Power System Load Forecast Analysis Based on Computer Neural Network Technology

As a pillar industry that guarantees economic development, the power system is closely related to the blood of national economic development. Therefore, strengthening power supply and ensuring the power demand of various industries and sectors has become a top priority to encourage national economic growth. This article mainly introduces the BP neural network (BPNN) and the bilinear search method under the computer neural network technology environment. This paper uses computer neural network technology to analyze and study power system load forecasting, and establish a potential bilinear search method model. The model is solved by the bilinear search method, and the power system load forecast analysis status is detected, and the model is revised using historical data to improve the accuracy of the power system load forecast analysis status detection. The test results in this document show that BPNN and two-line search methods improve the performance of a power load analysis system by 53% and reduce the level of false alarms and false alarm systems. Finally, by comparing state-of-the-art power system analysis with electrical system analysis, the system shows the computer effect of the power system on the system load analysis.