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Under financing difficulties, asset securitization has the advantages of activating stock assets, enhancing credit, and isolating risk and is therefore a potential financing mode for renewable energy enterprises. This paper provides a systematical overview of asset securitization financing as it applies to renewable energy enterprises. The feasibility of such financing is first analyzed from the perspectives of the typical financing difficulties experienced by renewable energy enterprises, the underlying assets available for securitization, the legal and policy basis for such financing, as well as the history and current state of the practice in China and internationally. On this basis, three asset securitization mechanisms are proposed. Two case studies are conducted, which use a financing cost measurement model to show that asset securitization offers no cost advantage and that its main advantage lies in its high accessibility. Currently, asset securitization financing for China’s renewable energy enterprises faces many difficulties, including the inadequacy of government subsidies as underlying assets, the high risks and cost of asset securitization financing, the challenges of patent securitization, and imperfections of institutions and mechanisms. It is suggested for Chinese government that to ensure adequate revenue for renewable energy projects and reduce risks and cost, promote patent securitization and improve the basic institutions and mechanisms of securitization.

Currently, many low-carbon approaches are being applied in the power dispatching process, such as dynamic economic emission dispatch (DEED), wind power integration and carbon trading. Furthermore, these approaches may influence the carbon emission from electricity. To investigate such joint influence, this paper firstly builds a stochastic DEED model in the forms of chance-constrained programming related to wind power uncertainties. After that, the established model is transformed to a deterministic form by discussing relevant statistical characteristics. Next, an auxiliary decision-making method is designed to draw the optimal dispatching solution upon real-time price of carbon trading. Finally, empirical analysis shows that: (1) the minimization of carbon emissions and fuel costs comes at the expense of the reliability of wind power integrated system, for reasons that the decrement rate of thermal power output is about 60.8% from higher reliability level to lower level, (2) the decrement rate of carbon emissions (0.01%–0.012%) is superior to the growth rate of fuel costs (0.0011%–0.0022%) as the carbon trading price increases, which proves that carbon emission reduction can be effectively realized by carbon trading rather than substantial increase in fuel costs, and (3) carbon trading is conducive to the improvement of carbon emission efficiency.

Scientific prediction and accurate grasp of the future trend of population change are conducive to the formulation of different population policies at different stages, so as to alleviate the adverse effects of the aging population on society and provide scientific theoretical reference for controlling the population size and making policy. Considering that the population system is affected by many complex factors and the structural relationship among these factors is complex, it can be regarded as a typical dynamic grey system. In this paper, the fractional-order GM (1, 1) model and the fractional-order Verhulst model are established, respectively, based on the statistical data of China's population indices from 2015 to 2019 to forecast the population size and the change trend of population structure of China from 2015 to 2050 in the short-term and medium- to long-term. The forecast results show that China’s population will grow in an inverse S shape from 2015 to 2050, when the total population will reach 1.43 billion. Moreover, during this period, the birth rate and natural growth rate of population will decrease year by year, and the proportion of aging population and the dependency ratio of population will increase year by year. Besides, the problem of aging population is going to become increasingly serious. The application of grey system method to population prediction can mine the complex information contained in the population number series. Meanwhile, the fractional-order accumulation can weaken the randomness of the original data series and reduce the influence of external disturbance factors, so it is a simple and effective population prediction method.