The knowledge representation mode and inference control strategy were analyzed according to the specialties of air-conditioning cooling/heating sources selection. The constructing idea and working procedure for knowle...The knowledge representation mode and inference control strategy were analyzed according to the specialties of air-conditioning cooling/heating sources selection. The constructing idea and working procedure for knowledge base and inference engine were proposed while the realization technique of the C language was discussed. An intelligent decision support system (IDSS) model based on such knowledge representation and inference mechanism was developed by domain engineers. The model was verified to have a small kernel and powerful capability in list processing and data driving, which was successfully used in the design of a cooling/heating sources system for a large-sized office building.展开更多
The energy saving performance of energy efficient windows has strong dependence on window direction. Transmitted insolation level definitely affected the cooling and heating load. Simple simulation on the decrement of...The energy saving performance of energy efficient windows has strong dependence on window direction. Transmitted insolation level definitely affected the cooling and heating load. Simple simulation on the decrement of cooling load and the increment of heating load of a shading window compared with those of a transparent window show the prospect of energy saving effect clearly.From southeastward to southwestward, shading window even enlarges total heating and cooling loads when the thermal transmission is the same. However, if the shading coefficient of window is switched between summer and winter, total cooling and heating load can be reduced. This result clarifies the importance of "smart window".展开更多
An actively water-cooled limiter has been designed for the long pulse operation of an HT-7 device, by adopting an integrated structure-doped graphite and a copper alloy heat sink with a super carbon sheet serving as a...An actively water-cooled limiter has been designed for the long pulse operation of an HT-7 device, by adopting an integrated structure-doped graphite and a copper alloy heat sink with a super carbon sheet serving as a compliant layer between them. The behaviors of the integrated structure were evaluated in an electron beam facility under different heat loads and cooling conditions. The surface temperature and bulk temperature distribution were carefully measured by optical pyrometers and thermocouples under a steady state heat flux of 1 to 5 MW/m^2 and a water flow rate of 3 m^3/h, 4.5 m^3/h and 6 m^3/h, respectively. It was found that the surface temperature increased rapidly with the heat flux rising, but decreased only slightly with the water flow rate rising. The surface temperature reached approximately 1200℃ at 5 MW/m^2 of heat flux and 6 m^3/h of water flow. The primary experimental results indicate that the integrated design meets the requirements for the heat expelling capacity of the HT-7 device. A set of numerical simulations was also completed, whose outcome was in good accord with the experimental results.展开更多
This paper presents an experimental study of a new designed Trombe wall in combination with solar chimney and water spraying system in a test room under Yazd(Iran) desert climate.The Trombe wall area is 50% of that of...This paper presents an experimental study of a new designed Trombe wall in combination with solar chimney and water spraying system in a test room under Yazd(Iran) desert climate.The Trombe wall area is 50% of that of the southern wall of the building that occupies less space and reduces the implementation costs. The new design of the channel has caused the absorber to receive the solar radiation from three directions. Based on the results, the optimum mass flow rate and the nozzle diameter of the water spraying system has been obtained 10 l/h and 30 μm, respectively. The results indicate that the water spraying system decreases indoor temperature and increases indoor relative humidity by about 8 ℃ and 17%, respectively. The most effect of outdoor relative humidity variation is on indoor relative humidity, rather than indoor temperature. When outdoor temperature increases, both indoor relative humidity and the difference between indoor and outdoor relative humidity decreases. The results also showed that theTrombe wall; Solar chimney; Water spraying system(2) Prediction of energy performance of residential buildings:A genetic programming approach, P67-74, by Mauro Castelli,Leonardo Trujillo, Leonardo Vanneschi, Ale觢 Popovic Abstract: Energy consumption has long been emphasized as an important policy issue in today's economies. In particular, the energy efficiency of residential buildings is considered a top priority of a country's energy policy. The paper proposes a genetic programming-based framework for estimating the energy performance of residential buildings. The objective is to build a model able to predict the heating load and the cooling load of residential buildings. An accurate prediction of these parameters facilitates a better control of energy consumption and, moreover, it helps choosing the energy supplier that better fits the energy needs,which is considered an important issue in the deregulated energy market. The proposed framework blends a recently developed version of genetic programming with a local search method and linear scaling. The resulting system enables us to build a model that produces an accurate estimation of both considered parameters. Extensive simulations on 768 diverse residential buildings confirm the suitability of the proposed method in predicting heating load and cooling load. In particular, the proposed method is more accurate than the existing state-of-the-art techniques.展开更多
An active distribution system power-supply planning model considering cooling,heating and power load balance is proposed in this paper.A regional energy service company is assumed to be in charge of the investment and...An active distribution system power-supply planning model considering cooling,heating and power load balance is proposed in this paper.A regional energy service company is assumed to be in charge of the investment and operation for the system in the model.The expansion of substations,building up distributed combined cooling,heating and power(CCHP),gas heating boiler(GHB)and air conditioner(AC)are included as investment planning options.In terms of operation,the load scenarios are divided into heating,cooling and transition periods.Also,the extreme load scene is included to assure the power supply reliability of the system.Numerical results demonstrate the effectiveness of the proposed model and illustrate the economic benefits of applying distributed CCHP in regional power supply on investment and operation.展开更多
As the ubiquitous electric power internet of things(UEPIoT)evolves and IoT data increases,traditional scheduling modes for load dispatch centers have yielded a variety of chal-lenges such as calculation of real-time o...As the ubiquitous electric power internet of things(UEPIoT)evolves and IoT data increases,traditional scheduling modes for load dispatch centers have yielded a variety of chal-lenges such as calculation of real-time optimization,extraction of time-varying characteristics and formulation of coordinated scheduling strategy for capacity optimization of electric heating and cooling loads.In this paper,a deep neural network coor-dination model for electric heating and cooling loads based on the situation awareness(SA)of thermostatically controlled loads(TCLs)is proposed.First,a sliding window is used to adaptively preprocess the IoT node data with uncertainty.According to personal thermal comfort(PTC)and peak shaving contribution(PSC),a dynamic model for loads is proposed;meanwhile,personalized behavior and consumer psychology are integrated into a flexible regulation model of TCLs.Then,a deep Q-network(DQN)-based approach,using the thermal comfort and electricity cost as the comprehensive reward function,is proposed to solve the sequential decision problem.Finally,the simulation model is designed to support the validity of the deep neural network coordination model for electric heating and cooling loads,by using UEPIoT intelligent dispatching system data.The case study demonstrates that the proposed method can efficiently manage coordination with large-scale electric heating and cooling loads.展开更多
The indoor parameters are generally non-uniform distributed.Consequently,it is important to study the space cooling/heating load oriented to local requirements.Though the influence of indoor set point,heat sources,and...The indoor parameters are generally non-uniform distributed.Consequently,it is important to study the space cooling/heating load oriented to local requirements.Though the influence of indoor set point,heat sources,and ambient temperature of convective thermal boundary on cooling/heating load has been investigated in the uniform environment in previous research,the influence of these factors,particularly the convective heat gain/loss through a building envelope,on cooling/heating load of non-uniform environment has not yet been investigated.Therefore,based on the explicit expression of indoor temperature under the convective boundary condition,the expression of space cooling/heating load with convective heat transfer from the building envelope is derived and compared through case studies.The results can be summarized as follows.(1)The convective heat transferred through the building envelope is significantly related to the airflow patterns:the heating load in the case with ceiling supply air,where the supply air has a smaller contribution to the local zone,is 24%higher than that in the case with bottom supply air.(2)The degree of influence from each thermal boundary to the local zone of space cooling cases is close to that of a uniform environment,while the influence of each factor,particularly that of supply air,is non-uniformly distributed in space heating.(3)It is possible to enhance the influence of supply air and heat source with a reasonable airflow pattern to reduce the space heating load.In general,the findings of this study can be used to guide the energy savings of rooms with non-uniform environments for space cooling/heating.展开更多
Building energy consumption is heavily dependent on its heating load(HL)and cooling load(CL).Therefore,an efficient building demand forecast is critical for ensuring energy savings and improving the operating efficacy...Building energy consumption is heavily dependent on its heating load(HL)and cooling load(CL).Therefore,an efficient building demand forecast is critical for ensuring energy savings and improving the operating efficacy of the heating,ventilation,and air conditioning(HVAC)system.Modern and specialized energy-efficient building modeling technologies may offer a fair estimate of the influence of different construction methods.However,deploying these tools could be time-consuming and complex for the user.Thus,in this article,an ensemble model based on decision trees and the least square-boosting(LS-boosting)algorithm known as the regression tree ensemble(RTE)is proposed for the accurate prediction of HL and CL.The hyper parameters of the RTE are optimized by shuffled frog leaping optimization(SFLA),which leads to SRTE.Stepwise regression(STR)and Gaussian process regression(GPR)based on different kernel functions are also designed for comparison purposes.Results demonstrate that the value of root mean squared error is reduced by 37%–68%and 30%–41%for HL and CL of residential buildings,respectively,by the proposed SRTE in comparison to other models.Furthermore,the findings from the real dataset support the proposed model’s effectiveness in predicting HVAC energy usage.It can be concluded that the proposed SRTE is more effective and accurate than other methods for predicting the energy consumption of HVAC systems.展开更多
为解决能源危机问题,提高能源利用率,综合能源系统(integrated energy system,IES)成为发展创新型能源系统的重要方向。准确的多元负荷预测对IES的经济调度和优化运行有着重要的影响,而借助混沌理论能够进一步挖掘IES多元负荷潜在的耦...为解决能源危机问题,提高能源利用率,综合能源系统(integrated energy system,IES)成为发展创新型能源系统的重要方向。准确的多元负荷预测对IES的经济调度和优化运行有着重要的影响,而借助混沌理论能够进一步挖掘IES多元负荷潜在的耦合特性。提出了一种基于多变量相空间重构(multivariate phase space reconstruction,MPSR)和径向基函数神经网络(radial basis function neural network,RBFNN)相结合的IES超短期电冷热负荷预测模型。首先,分析了IES中能源子系统之间的耦合关系,运用Pearson相关性分析定量描述多元负荷和气象特征的相关性。然后,采用C-C法对时间序列进行MPSR以进一步挖掘电冷热负荷和气象特征在时间上的耦合特性。最后,利用RBFNN模型对电冷热负荷间耦合关系进行学习并预测。实验结果表明,所提方法有效挖掘并学习电冷热负荷在时间上的耦合特性,且在不同样本容量下具有良好且稳定的预测效果。展开更多
With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This st...With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs.With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads,an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established.The role of flexible loads in improving the economy of an energy system was investigated using examples,and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios.The results showed that the total cost of the system in different scenarios was reduced by 18.04%,9.1%,3.35%,and 7.03%,respectively,whereas the total carbon emissions of the system were reduced by 65.28%,20.63%,3.85%,and 18.03%,respectively,when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously.Flexible electrical and thermal loads did not have the same impact on the system performance.In the analyzed case,the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account.Photovoltaics have an excess of carbon trading credits and can profit from selling them,whereas other devices have an excess of carbon trading and need to buy carbon credits.展开更多
文摘The knowledge representation mode and inference control strategy were analyzed according to the specialties of air-conditioning cooling/heating sources selection. The constructing idea and working procedure for knowledge base and inference engine were proposed while the realization technique of the C language was discussed. An intelligent decision support system (IDSS) model based on such knowledge representation and inference mechanism was developed by domain engineers. The model was verified to have a small kernel and powerful capability in list processing and data driving, which was successfully used in the design of a cooling/heating sources system for a large-sized office building.
文摘The energy saving performance of energy efficient windows has strong dependence on window direction. Transmitted insolation level definitely affected the cooling and heating load. Simple simulation on the decrement of cooling load and the increment of heating load of a shading window compared with those of a transparent window show the prospect of energy saving effect clearly.From southeastward to southwestward, shading window even enlarges total heating and cooling loads when the thermal transmission is the same. However, if the shading coefficient of window is switched between summer and winter, total cooling and heating load can be reduced. This result clarifies the importance of "smart window".
基金The project partially supported by National Natural Science Foundation of China (No. 10275069)
文摘An actively water-cooled limiter has been designed for the long pulse operation of an HT-7 device, by adopting an integrated structure-doped graphite and a copper alloy heat sink with a super carbon sheet serving as a compliant layer between them. The behaviors of the integrated structure were evaluated in an electron beam facility under different heat loads and cooling conditions. The surface temperature and bulk temperature distribution were carefully measured by optical pyrometers and thermocouples under a steady state heat flux of 1 to 5 MW/m^2 and a water flow rate of 3 m^3/h, 4.5 m^3/h and 6 m^3/h, respectively. It was found that the surface temperature increased rapidly with the heat flux rising, but decreased only slightly with the water flow rate rising. The surface temperature reached approximately 1200℃ at 5 MW/m^2 of heat flux and 6 m^3/h of water flow. The primary experimental results indicate that the integrated design meets the requirements for the heat expelling capacity of the HT-7 device. A set of numerical simulations was also completed, whose outcome was in good accord with the experimental results.
文摘This paper presents an experimental study of a new designed Trombe wall in combination with solar chimney and water spraying system in a test room under Yazd(Iran) desert climate.The Trombe wall area is 50% of that of the southern wall of the building that occupies less space and reduces the implementation costs. The new design of the channel has caused the absorber to receive the solar radiation from three directions. Based on the results, the optimum mass flow rate and the nozzle diameter of the water spraying system has been obtained 10 l/h and 30 μm, respectively. The results indicate that the water spraying system decreases indoor temperature and increases indoor relative humidity by about 8 ℃ and 17%, respectively. The most effect of outdoor relative humidity variation is on indoor relative humidity, rather than indoor temperature. When outdoor temperature increases, both indoor relative humidity and the difference between indoor and outdoor relative humidity decreases. The results also showed that theTrombe wall; Solar chimney; Water spraying system(2) Prediction of energy performance of residential buildings:A genetic programming approach, P67-74, by Mauro Castelli,Leonardo Trujillo, Leonardo Vanneschi, Ale觢 Popovic Abstract: Energy consumption has long been emphasized as an important policy issue in today's economies. In particular, the energy efficiency of residential buildings is considered a top priority of a country's energy policy. The paper proposes a genetic programming-based framework for estimating the energy performance of residential buildings. The objective is to build a model able to predict the heating load and the cooling load of residential buildings. An accurate prediction of these parameters facilitates a better control of energy consumption and, moreover, it helps choosing the energy supplier that better fits the energy needs,which is considered an important issue in the deregulated energy market. The proposed framework blends a recently developed version of genetic programming with a local search method and linear scaling. The resulting system enables us to build a model that produces an accurate estimation of both considered parameters. Extensive simulations on 768 diverse residential buildings confirm the suitability of the proposed method in predicting heating load and cooling load. In particular, the proposed method is more accurate than the existing state-of-the-art techniques.
基金This project is supported by National High Technology Research and Development Program of China(863 Program)(No.2014AA051902).
文摘An active distribution system power-supply planning model considering cooling,heating and power load balance is proposed in this paper.A regional energy service company is assumed to be in charge of the investment and operation for the system in the model.The expansion of substations,building up distributed combined cooling,heating and power(CCHP),gas heating boiler(GHB)and air conditioner(AC)are included as investment planning options.In terms of operation,the load scenarios are divided into heating,cooling and transition periods.Also,the extreme load scene is included to assure the power supply reliability of the system.Numerical results demonstrate the effectiveness of the proposed model and illustrate the economic benefits of applying distributed CCHP in regional power supply on investment and operation.
基金This project was supported by National Key Research and Development Plan(2017YFB0902100)Key Project of Liaoning Natural Science Foundation under Grant(20170520292).
文摘As the ubiquitous electric power internet of things(UEPIoT)evolves and IoT data increases,traditional scheduling modes for load dispatch centers have yielded a variety of chal-lenges such as calculation of real-time optimization,extraction of time-varying characteristics and formulation of coordinated scheduling strategy for capacity optimization of electric heating and cooling loads.In this paper,a deep neural network coor-dination model for electric heating and cooling loads based on the situation awareness(SA)of thermostatically controlled loads(TCLs)is proposed.First,a sliding window is used to adaptively preprocess the IoT node data with uncertainty.According to personal thermal comfort(PTC)and peak shaving contribution(PSC),a dynamic model for loads is proposed;meanwhile,personalized behavior and consumer psychology are integrated into a flexible regulation model of TCLs.Then,a deep Q-network(DQN)-based approach,using the thermal comfort and electricity cost as the comprehensive reward function,is proposed to solve the sequential decision problem.Finally,the simulation model is designed to support the validity of the deep neural network coordination model for electric heating and cooling loads,by using UEPIoT intelligent dispatching system data.The case study demonstrates that the proposed method can efficiently manage coordination with large-scale electric heating and cooling loads.
基金supported by the National Natural Science Foundation of China(No.51638010 and No.51578306).
文摘The indoor parameters are generally non-uniform distributed.Consequently,it is important to study the space cooling/heating load oriented to local requirements.Though the influence of indoor set point,heat sources,and ambient temperature of convective thermal boundary on cooling/heating load has been investigated in the uniform environment in previous research,the influence of these factors,particularly the convective heat gain/loss through a building envelope,on cooling/heating load of non-uniform environment has not yet been investigated.Therefore,based on the explicit expression of indoor temperature under the convective boundary condition,the expression of space cooling/heating load with convective heat transfer from the building envelope is derived and compared through case studies.The results can be summarized as follows.(1)The convective heat transferred through the building envelope is significantly related to the airflow patterns:the heating load in the case with ceiling supply air,where the supply air has a smaller contribution to the local zone,is 24%higher than that in the case with bottom supply air.(2)The degree of influence from each thermal boundary to the local zone of space cooling cases is close to that of a uniform environment,while the influence of each factor,particularly that of supply air,is non-uniformly distributed in space heating.(3)It is possible to enhance the influence of supply air and heat source with a reasonable airflow pattern to reduce the space heating load.In general,the findings of this study can be used to guide the energy savings of rooms with non-uniform environments for space cooling/heating.
基金supported by the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2021R1A2C3013687)the GIST Research Institute(GRI)grant funded by the GIST in GIST Research Project.
文摘Building energy consumption is heavily dependent on its heating load(HL)and cooling load(CL).Therefore,an efficient building demand forecast is critical for ensuring energy savings and improving the operating efficacy of the heating,ventilation,and air conditioning(HVAC)system.Modern and specialized energy-efficient building modeling technologies may offer a fair estimate of the influence of different construction methods.However,deploying these tools could be time-consuming and complex for the user.Thus,in this article,an ensemble model based on decision trees and the least square-boosting(LS-boosting)algorithm known as the regression tree ensemble(RTE)is proposed for the accurate prediction of HL and CL.The hyper parameters of the RTE are optimized by shuffled frog leaping optimization(SFLA),which leads to SRTE.Stepwise regression(STR)and Gaussian process regression(GPR)based on different kernel functions are also designed for comparison purposes.Results demonstrate that the value of root mean squared error is reduced by 37%–68%and 30%–41%for HL and CL of residential buildings,respectively,by the proposed SRTE in comparison to other models.Furthermore,the findings from the real dataset support the proposed model’s effectiveness in predicting HVAC energy usage.It can be concluded that the proposed SRTE is more effective and accurate than other methods for predicting the energy consumption of HVAC systems.
文摘为解决能源危机问题,提高能源利用率,综合能源系统(integrated energy system,IES)成为发展创新型能源系统的重要方向。准确的多元负荷预测对IES的经济调度和优化运行有着重要的影响,而借助混沌理论能够进一步挖掘IES多元负荷潜在的耦合特性。提出了一种基于多变量相空间重构(multivariate phase space reconstruction,MPSR)和径向基函数神经网络(radial basis function neural network,RBFNN)相结合的IES超短期电冷热负荷预测模型。首先,分析了IES中能源子系统之间的耦合关系,运用Pearson相关性分析定量描述多元负荷和气象特征的相关性。然后,采用C-C法对时间序列进行MPSR以进一步挖掘电冷热负荷和气象特征在时间上的耦合特性。最后,利用RBFNN模型对电冷热负荷间耦合关系进行学习并预测。实验结果表明,所提方法有效挖掘并学习电冷热负荷在时间上的耦合特性,且在不同样本容量下具有良好且稳定的预测效果。
基金supported by State Grid Shanxi Electric Power Company Science and Technology Project“Research on key technologies of carbon tracking and carbon evaluation for new power system”(Grant:520530230005)。
文摘With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs.With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads,an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established.The role of flexible loads in improving the economy of an energy system was investigated using examples,and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios.The results showed that the total cost of the system in different scenarios was reduced by 18.04%,9.1%,3.35%,and 7.03%,respectively,whereas the total carbon emissions of the system were reduced by 65.28%,20.63%,3.85%,and 18.03%,respectively,when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously.Flexible electrical and thermal loads did not have the same impact on the system performance.In the analyzed case,the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account.Photovoltaics have an excess of carbon trading credits and can profit from selling them,whereas other devices have an excess of carbon trading and need to buy carbon credits.