3 results about "Line flow" patented technology

The application relates to the technical field of optimal scheduling of distributed power grids, and specifically discloses a two-stage optimal scheduling method for distributed power grids based on a probabilistic power flow and a WOA-PPSO algorithm, which comprises the following steps: constructing a probabilistic power flow model, calculating the probability distribution characteristics of node voltage and line flow in the power grid containing wind power, photovoltaic power and load randomness based on the semi-invariant method and Gram-Charlier series expansion. The application introduces the probabilistic power flow modeling into the optimization constraint of the scheduling algorithm, and responds to the uncertainty that may exist in the power grid in real time; by constructing a two-stage scheduling algorithm, the global optimal scheduling plan is generated based on the WOA algorithm in the day-ahead scheduling, and the deviation caused by the uncertainty is quickly responded on the basis of the optimal scheduling plan in the real-time scheduling of the day; and the result of the day-ahead scheduling is taken as the reference starting value of the real-time scheduling of the day, and the projection method is combined with the PSO algorithm to construct the PPSO algorithm, so that the solving speed in the real-time scheduling of the day is maximally improved.

The application relates to the technical field of optimal scheduling of distributed power grids, and specifically discloses a two-stage optimal scheduling method for distributed power grids based on a probabilistic power flow and a WOA-PPSO algorithm, which comprises the following steps: constructing a probabilistic power flow model, calculating the probability distribution characteristics of node voltage and line flow in the power grid containing wind power, photovoltaic power and load randomness based on the semi-invariant method and Gram-Charlier series expansion. The application introduces the probabilistic power flow modeling into the optimization constraint of the scheduling algorithm, and responds to the uncertainty that may exist in the power grid in real time; by constructing a two-stage scheduling algorithm, the global optimal scheduling plan is generated based on the WOA algorithm in the day-ahead scheduling, and the deviation caused by the uncertainty is quickly responded on the basis of the optimal scheduling plan in the real-time scheduling of the day; and the result of the day-ahead scheduling is taken as the reference starting value of the real-time scheduling of the day, and the projection method is combined with the PSO algorithm to construct the PPSO algorithm, so that the solving speed in the real-time scheduling of the day is maximally improved.

The present application relates to the technical field of flow calibration, and discloses a multi-pipeline flow collaborative calibration system. The system comprises six modules, namely, flow characteristic acquisition, flow category classification, sequence analysis, trend analysis, correction and collaborative decision. The flow characteristic acquisition module acquires current flow data and real-time characteristic information of the multi-pipeline and indexes a historical flow data set; the flow category classification module classifies the historical characteristic information to obtain multiple flow categories, extracts relevant information to obtain a historical calibration score set; the sequence analysis module sequences the historical calibration score set and sorts it according to time to form a historical flow sequence; the trend analysis module analyzes the historical flow sequence to obtain a flow change rate and a stability deviation rate; the correction module matches the real-time characteristic information with the flow categories and corrects the above rate values according to the deviation; and the collaborative decision module makes a multi-pipeline collaborative calibration decision based on the corrected data, generates and executes a flow calibration scheme, and helps to accurately control the flow of the multi-pipeline system.