Research on the optimal model for the evaluation of new power system investment projects based on the cloud model–DS evidence theory–TOPSIS method - Shun Ma; Ming Chen; Shiyan Mei (Energy Science & Engineering, 2024)
Abstract Considering that the traditional investment project evaluation system can no longer fully adapt to the characteristics of the new power system under the investment environment of the new power system, this study constructed a new power system investment project evaluation and optimization method based on the combination of the cloud model, evidence theory and the TOPSIS method. First, 16 evaluation indexes were considered based on four dimensions, namely green and low‐carbon, safe and reliable, flexible and intelligent, and economical and efficient, and the optimal evaluation index system of new power system investment projects was designed. Second, the normal cloud model was used to obtain the evaluation membership distribution of each index and turn it into evidence. Considering the conflicts between indicators and the combinational contradictions of traditional evidence theories, an improved DS evidence theory based on a game weight coefficient discount to reduce conflicting evidence was used to fuse the membership information of multiple indicators. On the basis of the evaluation results of each scheme, this study used the TOPSIS method to sort the advantages and disadvantages of each scheme. Finally, the project of planning and putting this model into operation in the 14th Five‐Year project database of a power grid enterprise was selected as an example to carry out empirical analysis, and the effectiveness and superiority of the proposed model were verified.