New energy power station power prediction system based on cloud-side cooperative computing

Abstract

The invention discloses a new energy power station power prediction system based on cloud-side cooperative computing, which comprises a power prediction terminal based on edge computing, a monitoringterminal and a cloud, and is characterized in that the power prediction terminal based on edge computing is connected with the monitoring terminal, the cloud, a power dispatching mechanism and an APPin mobile equipment; wherein the power prediction terminal based on edge computing is provided with a four-core CortexA53 processor, a serial port, an industrial Ethernet interface, a ZIgBee / LoRa module interface and an Internet of Things card; an irradiance sensor, a temperature sensor, a humidity sensor, a wind speed sensor and an air pressure sensor in the new energy power station are connectedwith a power prediction terminal based on edge calculation through a serial port, an industrial Ethernet interface and a ZIgBee / LoRa module interface. The irradiance sensor, the temperature sensor, the humidity sensor, the wind speed sensor and the air pressure sensor are used for collecting microclimate real-time data, the microclimate real-time data comprises irradiance, temperature and humidity, air pressure and wind speed, and the microclimate real-time data is sent to the cloud through the Internet of Things card.

Description

technical field [0001] The invention relates to the technical field of new energy power station power prediction grid connection, in particular to a new energy power station power prediction system based on cloud-edge collaborative computing. Background technique [0002] In order to realize the power prediction of new energy (wind power, photovoltaic) power stations, realize the orderly arrangement of power dispatching power generation plan and the consumption of new energy power generation, all new energy stations are equipped with power prediction systems. At present, the new energy station power prediction system at home and abroad connects the numerical weather forecast, local micro-meteorological data, real-time active power data of substation grid connection points, historical data, etc. to the new energy station prediction server, and uses physical and statistical methods to predict the power prediction value of the new energy station. ; Due to factors such as limite...

AI Technical Summary

Problems solved by technology

At present, the new energy station power prediction system at home and abroad connects the numerical weather forecast, local micro-meteorological data, real-time active power data of substation grid connection points, historical data, etc. to the new energy station prediction server, and uses physical and statistical methods to predict the power prediction value of the new energy station. ; Due to factors such as limited computing resources, complex algorithms, heavy computing workload, and long computing time, there are disadvantages such as long prediction time and low accuracy, which bring great difficulties to power grid dispatching power planning and new energy consumption. The continuous increase of new energy stations requires the power prediction accuracy of new energy stations to be greatly improved and the prediction time to be greatly shortened, which is conducive to improving the power grid's ability to absorb new energy and achieve energy conservation and emission reduction; the current power prediction system accuracy and prediction time scale are difficult Meet the requirements of new energy development and improve the power grid consumption capacity

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