5 results about "Power-flow study" patented technology

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.

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.

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.