Abstract: The present invention provides a method for managing heat-electric outputs of a high-proportion new energy system based on CSP-CHP combined energy supply, which belongs to the field of new energy system optimization and are used for solving the problems of insufficient flexibility of the high-proportion new energy system during the heating period and difficult consumption of renewable energy. The method includes: establishing a concentrating solar power (CSP) unit model and a combined heat and power (CHP) unit model based on the built structure; establishing a collaborative optimization model of the high-proportion new energy system based on the proposed unit models; acquiring relevant data of various units and renewable resource data; obtaining a sum of hourly electric power outputs and a sum of hourly heat outputs; and controlling a heat storage apparatus to store or output a certain amount of heat energy.

Abstract: A method and apparatus for optimally configuring a capacity of a high-proportion new energy system, a device, and a medium, which belong to the field of new energy system optimization and are used for solving the problems of insufficient flexibility of the high-proportion new energy system during the heating period and difficult consumption of renewable energy. The method includes: constructing a high-proportion new energy system structure; establishing a concentrating solar power (CSP) unit model and a combined heat and power (CHP) unit model based on the proposed structure; establishing a high-proportion new energy system collaborative optimization model based on the proposed unit models; acquiring relevant data of various units and renewable resource data; and obtaining a capacity configuration and operation optimization scheme of various units in the high-proportion new energy system according to the established model, thereby improving the renewable energy consumption of the system.

Abstract: A distribution network risk identification system and method and a computer storage medium include: multi-source information data for risk identification is acquired; the multi-source information data is analyzed and processed to obtain a risk characteristic; a risk identification index is calculated on the basis of the risk characteristic, and a state of a power grid is determined according to the risk identification index; a temporal and spatial variation rule and variation trend of the risk characteristic are analyzed; a location and cause of occurrence of a risk are determined according to the temporal and spatial variation rule and variation trend of the risk characteristic; a severity of the risk is analyzed by adopting an analogue simulation manner; and the severity of the risk is assessed, and risk early warning information is issued on the basis of an assessment result.

Abstract: A digital simulation system of a power distribution network, comprising: a client and a server end. The server end is a simulation server cluster composed of several simulation servers; the simulation server cluster and the client are mutually connected through a communication bus, wherein the client is configured to use a DCOM component to invoke a simulation service provided by the server end, and the server end is configured to distribute a task to be processed to each cluster node. Constructing the above-mentioned digital simulation system facilitates an optimal planning and operation of a smart power distribution network, thereby improving the utilization efficiency and reliability of the smart power distribution network and reducing the loss of a power outage.

Abstract: An embodiment provides a multi-time-scale Digital/Analog (D/A) hybrid simulation system and simulation method therefor for a complex power distribution network and a computer storage medium, and is intended to solve existing problems about multi-time-scale modeling and simulation of the complex power distribution network and simulation accuracy and efficiency of the complex power distribution network.

Abstract: A method of predicting the operation reliability of a distribution network, the method being based on an ARIMA model. By establishing an ARIMA model predict a user monthly power outage count; convert a non-smooth element outage count time series to a smooth time series; perform regression on only lagged values of a dependent variable, and on current values and lagged values of a stochastic error term, so as to establish a user monthly power outage count model; according to a prediction result sample an outage point, and at the same time, taking into account a real time load operating state, establish a failure mode effects table based on TLOC criteria and PLOC criteria; and calculate a system recovery time for each instance of device outage, and finally obtain a whole-year reliability index.

Abstract: A distribution network risk identification system and method and a computer storage medium include: multi-source information data for risk identification is acquired; the multi-source information data is analyzed and processed to obtain a risk characteristic; a risk identification index is calculated on the basis of the risk characteristic, and a state of a power grid is determined according to the risk identification index; a temporal and spatial variation rule and variation trend of the risk characteristic are analyzed; a location and cause of occurrence of a risk are determined according to the temporal and spatial variation rule and variation trend of the risk characteristic; a severity of the risk is analyzed by adopting an analogue simulation manner; and the severity of the risk is assessed, and risk early warning information is issued on the basis of an assessment result.

Abstract: An embodiment provides a multi-time-scale Digital/Analog (D/A) hybrid simulation system and simulation method therefor for a complex power distribution network and a computer storage medium, and is intended to solve existing problems about multi-time-scale modeling and simulation of the complex power distribution network and simulation accuracy and efficiency of the complex power distribution network.

Abstract: A digital simulation system of a power distribution network, comprising: a client and a server end. The server end is a simulation server cluster composed of several simulation servers; the simulation server cluster and the client are mutually connected through a communication bus, wherein the client is configured to use a DCOM component to invoke a simulation service provided by the server end, and the server end is configured to distribute a task to be processed to each cluster node. Constructing the above-mentioned digital simulation system facilitates an optimal planning and operation of a smart power distribution network, thereby improving the utilization efficiency and reliability of the smart power distribution network and reducing the loss of a power outage.

Abstract: A method of predicting the operation reliability of a distribution network, the method being based on an ARIMA model. By establishing an ARIMA model predict a user monthly power outage count; convert a non-smooth element outage count time series to a smooth time series; perform regression on only lagged values of a dependent variable, and on current values and lagged values of a stochastic error term, so as to establish a user monthly power outage count model; according to a prediction result sample an outage point, and at the same time, taking into account a real time load operating state, establish a failure mode effects table based on TLOC criteria and PLOC criteria; and calculate a system recovery time for each instance of device outage, and finally obtain a whole-year reliability index.