Abstract: The disclosure provides a distributed dispatch method for ubiquitous power Internet of Things based on a transition matrix. The ubiquitous power Internet of Things includes generators. The method includes: S1, setting a marginal cost function of each of the generators, and extracting key cost parameters in the marginal cost function; S2, establishing an optimization model based on the key cost parameters of each of the generators and a communication topology of the ubiquitous power Internet of Things, and solving the optimization model to obtain an optimized transition matrix; and S3, generating a plan of a power output of each of the generators based on the optimized transition matrix and a distributed dispatch protocol to perform a distributed dispatch.

Abstract: 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.

Abstract: The disclosure provides a method for identifying a power feasible region of a virtual power plant, and an apparatus for identifying a power feasible region of a virtual power plant. The method includes: S1, obtaining operation basic data of the internal power-distribution system; S2, establishing a static safety-constrained model of the virtual power plant based on the operation basic data, in which the static safety-constrained model is based on alternating current power flow equations; S3, establishing a power feasible region model of the virtual power plant based on the static safety-constrained model; and S4, calculating the power feasible region model based on the operation basic data and a feasible region vertex enumeration algorithm to obtain the power feasible region of the virtual power plant.

Abstract: The present disclosure provides a method and apparatus for calculating carbon emission response based on carbon emission flows. The method includes: calculating a total carbon flow rate of a power system from a carbon flow rate of each of carbon meter users, the carbon flow rate being obtained based on a carbon emission flow of the carbon meter user; determining whether the total carbon flow rate is greater than a carbon emission response threshold; and calculating, in response to determining that the total carbon flow rate is greater than the carbon emission response threshold, a target carbon emission reduction of one or more of the carbon meter users during a carbon emission response period based on target carbon emission response demand, and initiating a carbon emission response based on the target carbon emission reduction.

Abstract: Provided is a carbon emission flow calculation method for a regional integrated energy system.

Abstract: The present disclosure discloses a method and apparatus for measuring carbon emission of a district heating system, an electronic device, and a medium. The method includes: obtaining a steady carbon emission amount of a current district heating system using a pre-trained steady carbon emission flow model; obtaining a dynamic carbon emission amount of the current district heating system using a pre-trained dynamic carbon emission flow model; and counting a carbon emission amount of the current district heating system based on the steady carbon emission amount and the dynamic carbon emission amount. Therefore, the present disclosure can effectively identify carbon emission details of each link of a source, a grid, and a load of the district heating system, clarify carbon emission responsibilities on both a source side and a load side, and realize accurate measurement of carbon emission of the district heating system, which has high application value.

Abstract: The disclosure provides a method and a system for dispatching a multi-region power system. The method includes: obtaining, by each regional system operator, basic operating parameters of the regional power system; establishing, by each regional system operator, a dispatching model of the regional power system based on the basic operating parameters; identifying, by each regional system operator, an aggregation model of the regional power system based on the dispatching model of the regional power system; reporting, by each regional system operator, the aggregation model to the cross-region system operator; establishing, by the cross-region system operator, a reduced dispatching model of the multi-region power system based on the aggregation model from each regional system operator; and solving, by the cross-region system operator, the reduced dispatching model to obtain a dispatching result of each regional power system.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: The disclosure provides a method and a system for dispatching a multi-region power system. The method includes: obtaining, by each regional system operator, basic operating parameters of the regional power system; establishing, by each regional system operator, a dispatching model of the regional power system based on the basic operating parameters; identifying, by each regional system operator, an aggregation model of the regional power system based on the dispatching model of the regional power system; reporting, by each regional system operator, the aggregation model to the cross-region system operator; establishing, by the cross-region system operator, a reduced dispatching model of the multi-region power system based on the aggregation model from each regional system operator; and solving, by the cross-region system operator, the reduced dispatching model to obtain a dispatching result of each regional power system.

Abstract: The disclosure provides a distributed dispatch method for ubiquitous power Internet of Things based on a transition matrix. The ubiquitous power Internet of Things includes generators. The method includes: S1, setting a marginal cost function of each of the generators, and extracting key cost parameters in the marginal cost function; S2, establishing an optimization model based on the key cost parameters of each of the generators and a communication topology of the ubiquitous power Internet of Things, and solving the optimization model to obtain an optimized transition matrix; and S3, generating a plan of a power output of each of the generators based on the optimized transition matrix and a distributed dispatch protocol to perform a distributed dispatch.

Abstract: 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.

Abstract: The disclosure provides a method for identifying a power feasible region of a virtual power plant, and an apparatus for identifying a power feasible region of a virtual power plant. The method includes: S1, obtaining operation basic data of the internal power-distribution system; S2, establishing a static safety-constrained model of the virtual power plant based on the operation basic data, in which the static safety-constrained model is based on alternating current power flow equations; S3, establishing a power feasible region model of the virtual power plant based on the static safety-constrained model; and S4, calculating the power feasible region model based on the operation basic data and a feasible region vertex enumeration algorithm to obtain the power feasible region of the virtual power plant.

Abstract: 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.

Abstract: The present disclosure provides a method and an apparatus for photovoltaic power forecast based on numerical weather prediction.

Abstract: 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.

Abstract: A method, an apparatus and a storage medium for transmission network expansion planning considering extremely large amounts of operation scenarios is provided. The method comprises establishing an optimization model for transmission network expansion planning, the optimization model including an objective function for minimizing the sum of investment costs for the transmission lines and expected values of operation costs in the power transmission network, solving the optimization model to obtain an optimal investment decision variable; and determining the transmission network expansion planning based on the optimal investment decision variable.

Abstract: A blockchain-based optimization method for complex scenarios in an energy system, in which an optimization problem is solved by nodes in the whole network after initialization, a node that solves the problem most quickly obtains a block accounting right and performs a broadcast to the whole network, other nodes verify the correctness of the received block, and the verified block is the global optimal solution of an energy system optimization model. The energy blockchain model provided by the invention can meet the performance demands of complex scenarios in the energy system optimization for safety, openness, throughput capacity and has the landing and application capability.