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公开(公告)号：US20200233021A1
公开(公告)日：2020-07-23
申请号：US16844798
申请日：2020-04-09
申请人： Tsinghua University
发明人： Qixin CHEN , Kedi ZHENG , Yi WANG , Chongqing KANG , Qing XIA
摘要： The present disclosure provides a method and a device for detecting electricity theft, and a computer readable medium, smart meter data of each user and aggregated electricity consumption data are obtained during the detection period in the target area, a load profile set and non-technical loss data are obtained, and a correlation between each load profile in the load profile set and the non-technical loss data is obtained through a maximum information coefficient method and based on the smart meter data and the aggregated electricity consumption data, so as to obtain a correlation indicator for measuring the correlation.
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2.发明申请公开(公告)号：US20220109304A1
公开(公告)日：2022-04-07
申请号：US17551178
申请日：2021-12-14
申请人： Tsinghua University
发明人： Pei YONG , Ning ZHANG , Ershun DU , Yi WANG , Chongqing KANG
摘要： A multi-energy system planning method is disclosed based on security region identification. The method includes obtaining alternative planning schemes from a multi-energy system planning department; for each alternative scheme, establishing a matrix model for describing energy conversion relationships in the multi-energy system, in which the multi-energy system comprises N energy conversion elements, N being an integer greater than or equal to 1; identifying N feasible domains of the multi-energy system under N operation scenarios, in which the i-th energy conversion element is out of operating under the i-th operation scenario, and calculating a security region of the multi-energy system by intersecting the identified feasible domains under N operation scenarios; calculating a load fitness rate of each alternative scheme based on each security region; and selecting an alternative scheme with the highest load fitness rate as a target scheme for planning the multi-energy system.
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公开(公告)号：US20210192643A1
公开(公告)日：2021-06-24
申请号：US17190402
申请日：2021-03-03
申请人： TSINGHUA UNIVERSITY
发明人： Ning ZHANG , Jingkun LIU , Yi WANG , Chongqing KANG
摘要： Disclosed is a centralized cloud energy storage system for massive and distributed users and a transaction settlement method thereof, a storage medium, and a terminal. The system includes: a centralized energy storage facility invested and operated by a cloud energy storage service provider; the massive and distributed users; and a power network and a user energy management system connecting the centralized energy storage facility with the massive and distributed users. A user sends a charging and discharging request to the cloud energy storage service provider through the user energy management system, and the cloud energy storage service provider issues a charging and discharging instruction to the centralized cloud energy storage system.
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公开(公告)号：US20220294224A1
公开(公告)日：2022-09-15
申请号：US17824113
申请日：2022-05-25
申请人： Tsinghua University
发明人： Ning ZHANG , Jingkun LIU , Yi WANG , Chongqing KANG
IPC分类号： H02J3/28 , G05B19/042 , H02J3/00
摘要： An operation decision-making method for centralized cloud energy storage capable of participating in power grid auxiliary services. The method includes: establishing a model predictive control model; obtaining operating parameters of the current period t from a grid control center at a beginning of a current decision-making cycle; predicting operating parameters within the predetermined time range based on historical data; obtaining decision variables according to the model predictive control model, the operating parameters of the current period and the operating parameters within the predetermined time range; setting a charging power of the centralized energy storage facility in the current period t and a discharging power according to the decision variables; obtaining an actual power of the centralized energy storage facility at an end of the current period t through sensors installed on the centralized energy storage facility as a parameter for a next decision period.
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公开(公告)号：US20210047366A1
公开(公告)日：2021-02-18
申请号：US16639570
申请日：2018-07-05
申请人： TSINGHUA UNIVERSITY
发明人： Xinhui XING , Yi WANG , Chong ZHANG , Nan SU
摘要： Disclosed is an Andrias davidianus cartilage preparation. The Andrias davidianus cartilage enzymatic extract of the present invention is obtained by a method comprising: obtaining cartilage from Andrias davidianus, proteolyzing the obtained cartilage, obtaining a supernatant after the proteolysis, and drying the supernatant. The Andrias davidianus cartilage enzymatic extract and an alcohol-soluble component thereof according to the present invention comprise a cartilage polypeptide, and have the effects of lowering uric acid, or treating hyperuricemia.
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公开(公告)号：US20210097453A1
公开(公告)日：2021-04-01
申请号：US17118922
申请日：2020-12-11
申请人： Tsinghua University
发明人： Yi WANG , Ning ZHANG , Chongqing KANG , Ershun DU
摘要： The disclosure relates to a quantile probabilistic short-term power load ensemble forecasting method. The method includes: dividing historical power load data of a power system into a first data set and a second data set; performing bootstrap sampling on the first data set to generate multiple training data sets; training a neural network quantile regression model, a random forest quantile regression model and a gradient boosting regression tree regression model for the each training data set to obtain quantile forecasting models; establishing an optimization model with an objective function for minimizing the quantile loss for the second data set, and determining a weight for each of the quantile regression models, to calculate a power load ensemble forecasting model for predicting the power load in the power system.
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