ZTE Corporation is China’s largest listedtelecommunications equipment provider spe-cialized in offering a full range of tailor-madesolutions for customers in high-,middle-andlow-end markets.
The CO2 emission reduction policy of the International Maritime Organization(IMO)recommends that the operation of ships,managed by maritime transport companies,should be energy-efficient.An evaluation method that can ...The CO2 emission reduction policy of the International Maritime Organization(IMO)recommends that the operation of ships,managed by maritime transport companies,should be energy-efficient.An evaluation method that can determine how successfully a ship implements the energy efficiency plan is proposed in this study.To develop this method,the measures required for energy-efficient ship operations according to the Ship Energy Efficiency Management Plan(SEEMP)operational guidelines were selected.The weights of the selected measures,which indicate how they contribute to the energy-efficient operation of a ship,were derived using a survey based on the analytic hierarchy process(AHP)method.Consequently,using these measures and their weights,a new evaluation method was proposed.This evaluation method was applied to shipping companies in South Korea,and their ship operation energy efficiency indices were derived and compared.This evaluation method will be useful to the government and shipping companies in assessing the energy efficiency of ship operations.展开更多
An integrated energy service company in an industrial park or commercial building is responsible for managing all energy sources in their local region, including electricity, water, gas, heating, and cooling. To reduc...An integrated energy service company in an industrial park or commercial building is responsible for managing all energy sources in their local region, including electricity, water, gas, heating, and cooling. To reduce energy wastage and increase energy utilization, it is necessary to perform efficiency analyses and diagnoses on integrated energy systems(IESs). However, the integrated energy data necessary for energy efficiency analyses and diagnoses come from a wide variety of instruments, each of which uses different transmission protocols and data formats. This makes it challenging to handle energy-flow data in a unified manner. Thus, we have constructed a unified model for diagnosing energy usage abnormalities in IESs. Using this model, the data are divided into working days and non-working days, and benchmark values are calculated after the data have been weighted to enable unified analysis of several types of energy data. The energy-flow data may then be observed, managed, and compared in all aspects to monitor sudden changes in energy usage and energy wastage. The abnormal data identified and selected by the unified model are then subjected to big-data analysis using technical management tools, enabling the detection of user problems such as abnormalities pertaining to acquisition device, metering, and energy usage. This model facilitates accurate metering of energy data and improves energy efficiency. The study has significant implications in terms of fulfilling the energy saving.展开更多
The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular ...The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.展开更多
Buildings are becoming suitable for application of sophisticated energy management approaches to increase their energy efficiency and possibly turn them into active energy market participants.The paper proposes a modu...Buildings are becoming suitable for application of sophisticated energy management approaches to increase their energy efficiency and possibly turn them into active energy market participants.The paper proposes a modular coordination mechanism between building zones comfort control and building microgrid energy flows control based on model predictive control. The approach opens possibilities to modularly coordinate technologically heterogeneous building subsystems for economically-optimal operation under user comfort constraints. The imposed modularity is based on a simple interface for exchanging building consumption and microgrid energyprice profiles. This is a key element for technology separation,replication and up-scaling towards the levels of smart grids and smart cities where buildings play active roles in energy management. The proposed coordination mechanism is presented in a comprehensive realistic case study of maintaining comfort in an office building with integrated microgrid. The approach stands out with significant performance improvements compared to various non-coordinated predictive control schemes and baseline controllers. Results give detailed information about yearly cost-effectiveness of the considered configurations,which are suitable for deployment as short-and long-term zero-energy building investments.展开更多
随着人工智能(artificial intelligence,AI)的兴起,大模型(large language model,LLM)日益成为知识推介和多轮对话的核心技术。伴随而来,AI大模型在数据处理、模型训练和部署过程中的高能耗问题亟须有效评估,以便在模型优化后进行前后...随着人工智能(artificial intelligence,AI)的兴起,大模型(large language model,LLM)日益成为知识推介和多轮对话的核心技术。伴随而来,AI大模型在数据处理、模型训练和部署过程中的高能耗问题亟须有效评估,以便在模型优化后进行前后量化对比。提出一种AI大模型能耗的评估方法,旨在量化评估AI模型的服务效率(efficiency,E)。该模型使用训练收敛时间(time,T)、模型参数规模(parameter,P)和浮点运算量(floating-point operations,F)等多维度因素,通过构建能源消耗函数C(T,P,F)实现量化分析;同时,运用非线性最小二乘法,得出模型参数。该分析方法不仅适用于电信运营商客服AI模型的运行效率分析,也可泛化于其他行业的AI模型能耗评估。展开更多
文摘ZTE Corporation is China’s largest listedtelecommunications equipment provider spe-cialized in offering a full range of tailor-madesolutions for customers in high-,middle-andlow-end markets.
基金support from the project titled "Development of Ship-handling and Passenger Evacuation Support System" funded by the Ministry of Oceans and Fisheries(South Korea-MOF)
文摘The CO2 emission reduction policy of the International Maritime Organization(IMO)recommends that the operation of ships,managed by maritime transport companies,should be energy-efficient.An evaluation method that can determine how successfully a ship implements the energy efficiency plan is proposed in this study.To develop this method,the measures required for energy-efficient ship operations according to the Ship Energy Efficiency Management Plan(SEEMP)operational guidelines were selected.The weights of the selected measures,which indicate how they contribute to the energy-efficient operation of a ship,were derived using a survey based on the analytic hierarchy process(AHP)method.Consequently,using these measures and their weights,a new evaluation method was proposed.This evaluation method was applied to shipping companies in South Korea,and their ship operation energy efficiency indices were derived and compared.This evaluation method will be useful to the government and shipping companies in assessing the energy efficiency of ship operations.
基金supported by National Key Research and Development Program of China (No.2017YFB903304)the State Grid Science and Technology Program (Hybrid Simnlation Key Technology for Integrated Energy System and Platform Construction)
文摘An integrated energy service company in an industrial park or commercial building is responsible for managing all energy sources in their local region, including electricity, water, gas, heating, and cooling. To reduce energy wastage and increase energy utilization, it is necessary to perform efficiency analyses and diagnoses on integrated energy systems(IESs). However, the integrated energy data necessary for energy efficiency analyses and diagnoses come from a wide variety of instruments, each of which uses different transmission protocols and data formats. This makes it challenging to handle energy-flow data in a unified manner. Thus, we have constructed a unified model for diagnosing energy usage abnormalities in IESs. Using this model, the data are divided into working days and non-working days, and benchmark values are calculated after the data have been weighted to enable unified analysis of several types of energy data. The energy-flow data may then be observed, managed, and compared in all aspects to monitor sudden changes in energy usage and energy wastage. The abnormal data identified and selected by the unified model are then subjected to big-data analysis using technical management tools, enabling the detection of user problems such as abnormalities pertaining to acquisition device, metering, and energy usage. This model facilitates accurate metering of energy data and improves energy efficiency. The study has significant implications in terms of fulfilling the energy saving.
基金the National Renewable Energy Laboratory(NREL)operated by Alliance for Sustainable Energy,LLC,for the U.S.Department of Energy(DOE)under Contract No.DE-AC36-08GO28308the U.S.Department of Energy Office of Electricity AOP Distribution Grid Resilience Project.The views expressed in the article do not necessarily represent the views of the DOE or the U.S.Government.The U.S.Government retains and the publisher,by accepting the article for publication,acknowledges that the U.S.Government retains a nonexclusive,paid-up,irrevocable,worldwide license to publish or reproduce the published form of this work,or allow others to do so,for U.S.Government purposes.
文摘The rapid growth of distributed generator(DG)capacities has introduced additional controllable assets to improve the performance of distribution systems in terms of service restoration.Renewable DGs are of particular interest to utility companies,but the stochastic nature of intermittent renewable DGs could have a negative impact on the electric grid if they are not properly handled.In this study,we investigate distribution system service restoration using DGs as the primary power source,and we develop an effective approach to handle the uncertainty of renewable DGs under extreme conditions.The distribution system service restoration problem can be described as a mixed-integer second-order cone programming model by modifying the radial topology constraints and power flow equations.The uncertainty of renewable DGs will be modeled using a chance-constrained approach.Furthermore,the forecast errors and noises in real-time operation are solved using a novel model-free control algorithm that can automatically track the trajectory of real-time DG output.The proposed service restoration strategy and model-free control algorithm are validated using an IEEE 123-bus test system.
文摘Buildings are becoming suitable for application of sophisticated energy management approaches to increase their energy efficiency and possibly turn them into active energy market participants.The paper proposes a modular coordination mechanism between building zones comfort control and building microgrid energy flows control based on model predictive control. The approach opens possibilities to modularly coordinate technologically heterogeneous building subsystems for economically-optimal operation under user comfort constraints. The imposed modularity is based on a simple interface for exchanging building consumption and microgrid energyprice profiles. This is a key element for technology separation,replication and up-scaling towards the levels of smart grids and smart cities where buildings play active roles in energy management. The proposed coordination mechanism is presented in a comprehensive realistic case study of maintaining comfort in an office building with integrated microgrid. The approach stands out with significant performance improvements compared to various non-coordinated predictive control schemes and baseline controllers. Results give detailed information about yearly cost-effectiveness of the considered configurations,which are suitable for deployment as short-and long-term zero-energy building investments.
文摘随着人工智能(artificial intelligence,AI)的兴起,大模型(large language model,LLM)日益成为知识推介和多轮对话的核心技术。伴随而来,AI大模型在数据处理、模型训练和部署过程中的高能耗问题亟须有效评估,以便在模型优化后进行前后量化对比。提出一种AI大模型能耗的评估方法,旨在量化评估AI模型的服务效率(efficiency,E)。该模型使用训练收敛时间(time,T)、模型参数规模(parameter,P)和浮点运算量(floating-point operations,F)等多维度因素,通过构建能源消耗函数C(T,P,F)实现量化分析;同时,运用非线性最小二乘法,得出模型参数。该分析方法不仅适用于电信运营商客服AI模型的运行效率分析,也可泛化于其他行业的AI模型能耗评估。
