Analysis of Key Factors Influencing Electrical Load Profiles

The electric power industry serves as a critical foundational sector in the energy domain and represents the lifeline of the national economy. For economic development, electricity takes precedence, and the development and construction of the power industry play a crucial role across various sectors of the nation. With the continuous expansion of installed generator capacity and ongoing development and construction of the power grid in China, the resulting fluctuations in electrical load become increasingly complex. Therefore, research on load forecasting becomes more and more important. This study employs regression analysis and variance analysis methods to analyze the determinants of power load fluctuations. By statistically studying multiple factors (such as temperature, humidity, wind speed, rainfall, etc.) affecting load size, this research establishes load forecasting models to guide real-time unit scheduling. Based on the load forecasting model, the factors with the greatest impact on power load are identified, and single-factor variance analysis is conducted on these factors to further determine their impact on the load. The case results presented in this paper further validate the effectiveness of the proposed forecasting model.