39results about "Apparent power measurement" patented technology

The invention discloses an intelligent load monitoring system of a safety type electric energy metering box, which comprises a data acquisition layer, a data transmission layer, a data intelligent processing layer and an application layer, and is characterized in that the data acquisition layer is provided with an intelligent electric meter, a high-precision sensor and an electric energy quality analysis layer, and the data transmission layer comprises a protocol conversion module, an edge conversion module and a communication module; the intelligent data processing layer comprises data access, data processing, data storage, load analysis and intelligent processing, the application layer comprises real-time monitoring, alarm, management, energy efficiency analysis and report, and the electric energy metering box carries out real-time data monitoring on all components in the metering box, collects detailed energy consumption data in each time period, and carries out real-time monitoring on all the components in the metering box. And the collected real-time data is uploaded to the terminal, and is calculated, classified and counted into a table, so that the real-time load condition of each component in the electric energy metering box can be known in time, and the service life of the electric energy metering box is greatly prolonged under the condition that the long-time safe use of the electric energy metering box is ensured.

The invention provides an industrial load decomposition method based on harmonic coupling and nonlinear feature fusion, and belongs to the technical field of intelligent power grid monitoring. The method comprises the following steps: acquiring an electrical signal at a main power supply of an industrial load; basic electrical characteristics are extracted based on the electrical signals, and a basic characteristic set is constructed; geometric mean features are determined through the basic electrical features, and a geometric mean feature set and a multi-time scale geometric mean feature set are constructed; combining the basic feature set, the multi-time scale geometric mean feature set and the geometric mean feature set to construct a fusion feature set; training a long-short-term memory network by using the fused feature set; and performing non-intrusive industrial load energy consumption monitoring by using the trained long-short-term memory network. According to the method, the long-short-term memory network is trained by fusing the feature set, and the trained long-short-term memory network set is utilized to carry out non-intrusive load monitoring, so that the energy consumption of each load in the industrial load can be more accurately detected, decomposed and evaluated.