14 results about "Power-flow study" patented technology

The invention relates to a method and a system for detecting carbon metering equipment of a power system based on power flow, which solve the problems of large metering error, difficulty in quantification, non-traceability and the like in the prior art, and adopts the technical scheme that the method comprises the following steps of: connecting and initializing the system, and configuring detection task parameters; generating and outputting a test signal of a preset parameter; issuing a preset dynamic electric power carbon emission factor to the measured carbon metering equipment; actual carbon emission is calculated based on electric energy metering and the dynamic electric power carbon emission factor; electricity consumption data and carbon emission data output by the detected carbon metering equipment are collected, and theoretical carbon emission is calculated; and determining the detection qualification of the detected carbon metering equipment based on the comparison result of the actual carbon emission and the theoretical carbon emission. The method has the advantages that the accuracy, the consistency and the reliability of the distributed carbon metering device are evaluated and verified on line, and the credibility of carbon emission accounting of an electric power system is improved.

The invention relates to the technical field of power grid control, in particular to a power flow sample reactive adjustment method and system, and the method comprises the steps: DC flow experience switching, reactive relaxation scene setting and calculation, reactive switching based on a relaxation scene result, and verification after adjustment convergence. Compared with a traditional method of determining key nodes one by one and setting reactive unconstrained PV nodes, the method has the advantages that the PV nodes can be set in batches to quickly obtain a convergent power flow scene in single alternating current power flow calculation time, the method is used for guiding setting of reactive compensation values, and rapidity is achieved. And the potential excessive investment risk is counteracted and avoided by checking different types of reactive power switching in a single plant station, so that the practicability is ensured. The method is simple in logic, direction adjustment is guided based on a mature alternating current load flow calculation program, and adjustment is fast.

The invention relates to the technical field of intelligent power grids, in particular to a model simulation method for a power supply system and a storage medium. The method comprises the following steps: acquiring power transmission line data; performing electric power tide simulation according to the power transmission line data to obtain electric power tide data; performing cable aging anomaly detection based on the power flow data to obtain cable aging data; performing thermal breakdown risk prediction according to the cable aging data to obtain thermal breakdown data; dielectric layer structure degradation analysis is carried out based on the thermal breakdown data to obtain dielectric layer structure degradation data; performing main bus off-network detection based on the dielectric layer structure degradation data to obtain main bus off-network data; and carrying out sweep range analysis according to the main bus off-network data to obtain local bus off-network data and full bus off-network data. The fault recognition rate and the simulation response accuracy of the power supply system are improved based on the intelligent power grid technology.

To predict a power flow of a power system without inputting setting information of a system included in the power system.SOLUTION: A power flow prediction system includes: an acquisition unit configured to acquire system facility information indicating a verification target system included in a power system; an extraction unit configured to compare the system facility information acquired by the acquisition unit with actual data of the power system stored in a storage device, and extract the actual data of the power system from the storage device based on a comparison result; and a prediction unit configured to predict a power flow in the power system based on the actual data of the power system extracted by the extraction unit.SELECTED DRAWING: Figure 2

A power grid comprises at least one power unit to consume electric power from and / or provide electric power to the grid. A power change by the power unit causes a change in value of a first parameter

A power grid comprises at least one power unit to consume electric power from and / or provide electric power to the grid. A power change by the power unit causes a change in value of a first parameter

The invention discloses a power flow optimization method and device based on deep learning and a quantum genetic algorithm, terminal equipment and a storage medium, and belongs to the technical field of power flow optimization of a power system. Constructing a power flow model and constraint conditions by taking minimization of fuel cost, power loss and voltage deviation of a load bus as targets, and generating an initial quantum population which meets the constraint conditions and is provided with a plurality of quantum bits; wherein each quantum bit represents the output active power variation of one group of generators; and then, according to the initial power flow data and the initial quantum population, power flow solving operation is repeatedly executed, the optimal output active power variation of each generator is obtained, and output adjustment is carried out on each generator according to the optimal output active power variation. By implementing the method, the problem that the power flow optimization result cannot meet the overall optimization requirement when a traditional optimization method is used in the prior art can be solved.

A power transmission and distribution operations management system according to the present disclosure includes a node and branch integration unit that generates integrated installation data including both installations in a transmission system and installations in a distribution system, using transmission system installation data that are data about the installations in the transmission system and distribution system installation data that are data about the installations in the distribution system; and a power flow calculation unit that determines control quantities for the installations in the transmission system and the distribution system, using the integrated installation data, power supply and demand forecast data within the transmission system, and power supply and demand forecast data within the distribution system, for compliance with at least one of a current constraint or a voltage constraint.

This invention relates to the field of energy management technology, specifically disclosing a power supply and demand balance optimization system based on source-grid-load coordination. The system includes a data acquisition and prediction module, which acquires data from the distribution network and the external environment, and outputs prediction curves and confidence intervals; a power flow feasible region construction module, which generates a power flow feasible region based on the prediction curves and confidence intervals, and outputs a time-based constraint set; and a multi-time-scale rolling optimization module, which, within the power flow feasible region, simultaneously solves the time-based constraint set and uses a feasible region projection time-series scheduling algorithm for online rolling optimization; when the voltage proximity index is detected to exceed a preset threshold, a short-window re-optimization is initiated to optimize the power supply and demand balance. This invention satisfies network security and power supply and demand balance in distribution network scenarios with high penetration of distributed energy and coexisting uncertainties.

A method, apparatus, and system for determining a value of an electric power flow characteristic of an electric power grid are disclosed. The grid comprises at least one power unit configured to consume electric power from and / or provide electric power to the electric power grid. A power change by the at least one power unit causes a change in value of a first parameter of electric power flow in the electric power grid. The method comprises correlating a particular power change with at least one value of the first parameter at a first grid location and at least one value of the first parameter at a second grid location; determining a difference between the at least one value of the first parameter at the first grid location and the at least one value of the first parameter at the second grid location; and determining, based on the determined difference, a value of the electric power flow characteristic of the electric power grid.

The invention discloses an electric carbon metering simulation system for simulating full-link topology and a method thereof. The system comprises a power generation side panel, a power transmission and distribution side panel and a user side panel, and each panel comprises a plurality of meters and a plurality of acquisition terminals. And the meters are used for simulating real electric carbon meters on the corresponding sides, metering carbon emission and displaying electric carbon factors. The acquisition terminal is used for simulating a real electricity carbon acquisition terminal and acquiring an electricity metering quantity. The system executes the following operations: (1) if on-site to-be-simulated data exist, issuing the on-site to-be-simulated data to each panel, otherwise, issuing the multiplying power of the mutual inductor; (2) generating a full-link topology; (3) calculating the electric quantity through topological calculation, analyzing the power flow, calculating a node electric carbon factor, and issuing the node electric carbon factor to an acquisition terminal; and (4) calculating the carbon emission of the current node according to a formula. According to the method, the accuracy and timeliness of data are improved, the carbon emission conditions of different power production, transmission and consumption links are known more accurately, and a scientific basis is provided for optimizing resource allocation and improving the energy utilization efficiency.

A method, apparatus, and system for determining a value of an electric power flow characteristic (e.g. grid inertia or topology) of an electric power grid. The grid comprises a plurality of power units each configured to consume and / or provide power to the grid. A change in power causes a respective change in a value of a first parameter of electric power flow (e.g. frequency or voltage phase angle) in the grid. A computing system determines a first plurality of sets of event data generated by a respective first plurality of data generating devices, each associated with a respective power unit. Each set of event data is indicative of i) a change in power by the associated power unit and ii) a time of the change, within a first time window. The computing system determines grid response data indicating values of the first parameter during the first time window, and determines the value of the electric power flow characteristic based on the determined sets of event data and the determined grid response data.

The invention provides a power flow calculation model-based training sample generation method and apparatus. The method comprises the steps of obtaining a basic sample; randomly disturbing parameters of the indexes in the operation conditions, and correspondingly disturbing parameters of linkage indexes of the indexes in the operation conditions; performing power flow calculation on the disturbance sample by adopting a power flow calculation algorithm; when the load flow calculation result reaches a sample generation termination condition, determining the disturbance sample and the voltage of all nodes and the power of all nodes in the load flow calculation result as training samples of a power load flow calculation model; and when the load flow calculation result does not reach the sample generation termination condition, performing optimal load flow calculation by adopting the basic sample and the power grid optimization target, and determining the power grid structure and the optimal operation condition as a new basic sample so as to generate the load flow calculation result based on the new basic sample. And the generation efficiency of the training sample in the power flow calculation model is improved.

The invention proposes a power system frequency response prediction method based on a directed weighted graph convolutional network, and the method comprises the steps: encoding a power grid topology into a directed weighted graph according to a power flow calculation result, the directed weighted graph comprising a node set and an edge set, the node set being constructed based on bus nodes, and the edge set being determined based on a power transmission branch; a directed weighted graph convolutional network is constructed based on the directed weighted graph, and the directed weighted graph convolutional network comprises multiple directed weighted graph convolutional layers and a perceptron; inputting power grid operation data into the directed weighted graph convolutional network to extract graph embedding features, fusing the graph embedding features with scalar disturbance, and decoding through a multi-layer perceptron to generate a frequency track. According to the technical scheme of the embodiment of the invention, the rapid, accurate and generalizable prediction of the system frequency dynamic state can be realized by constructing the directed graph structure conforming to the physical characteristics of the power flow and designing a graph convolution message passing mechanism with clear physical significance.