Multi-scenario investment forecast of new energy projects based on multiple linear regression and comprehensive evaluation model of differentiated project priorities

Abstract

As China's resource shortage and environmental pollution intensify, the demand for new energy and electric energy substitution is becoming higher and higher. Accurately predicting the investment scale of China's new energy projects is of great practical significance for improving the efficiency of resource allocation and economically meeting energy demand. This paper builds a scientific and precise investment model for new energy projects from both macro and micro perspectives. First, from a macro perspective, considering macro indicators such as the external environment and internal economy, an annual total investment forecast model based on multiple linear regression is constructed, in order to predict the annual total investment scale of new energy investment entities and achieve preliminary accurate investment; second, designed the evaluation index system of different project priorities from three perspectives of external environment, internal development of enterprises and social development, and constructed the comprehensive weight design method based on AN-EWM and the comprehensive evaluation method of TOPSIS, in order to realize the priority of differentiated projects. Sorting; finally, a new energy project located in a city in northern China is selected as the research subject, and a multi-scenario example analysis is carried out. The results show that the new energy project investment scale index system constructed in this paper can effectively evaluate the investment capacity of the main body of the new energy project, and can better predict the total investment of the new energy investment project, so that the deviation rate can be controlled within 5 %, and the priority evaluation model constructed in this paper can provide a complete calculation method and a reference method for the judgement of the investment priority, which can promote accurate investment.