grid.However,ITCL clusters exhibit significant discrete response characteristics,which precludes the direct integration of load-side inertia support into the synchronous unit side.To address this issue,this paper elaborates on the existing technical framework and analyzes the underlying causes of the problem.It proposes a timestamp allocation mechanism for ITCL cluster control instructions,ensuring that many ITCL terminals can be triggered at staggered times,thereby allowing the load cluster power to adhere to the inertia analog control law at any moment.Building on this foundation,the paper further examines the impact of the inertia response delay of ITCL clusters,which is based on centralized frequency regulation,on the stability of the power system.A design scheme for inertia analog control parameters is proposed,taking into account dual constraints,frequency stability and load cluster regulation capacity.Finally,the feasibility and applicability of the proposed mechanism and parameter design scheme are investigated through simulations conducted via MATLAB/Simulink.
文摘Innovatively addressing the challenge of difficult winter starts for vehicles in northern regions,this study has developed a Thermally Controlled Preheating Engine Activation System.This system ingeniously integrates a thermal insulation kettle,an efficient water pump,precision valves,and temperature sensors,all closely linked with the engine’s coolant circulation system.In cold environments,the system automatically initiates a preheating mechanism by circulating and heating the coolant,significantly enhancing engine startup efficiency and reducing wear caused by cold starts.The anticipated outcome of this research is to substantially improve the operational reliability of vehicles in cold climates,extend their lifespan,promote energy conservation and emissions reduction,and drive the automotive industry towards greener,more efficient,and intelligent technologies,thus laying a solid foundation for industry upgrades and transformation.
基金supported by the National Natural Science Foundation of China(No.21961142017)the Ministry of Science and Technology of China(No.2017YFA0204901)。
文摘Accurate and efficient integration of the equations of motion is indispensable for molecular dynamics(MD)simulations.Despite the massive use of the conventional leapfrog(LF)integrator in modern computational tools within the framework of MD propagation,further development for better performance is still possible.The alternative version of LF in the middle thermostat scheme(LFmiddle)achieves a higher order of accuracy and efficiency and maintains stable dynamics even with the integration time stepsize extended by several folds.In this work,we perform a benchmark test of the two integrators(LF and LF-middle)in extensive conventional and enhanced sampling simulations,aiming at quantifying the time-stepsizeinduced variations of global properties(e.g.,detailed potential energy terms)as well as of local observables(e.g.,free energy changes or bondlengths)in practical simulations of complex systems.The test set is composed of six chemically and biologically relevant systems,including the conformational change of dihedral flipping in the N-methylacetamide and an AT(AdenineThymine)tract,the intra-molecular proton transfer inside malonaldehyde,the binding free energy calculations of benzene and phenol targeting T4 lysozyme L99A,the hydroxyl bond variations in ethaline deep eutectic solvent,and the potential energy of the blue-light using flavin photoreceptor.It is observed that the time-step-induced error is smaller for the LFmiddle scheme.The outperformance of LF-middle over the conventional LF integrator is much more significant for global properties than local observables.Overall,the current work demonstrates that the LF-middle scheme should be preferably applied to obtain accurate thermodynamics in the simulation of practical chemical and biological systems.
基金the Irish Research Council for Government-of-Ireland postdoctoral fellowship, under grant no. GOIPD/2016/365
文摘Molecular-dynamics(MD)simulations have been performed for the growth of a spherical methane-hydrate nano-crystallite,surrounded by a supersaturated water–methane liquid phase,using both a hybrid and globalsystem thermostatting approach.It was found that hybrid thermostatting led to more sluggish growth and the establishment of a radial temperature profile about the spherical hydrate crystallite,in which the growing crystal phase is at a higher temperature than the surrounding liquid phase in the interfacial region,owing to latent-heat dissipation.In addition,Onsager’s-hypothesis fluctuation–dissipation analysis of fluctuations in the number of crystal-state water molecules at the interface shows slower growth.
基金Project supported by the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No 20060003025)the State Key Program for Basic Research of China (Grant No 2003CB716201)
文摘In this paper, single-walled carbon nanotubes （SWCNTs） are studied through molecular dynamics （MD） simulation. The simulations are performed at temperatures of 1 and 300K separately, with atomic interactions characterized by the second Reactive Empirical Bond Order （REBO） potential, and temperature controlled by a certain thermostat, i.e. by separately using the velocity scaling, the Berendsen scheme, the Nose-Hoover scheme, and the generalized Langevin scheme. Results for a （5,5） SWCNT with a length of 24.5 nm show apparent distortions in nanotube configuration, which can further enter into periodic vibrations, except in simulations using the generalized Langevin thermostat, which is ascribed to periodic boundary conditions used in simulation. The periodic boundary conditions may implicitly be applied in the form of an inconsistent constraint along the axis of the nanotube. The combination of the inconsistent constraint with the cumulative errors in calculation causes the distortions of nanotubes. When the generalized Langevin thermostat is applied, inconsistently distributed errors are dispersed by the random forces, and so the distortions and vibrations disappear. This speculation is confirmed by simulation in the case without periodic boundary conditions, where no apparent distortion and vibration occur. It is also revealed that numerically induced distortions and vibrations occur only in simulation of nanotubes with a small diameter and a large length-to-diameter ratio. When MD simulation is applied to a system with a particular geometry, attention should be paid to avoiding the numerical distortion and the result infidelity.
基金Youth Research Start-up Fund of XinJiang University(QN070136)National Natural Science Foundation of China(50667002)
文摘The designed thermostat is based on the microcontroller featuring intelligence, programmable, environmental protection and power saving. The thermostat design is mainly composed of hardware and software design, the hardware includes the power supply circuit, temperature measurement circuit, humidity measurement circuit and backlight circuit; while the software design includes temperature measurement and compensation algorithm, moreover software flowchart is given as well. Finally the power supply circuit is simulated by the software of Pspice and the creative power stealing mode is verified by the simulation results. A target board is stuffed by hand with Pb-free electronic components and used to test hardware and debug software. Since the Pb-free components were used, power stealing mode is designed in hardware and temperature compensation algorithm is accomplished in software, and the thermostat is outstanding with its features of "green" and "power saving".
文摘The paper demonstrates deep unity of classic and quantum physics at the space thermostat (ST) presence, which fulfilled all space by the temperature T0 = 2.73 K. The ST presents itself the Cosmic Microwave Background (CMB). From the main quantum position we consider the ST/CMB as the wave function carrier (“quantum background”). The paper is devoted to ST/CMB medium the classic conservation laws of mass, momentum and energy. We show the soliton like solutions of our classic model correspond to Schrodinger’s quantum solutions, demonstrate the atom hydrogen specter and other quantum peculiarities. The paper contains typical technical examples classic/ quantum simulation at the ST presence.
文摘In this paper, the impact of limiting thermostat on the rupture event occuring in Fuel-Oil burner fuel pre-heaters＇ resistant （heat generating） wires is inspected numerically. Gaseous fuel content in the pipeline has also been issued as a possibility. Heater＇s inner temperature distributions have been simulated by an in-house MATrix LABoratory （MATLAB） script in order to understand the resistant wire exposure to high temperatures by numerous scenarios. It is concluded that the effect of fuel flowrate is not a major effect on the wires＇ fate because of the limiting thermostat co-working. The main difference between the calculations is the effect of thermostat cut off function. The numerical simulations enlightened the dominant effect of thermostat sensing delay, so the overheating event. Intolerable delay results with a quick drop in the thermal efficiency and an increased possibility on wire rupture due to overheating which means a burner malfunction. Referring to the first numerical simulation results, a distributed and reduced heat flux was implemented with the same fluid and thermodynamic properties on a revised pre-heater model with an increased heater plate. The increment, thus the reduction on the heat flux of the ribbon wires has been noted as the key for safe operation.
基金supported by the National Science Foundation(award OAC-2005572)the State of Illinois,USA.
文摘Heating,ventilation,and air conditioning system runtime is a crucial metric for establishing the connection between system operation and energy performance.Similar homes in the same location can have varying runtime due to different factors.To understand such heterogeneity,this study conducted an energy signature analysis of heating and cooling system runtime for 5,014 homes across the US>using data from ecobee smart thermostats.Two approaches were compared for the energy signature analysis:(1)using daily mean outdoor temperature and(2)using the difference between the daily mean outdoor temperature and the indoor thermostat setpoint(delta T)as the independent variable.The best-fitting energy signature parameters(balance temperatures and slopes)for each house were estimated and statistically analyzed.The results revealed significant differences in balance temperatures and slopes across various climates and individual homes.Additionally,we identified the impact of housing characteristics and weather conditions on the energy signature parameters using a long absolute shrinkage and selection operator(LASSO)regression.Incorporating delta T into the energy signature model significantly enhances its ability to detect hidden impacts of various features by minimizing the influence of setpoint preferences.Moreover,our cooling slope analysis highlights the significant impact of outdoor humidity levels,underscoring the need to include latent loads in building energy models.
基金the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement No.957755,project SENDER:Sustainable consumer engagement and demand response.
文摘Demand-side flexibility is crucial to balancing supply and demand,as renewable energy sources are increasingly integrated into the energy mix,and heating and transport systems are becoming more and more electrified.Historically,this balancing has been managed from the supply side.However,the shift towards renewable energy sources limits the controllability of traditional fossil fuel plants,increasing the importance of demand response(DR)techniques to achieve the required flexibility.Aggregators participating in flexibility markets need to accurately forecast the adaptability they can offer,a task complicated by numerous influencing variables.Based on a top-down approach,this study addresses the problem of forecasting electricity demand in the presence of flexibility from thermostatically controlled loads.We propose a hybrid model that combines data-driven techniques for probabilistic estimation of electricity consumption with a disaggregation of electricity consumption to identify the fraction of thermal loads,subject to flexibility,which is simulated by a virtual battery model.The technique is applied to a synthetic dataset that simulates the response of a European neighborhood to demand response interventions.The results demonstrate the model’s ability to accurately predict both the reduction in electricity demand during DR events and the subsequent rebound in consumption.The model achieves a mean absolute percentage error(MAPE)lower than 17.0%,comparable to the accuracy without flexibility.The results obtained are compared with a direct data-driven approach,demonstrating the validity and effectiveness of our model.
基金supported in part by the National Key Research and Development Program of China(No.2023YFB2406600)the Joint Funds of the National Natural Science Foundation of China(No.U22A6007)the National Science Fund for Excellent Young Scholars of China(No.52222703).
文摘Thermostatically controlled loads(TCLs)on the demand side have been a vital energy resource in smart grids.To efficiently utilize the large-scale TCLs and enhance the flexibility of micro-community systems,this paper proposes a distributed coordinated control strategy based on the distributed model predictive control(MPC).To achieve the adaptive coordinated control among TCLs and consider user comfort constraints,a distributed dual-layer internal control strategy based on MPC is established on a scalable communication network.This strategy achieves the efficient utilization of TCLs in a distributed manner and notably improves the convergence speed through sparse network communication between neighbors.For external resource utilization of TCLs,a multi-timescale scheduling framework is proposed to realize the pre-allocation of electricity.Furthermore,the feasibility of the proposed distributed coordinated control strategy is confirmed through comparative case analysis.
基金supported by the Federal Ministry for Economic Affairs and Climate Action(BMWK),promotional reference 03EN3026C(FUBIC All-Electricity-Realization).
文摘Thermostatic Radiator Valves(TRVs)are a widely used technology for regulating room heating in Europe countries.Smart TRVs can provide significant energy savings,often ranging from 20–40%compared to conventional heating systems.They use sensors and algorithms to learn user behavior and optimize heating schedules accordingly.They can often be easily retrofitted to existing heating systems,making them a practical option for enhancing energy efficiency in present buildings,especially in office buildings due to their highly dynamic operational patterns.This work presents a novel human-in-the-loop control strategy for Internet of Things(IoT)-based TRVs using Deep Reinforcement Learning(DRL).A key focus of this research is enhancing the adaptability of agents’behavior by implementing a more generic and flexible Markov Decision Process(MDP)to promote policy generalization across diverse scenarios.The study explores the challenges of transferring control behaviors from simulation environments to real-world settings,examining the performance across different thermal zones and evaluating the integration flexibility of the control strategy within building systems.Real-world occupant behavior is incorporated,including dynamic comfort preferences and occupancy predictions,to better align thermostat operation with user preferences.Furthermore,this paper discusses the practical challenges encountered during implementation,including battery consumption of IoT devices,integration of occupancy detection and prediction systems,and maintenance requirements.By addressing these issues,the proposed control strategy seeks to improve the scalability and feasibility of IoT-based TRVs,thereby providing a viable solution for their widespread deployment in buildings.
文摘Occupant-centric controls(OcC)is an indoor climate control approach whereby occupant feedback is used in the sequence of operation of building energy systems.While OcC has been used in a wide range of building applications,an OcC category that has received considerable research interest is learning occupants'thermal preferences through their thermostat interactions and adapting temperature setpoints accordingly.Many recent studies used reinforcement learning(RL)as an agent for OcC to optimize energy use and occupant comfort.These studies depended on predicted mean vote(PMV)models or constant comfort ranges to represent comfort,while only few of them used thermostat interactions.This paper addresses this gap by introducing a new off-policy reinforcement learning(RL)algorithm that imitates the occupant behaviour by utilizing unsolicited occupant thermostat overrides.The algorithm is tested with a number of synthetically generated occupant behaviour models implemented via the Python APl of EnergyPlus.The simulation results indicate that the RL algorithm could rapidly learn preferences for all tested occupant behaviour scenarios with minimal exploration events.While substantial energy savings were observed with most occupant scenarios,the impact on the energy savings varied depending on occupants'preferences and thermostat use behaviour stochasticity.
基金National Key Research and Development Program of China,Grant/Award Number:2019YFA0704900National Natural Science Foundation of China,Grant/Award Number:52202289。
文摘As the core components of fifth-generation(5G)communication technology,optical modules should be consistently miniaturized in size while improving their level of integration.This inevitably leads to a dramatic spike in power consumption and a consequent increase in heat flow density when operating in a confined space.To ensure a successful start-up and operation of 5G optical modules,active cooling and precise temperature control via the Peltier effect in confined space is essential yet challenging.In this work,p-type Bi_(0.5)Sb_(1.5)Te_(3)and n-type Bi_(2)Te_(2.7)Se_(0.3)bulk thermoelectric(TE)materials are used,and a micro thermoelectric thermostat(micro-TET)(device size,2×9.3×1.1mm^(3);leg size,0.4×0.4×0.5mm^(3);number of legs,44)is successfully integrated into a 5G optical module with Quad Small Form Pluggable 28 interface.As a result,the internal temperature of this kind of optical module is always maintained at 45.7℃ and the optical power is up to 7.4 dBm.Furthermore,a multifactor design roadmap is created based on a 3D numerical model using the ANSYS finite element method,taking into account the number of legs(N),leg width(W),leg length(L),filling atmosphere,electric contact resistance(Rec),thermal contact resistance(Rtc),ambient temperature(Ta),and the heat generated by the laser source(QL).It facilitates the integrated fabrication of micro-TET,and shows the way to enhance packaging and performance under different operating conditions.According to the roadmap,the micro-TET(2×9.3×1mm^(3),W=0.3 mm,L=0.4 mm,N=68 legs)is fabricated and consumes only 0.89W in cooling mode(Q_(L)=0.7W,T_(a)=80℃)and 0.36Win heating mode(T_(a)=0℃)to maintain the laser temperature of 50℃.This research will hopefully be applied to other microprocessors for precise temperature control and integrated manufacturing.
