Investment Allocation Method for Distribution Networks Based on a Panel Data Model and an IncentivePenalty Mechanism

The scale of distribution network construction is huge and the differences in construction areas are significant.The accuracy of investment strategies would directly affect the effectiveness of upgrading distribution networks.In response to the current subjectivity and lack of precision in the distribution network investment allocation process, this study proposed a method to allocate the investment amount to distribution networks based on a panel data model and an incentive-penalty mechanism.First, the type of panel data model was selected using the joint hypothesis test and the Hausman test.Second, the initial allocation of the investment amount was calculated based on the selected panel data model.Third, investment productivity in each region in recent years was calculated using the data envelope analysis model.Given the variations in the importance of information during different periods, the concept of time degree was introduced to establish a time degree model.The weights of the model during different periods were assigned to the investment productivity and then the sum was calculated separately to obtain the comprehensive investment productivity of each distribution network.The final allocation of the investment amount for each distribution network was obtained based on its initial allocation of the investment amount and the comprehensive investment productivity.The case study showed the following points.(1) The differences among the distribution networks were significant and, thus, the fixed effects model could be employed to effectively compute the investment scale.(2) Given the differences in the construction and investment productivity of various distribution networks, the proposed method to calculate the complete investment productivity could be used to adjust the allocation of the investment amount and achieve an optimal allocation of funds.The research results exhibited practical significance in improving the investment allocation strategy of distribution networks.