Power load prediction method and device, electronic equipment and storage medium

Abstract

The invention provides a power load prediction method and device, electronic equipment and a storage medium, and relates to the technical field of micro-grid management, and the method comprises the steps: obtaining the user feature information of a first user in a micro-grid, the power load of the first user at a current date, and the environment information of the first user, wherein the environment information comprises a geographic position, climate information and/or a date type of a current date; and taking the user feature information of the first user, the power consumption load of thefirst user on the current date and the environment information of the first user as a trained power load prediction model to obtain a predicted power consumption load of a specified day output by thepower load prediction model. The problems that in the prior art, the load law is difficult to grasp, and prediction is inaccurate and easy can be solved, and the safety and stability of a microgrid system can be improved.

Description

technical field [0001] The present application relates to the technical field of microgrid management, in particular, to a power load forecasting method, device, electronic equipment and storage medium. Background technique [0002] With the improvement of my country's industrial structure and the improvement of people's overall living standards, the demand for electric energy is increasing year by year, and due to the simultaneity of electric energy production and consumption, higher requirements are put forward for smart distribution network, smart microgrid and layout. The short-term load forecasting results of the power system in the microgrid environment are related to the formulation of power system dispatching and production plans, as well as the cost of power generation, but the factors that affect the power load include weather factors such as temperature and precipitation, as well as holidays, industrial economic activities, etc. The randomness and uncertainty of t...

AI Technical Summary

Problems solved by technology

The short-term load forecasting results of the power system in the microgrid environment are related to the formulation of power system dispatching and production plans, as well as the cost of power generation, but the factors that affect the power load include weather factors such as temperature and precipitation, as well as holidays, industrial economic activities, etc. The influence of human factors, such as randomness and uncertainty of these factors, lead to great difficulties in the prediction of power load

At present, in the power system load forecasting in the microgrid environment, there are uncertainties in the influencing factors, which makes it difficult to grasp the load law, and inaccurate load forecasting will easily affect the security and stability of the microgrid system.

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