The implementation of measures to limit electricity consumption in many provinces of China has caused coal prices to rise irrationally, further aggravating the financing problems of small and medium-sized enterprises in the supply chain. Small and medium-sized enterprises lacking funds cannot effectively participate in the green transformation and development of the coal industry, which slows down the sustainable development process of the coal industry. Under the current background of low-carbon advocacy, blockchain technology can reasonably allocate resources and efficiently process information, thereby providing a solution for this financing problem. This paper first proposes a coal accounts receivable financing model based on blockchain technology, then builds a coal accounts receivable financing system dominated by ports through blockchain technology. Finally, the Stackelberg yield–benefit model is used to analyze the income function of each participant in the process of accounts receivable financing. The results show that the use of blockchain technology can reduce the financing condition of financial institutions and improve the maximum income of cooperative enterprises in the chain while solving the financing problems of small and medium-sized enterprises in the coal supply chain. This study provides practical significance and theoretical value for promoting the transformation and upgrading of coal enterprises and accelerating the opening of the sustainable development model of the coal industry.

This paper starts from the purpose of assisting electricity market entities to make better decisions, providing guidance for the design and selection of retail packages, improving market efficiency, and guiding the healthy development of the market, and considering the future development trend of the electricity retail market, designs an optimal package decision model under the background of competitive electricity retail market. The model can be based on retail customers' electricity consumption information and risk preference analysis and select the optimal retail package that meets their needs from the retail package library. Finally, an example is used to illustrate the package decision-making process that considers the consistency of the customers' power consumption curve and the time-of-use electricity price and considers the market transaction needs of different customers in the electricity retail market.