Energy Profile Forecast Based on Multivariate Time Series

Energy is not only an important material basis for economic development and social progress, but also a significant factor affecting the living environment of human beings. First of all, we preprocess the raw data and screen out seven variables, then we bring them into two categories of conventional energy and new energy. Secondly, based on the linear positive correlation between new energy and conventional energy, the time series model is used to summarize the energy development trend. Thirdly, we use the analytic hierarchy process (AHP) to take the best state of energy using as the target layer, the clean energy as the criterion layer, the four states as policy makers, furthermore, we calculate the weight coefficient through judgment matrix, finally we come to California for the best clean energy using state. Finally, considering the population, climate, geographical environment and other influencing factors, we use the time series prediction model to predict the year 2025 and 2050.