• Energy Research

To combat climate change, the Chinese government has implemented a package of policies to support the development of the biogas power generation industry. However, the promotion of biogas power generation technology in China is relatively slow. Therefore, it is of practical significance to study the promotion of biogas power generation technology against the background of policy support. In order to study the effect of policy on the promotion of biogas power generation technology, a system dynamics model is constructed in this paper. The results show that under the feed-in tariff subsidy policy, biogas power generation technology can be well promoted because it has good economic and environmental effects. In addition, if the biogas power generation technology is considered to participate in carbon emission trading, the carbon price also has a positive impact on the promotion of biogas power generation technology because it increases the perceived economic value of biogas power generation projects. Finally, this study can also provide reference value for the promotion of biogas power generation technology in other areas.

Currently, the reform of electricity cross-subsidies on the sales side is a crucial task in the market-oriented process. The resulting electricity prices, which reflect the true value, can not only enhance resource allocation efficiency but also contribute to increased carbon emissions. Consequently, it is imperative to actively pursue carbon trading policies to address this issue. In this study, we examined the reformed electricity prices for industrial and residential users by applying the Ramsey pricing model. Moreover, a recursive dynamic computable general equilibrium model is employed to analyze the carbon emissions and economic performance of the cross-subsidy reform under different settings of the quota decline scheme, quota allocation mode, and penalty mechanism within the carbon emissions trading scheme. The results demonstrate the following findings: (1) The calculated Ramsey prices for industrial and residential users are 0.541 and 0.792 yuan/kWh, respectively. (2) Implementation of the electricity cross-subsidy reform can lead to a significant increment in CO2 emission. However, it effectively improves national economic and social development and promotes the growth of gross domestic product, industrial output, and changes in residential consumption expenditure structure. (3) Carbon trading proves to be an effective means to achieve carbon emission reduction at a lower economic cost after the reform. Notably, the degree of impact is more sensitive to the carbon decline factor.

Abstract Government policies and investments in the photovoltaic power generation industry have contributed to the fast development of the photovoltaic power generation industry through technology push. But how does the research and development (R&D) investment affect the photovoltaic power generation industry, and what is its effect? This is a problem worthy of discussion. In order to answer this question scientifically, this paper constructs a system dynamics model to study the impact of R&D investment on China's photovoltaic power generation industry and analyzes the impact of other incentive policies such as Feed-in Tariff (FIT) on the photovoltaic industry. The results show that: firstly, R&D investment and FIT are conducive to the technological innovation of China's photovoltaic power generation industry. Secondly, a higher level of R&D investment can induce more cost reduction of photovoltaic power industry. Finally, the effect of FIT in promoting the growth of installed capacity of the photovoltaic power generation industry is more obvious.

With the process of economic transformation and structural adjustment, low-carbon development has become an intrinsic and realistic demand for China's national economic and social development. This paper builds a system dynamic (SD) model of China's low-carbon development based on the internal influencing mechanisms of carbon sources, carbon flows, and carbon sinks, and then explores the impact of carbon sources, carbon flows, and carbon sinks system on carbon emissions under different scenarios. The model in our study is effective and practical, and it can not only clearly demonstrate the interaction mechanism between various systems but also provide effective policy recommendations for policymakers. The results show that (1) with the steady growth of the economy, China's total energy consumption and carbon emissions have increased significantly. By 2025, the total energy consumption will reach 628 798 ten thousand tons, and the carbon emissions will reach 689 257 ten thousand tons; (2) as for energy and industrial structure, on the one hand, energy restructuring is more effective in reducing carbon emissions than is industrial restructuring; (3) carbon sinks also play an important role in reducing greenhouse gas emissions.

Abstract Renewable portfolio standards (RPS) is an institutional change from Feed-in Tariff (FIT) to government policy and market mechanism. Is it conducive to improve China's social welfare? Given this problem, this paper constructs the social welfare function under the FIT policy and RPS system respectively based on consumer heterogeneity and simulates the social welfare of China under the two schemes on the basis of combining the real economic situation of China. The results show that: (1) Based on China's real economic situation, the implementation of RPS has achieved Pareto improvement and improves China's social welfare. (2) Under the RPS, compared with the actual situation of oligopoly in China's electricity market, competition can improve social welfare better. (3) The effective implementation of RPS depends on the quota level of the government's scientific design. As far as China's current real economic situation is concerned, when the quota is set in the interval (0,0.5], the social welfare under the RPS is always higher than that under the FIT. Therefore, to improve social welfare and promote low-carbon energy transition, China should effectively promote the implementation of RPS, a mandatory institutional change, and strengthen the system construction of RPS.

A renewable portfolio standard is implemented to promote the development of renewable energy at a minimum cost through tradable green certificate market mechanism. Formulating a scientific and feasible renewable energy quota allocation scheme helps RPS function smoothly and optimize resource allocation. This paper proposed a bi-level programming model combined with entropy weight method to allocate renewable portfolio standard quotas with provincial heterogeneity and stakeholders' behavior, and an optimized quota allocation scheme among China's 30 provinces in 2020 was obtained. By comparing with the government's issued scheme, the following were the results under the optimized scheme: (1) Quotas in most provinces have increased, and the responsibility for renewable electricity generation is shared with the provinces with developed economy and well-constructed transmission facilities, where electricity producers can meet the quotas by purchasing tradable green certificate. (2) Quota allocation has positive effects on energy, economy, and environment. Specifically, the non-hydro renewable electricity generation increased by 43.8%, the non-hydro renewable electricity producers' profit increased by 18.4%, and the environmental pollution cost reduced by 27.9%. (3) Quota allocation equity measured by the environmental Gini coefficient increased by 14.3%. Based on these findings, some policy implications related to quota allocation and renewable portfolio standard's institutional arrangement have been put forward.

As a kind of renewable energy, biomass power has great development potential in mitigating greenhouse gas emissions. Therefore, under the background of carbon peak and carbon neutrality, the diffusion of biomass power generation technology has practical significance. To address these issues, this paper constructs a system dynamics model to study the impact of different policy effects on the diffusion of biomass power generation technologies. The results show that the feed-in tariff policy can significantly promote the installed capacity growth of biomass power generation projects; on the other hand, carbon emission trading increases the investment value of projects and promotes the growth of the installed capacity of biomass power generation projects, to a certain extent, so relevant policies need to be improved to achieve the promotion of biomass power generation technology in the future.

Government incentive policies play an important role in the promotion of distributed photovoltaic power. However, which policy is more effective for the diffusion of distributed photovoltaic power? This is a question that needs to be answered. Based on this, we combined the two-factor learning curve and system dynamics model to study the dynamic diffusion process of China's distributed photovoltaic power (DSP). The results show that (1) the coefficients of learning by doing and learning by researching for DSP are 0.0435 and 0.2971 respectively. This indicates that technological innovation caused by R&D expenditures in the DSP is the driving force for cost reduction. (2) Both demand-pull and technology-push policies contribute to the diffusion of DSP; (3) the effect of FIT policy on the diffusion of distributed photovoltaic technology is more significant than that of R&D policy; and the reduction of production cost of photovoltaic power industry by R&D policy is more significant than FIT policy.

Abstract At present, China’s PV industry is experiencing a policy-driven to market-driven transition. Whether the endogenous driving force for China’s PV industry output growth has been changed is a question of substantial concern? To scientifically answer the question of the endogenous driving force of the output growth of China’s PV industry, we empirically analyse the driving force of China’s PV industry output growth by constructing an expanded Cobb-Douglas technology production function. The results demonstrate that the output elasticity of research and development (RD The contribution rate of R&D input to output growth exceeds physical capital and labour factors, indicating that the endogenous driving force of China’s PV industry output growth has changed from factor-driven to technological innovation-driven.

Currently, China is facing severe pressure of environmental emission reduction. As a kind of clean energy, waste-to-energy technology has the advantages of renewability, low pollution, and stable supply. To establish an affordable, effective, and sustainable waste disposable method is critical for the low carbon society transition. Therefore, the innovation diffusion of waste incineration power technology is a problem worth studying. Based on this, in order to answer this question scientifically, this paper constructs a system dynamics model of innovative diffusion, and analyzes the internal mechanism of innovation diffusion. The results show that firstly, the government support policies have a positive influence on the innovation and diffusion of waste incineration power technology; secondly, compared with the R&D policy, feed-in tariffs policy is more efficient to expand the installed capacity of waste incineration power; At last, technological innovation caused by government support policies is the main driving force of waste incineration power industry investment cost reduction.