The mismatch between energy distribution and power load in China can be alleviated by inter-regional and inter-provincial power transactions. However, it also brings challenges to transaction settlement. In the new round of electric power reform, the transaction settlement deviation quantity needs to be more standardized. Based on the analysis of the related work, this article used the analytical framework of the analytic hierarchy process to calculate the transaction type weight, the inter-regional, and the inter-provincial weight, respectively, and accordingly, quantifies the amount of deviation quantity allocated by the corresponding trading subjects. According to the size and volatility of the trading quantity, we further propose a comprehensive weighting method based on kernel density and entropy weight to quantify the deviation quantity of inter-regional and inter-provincial trading subjects of different trading types. Specifically, this article first used the kernel function weighting method to calculate the weights of different transaction types that measure the transaction quantity, and then the improved entropy weight method was used to calculate the weights of different transaction types that reflect the volatility of the transaction quantity. Then, the comprehensive weights were constructed by considering the influence of the above two dimensions on the distribution of the deviation electricity simultaneously. The deviation electricity responsibility determination model was used to clarify the transaction subject's deviated electricity responsibility, and the deviated electric quantity calculation model was used for quantification. At last, the validity and practicability of the method were verified through the analysis of examples using the inter-regional and inter-provincial power transaction data from China.

There are many shortcomings in budget management under the ERP environment of power energy companies. Due to the large number of branches, the power energy company has experienced insufficient connection with some branches. Power energy companies must do a good job in the construction and application of the budget management system under the ERP environment, and need to optimize the existing problems. Therefore, the comprehensive budget of the power energy company is a subject to be further studied. It plays an important role in deepening the reform of the power energy company, accelerating its health transformation, reducing operating costs, optimizing resource allocation, and achieving strategic goals.

In the context of double carbon, it is an inevitable requirement for the low-carbon power industry to take economic efficiency and low carbon into consideration. This article introduces the carbon emission constraint into the economic dispatching of the power system. Then, combined with the blockchain theories, the methods of particle swarm optimization and multi-objective particle swarm optimization (MOPSO) are employed to simulate the economic and environmental scheduling of a power generation system based on six thermal power units. Research shows that the constraint processing approach is practical and effective, and it can firmly adhere to equality requirements, which is superior to other algorithms’ constraint processing methods; the algorithm is stable, and the global optimal solution can be determined under different initial solutions. In the process of multi-objective optimization, the solutions of POF obtained by using the slope method are evenly distributed.