The invention discloses a base line prediction and optimization method based on a non-demand response factor, and the method is characterized in that the method comprises the following steps: 1) determining alternative non-demand response factors; 2) calculating the relevancy of all alternative non-demand response factors with a load; 3) building a characteristic quantity matrix, and building a characteristic quantity matrix according to a demand corresponding day; 4) calculating the relevancy and determining a similar day; 5) respectively employing a similar day weighting method, a multiple linear regression method and an RBF nerve network method to calculate the base line; 6) employing a combined calculation model to carry out calculation, and obtaining a final base line prediction value. The beneficial effects of the invention are that the method gives full consideration to the impact on the characteristics of a user load and base line prediction from the non-demand response factors, and greatly improves the accuracy of demand response base line prediction through the steps (the mining of the non-demand response factors, the selecting of a similar day and the calculating of the base line) and employing the advantages of the combined calculation model comprehensive weighting method, the multiple linear regression method and the RBF nerve network method.