This invention relates to the field of power
system data analysis and
energy management technology, specifically to a
system and method for real-
time data acquisition and forecasting of
electricity user
energy consumption. It collects multi-source heterogeneous data from the user side in real time, and after
standardization, cleaning, and time-series alignment, fuses the data based on a unified
data model to construct a correlated data cube. This allows for the construction and dynamic updating of digital twin models for
electricity users, simulating their
electricity consumption characteristics and
market behavior. A multi-timescale collaborative forecasting mechanism is activated to generate short-term, medium-term, and long-term electricity demand and
electricity market price forecasts, and to formulate trading strategies accordingly. By feeding back actual transaction and market data, the
model parameters and forecasting strategies are continuously optimized. This effectively solves the problem of limited accuracy in
energy consumption and market forecasting caused by insufficient fusion of multi-source heterogeneous data and lack of collaborative analysis, significantly improving the accuracy of load and
electricity price forecasts.