Renewable Energy Quota Research Articles

Analysis of the impacts of carbon neutral policy portfolios on the economy, environment, and residents' welfare based on computable general equilibrium models

The efficacy of the synergistic interplay of various programs about energy efficiency and emission reduction in China's endeavor to achieve carbon peaking and carbon neutrality remains to be determined. This research constructed a computable general equilibrium (CGE) model to examine the economic, environmental, social, and energy consequences of various policy combinations. Using data from the 2018 input-output table of China, we create 21 industry sectors and examine the combined impacts of different carbon policies. Our findings indicate that the effects of carbon emission reduction are more favorable when multiple carbon-neutral policies are implemented together, compared to the impact of a single policy. Among the various combinations of policies examined, the combination of feed-in tariff subsidy policy (FIT), renewable energy quota policy (RPS), carbon trading, carbon tax, and carbon capture, utilization, and sequestration (CCUS) technology proves to be the most effective. The study predicts that by 2060, this combination of policies could lead to a reduction of 32.5% in carbon dioxide emissions. At the same time, it was discovered that a combination of lower-intensity renewable energy quotas, carbon trading, carbon taxes, and higher-intensity subsidies for carbon capture, utilization, and storage (CCUS) technologies, the synergy indicator θ exceeds 1, indicating a more stable economy; When the carbon tax policy is more robust, and the remaining three policies are more minor, carbon emissions fall the most and are the most ecologically beneficial. Imposing excessively high renewable energy quotas while maintaining the same level of technology and substitutability between fossil fuels and electric energy sources will result in economic instability afterward. Therefore, we suggest that to attain balanced growth of the environment, society, and economy, the government should increase the function of policy combinations and balance several objectives.

How to promote the trading in China's green electricity market? Based on environmental perceptions, renewable portfolio standard and subsidies

The behavior evolution of market players is crucial to promoting green electricity trading. This paper develops an evolutionary game model of China's green electricity market to analyze the strategic interactions among players. The model incorporates key variables such as renewable energy subsidies, renewable energy quotas, and environmental perceptions. Then, a system dynamics simulation model is constructed, and simulation experiments are designed to reveal the influence of key factors on the evolutionary path. The results indicate that: (1) Players exhibit varying sensitivities to green electricity prices under different trading modes. (2) Renewable energy projects with high subsidy intensity have no willingness to enter the market if the benefits of participating in the green electricity market cannot surpass subsidies. (3) The evolutionary stabilization trend depends on users' environmental perceptions, and the environmental perception effect exhibits a diminishing marginal trend. (4) The implementation of renewable portfolio standard is an effective way to promote green electricity trading, especially when there is a high green electricity premium. (5) There is a trade-off between low incentive participation and high incentive coefficients in the system. These findings provide valuable policy recommendations for effectively promoting green electricity trading in China.

Cross-regional green certificate transaction strategies based on a double-layer game model

With the implementation of the renewable energy quota system and the development of the green certificate market, the diversification of cross-region trading subjects has brought about the problem of complicating the competition and cooperative relationship between multiple subjects. This problem makes it difficult to balance the conflict of interests of multiple participating subjects in green certificate transactions, and reduces the enthusiasm for trading. To this end, this paper proposes a multi-participant decision model of cross-regional green certificate trading behavior that takes into account the uncertainty of renewable energy generation. In the model, in order to explore the potential full set of strategies of the participating subjects, the cooperative game theory is utilized to analyze the complex interaction between multiple participating subjects in the cross-regional transaction, and the cooperative game model based on green certificates is established. As the participating subjects' information about other participants and their knowledge of the game environment are limited, the decision-making behavior is uncertain. In order to more reasonably portray the subject's game behavior in the actual decision-making scenario and to solve the defect that the traditional evolutionary game model can not reflect the influence of uncertain factors, we use the stochastic evolutionary game theory to dynamically deduce the cooperative strategies of the participating subjects under the limited rationality, and at the same time, introduce the strategy influencing factors to explore the dependence relationship between strategies. In addition, in order to cope with the impact of power generation uncertainty on cross-regional trading and to solve the defects of distributionally robust fuzzy set construction which is subjective and only for the analysis of uncertainty in a single time section, it is proposed to use Bayesian multivariate nonlinear model and mixed-effects model to construct probability distribution fuzzy sets of wind and light power generation uncertainty on the basis of distributionally robust theory. Finally, based on the arithmetic example, the cooperative strategy of multi-participants in cross-regional transactions under finite rationality is deduced, and the impact of uncertainty factors on the cooperative strategy is analyzed.

Supply chain coordination mechanisms of coal power enterprises under renewable energy quota system: A perspective of game analysis

The renewable energy quota system has become an important policy tool for countries around the world to solve the differences in renewable energy resource endowments between regions and promote the transformation of energy structure. How to coordinate the supply chain of power generation enterprises from the micro level of enterprises has become a key issue to ensure the implementation of renewable energy quota system. By constructing a game analysis model, this research studied the coordination game problem between the supply chain of coal power enterprises and renewable energy enterprises, and compared and analyzed the differences in decision-making between centralized and decentralized situations. The results illustrate that in the case of centralized decision-making, although renewable energy enterprises and coal power enterprises can guarantee profits and carbon emission reduction effects. However, in the real situation of independent rational economic man, it is difficult to ensure the real realization of centralized decision-making. Further, the research proposed that in the case of decentralized decision-making, the negotiation mechanisms of revenue sharing, cost allocation, and revenue sharing + cost allocation were used to solve the supply chain coordination problem of renewable energy enterprises and coal power enterprises. The equilibrium solution of the game model under different negotiation mechanisms is obtained. Finally, the results of theoretical analysis were verified by practical examples and the corresponding sensitivity analysis is carried out. The conclusion has decision-making reference value for solving the coordination problem between coal power enterprises and renewable energy enterprises, improving the overall income of supply chain and carbon emission reduction, and effectively promoting the implementation of renewable energy quota system.

Synergistic effects of carbon cap-and-trade and renewable portfolio standards on renewable energy diffusion

Carbon cap-and-trade mechanisms (CCT) and renewable portfolio standards (RPS) have been identified as effective administrative instruments for steering the conduct of electricity generation and promoting the adoption of renewable energy sources. However, the synergistic effects of these policies are often overlooked, and static implementation can limit their effectiveness. To address these gaps, this study employs a dynamic CCT and RPS framework, utilizing complex network evolutionary game theory to examine their influence on renewable energy diffusion. The findings reveal a distinct synergy between CCT and RPS in enhancing renewable energy diffusion, although these policies may occasionally result in redundancy or conflict. A static CCT combined with a dynamic RPS demonstrates greater efficacy in promoting renewable energy diffusion, while a dynamic CCT does not consistently increase renewable energy adoption. Additionally, renewable energy quota standards facilitate higher levels of diffusion. In perfectly competitive markets, renewable energy diffusion is more effective than in monopolistic environments. These insights offer valuable policy suggestions for stimulating renewable energy diffusion and expediting high-quality, low-carbon transitions.

Is cleaner more efficient? Exploring nonlinear impacts of renewable energy deployment on regional total factor energy efficiency

Improving the deployment and penetration of renewable energy is considered to be the fundamental way to solve environmental problems, but whether higher penetration of renewable energy means higher energy efficiency remains to be empirically tested. To reveal the relationship between cleanliness and efficiency in the energy sector, this paper first uses the three-stage data envelopment analysis (DEA)method to measure the total factor energy efficiency (TFEE) of 30 provinces in China, and then applies static and dynamic panel threshold regression (PTR)models to estimate the nonlinear effect of renewable energy share on TFEE. The results show that renewable energy is usually beneficial for improving TFEE, but there are prominent heterogeneity and nonlinear characteristics in net electricity exporting and net electricity importing provinces. Renewable energy in low rather than high regimes can significantly improve energy efficiency, indicating that provinces with lower levels of economic development and energy consumption receive higher marginal energy efficiency and are more likely to achieve sustainable development goals. More renewable energy quotas should be given to economically developed and high energy consuming provinces, and comprehensive energy efficiency guarantees and improvement measures must be provided to achieve optimal emission mitigation.

How to optimize allocation of renewable portfolio standards for renewable energy development in China?

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.

Forestry products as renewable energy sources

Forestry products as renewable energy sources

Carbon abatement of electricity sector with renewable energy deployment: Evidence from China

The fundamental way for China to achieve carbon peak and carbon neutrality is to continuously improve the penetration of renewable energy (RE) in the power system and establish an electricity mix dominated by RE power. According to China's 14th Five-Year Plan, the proportion of non-fossil energy power generation should reach about 39% by 2025. However, the impact of the increase in share of RE power on carbon emissions of the electricity sector remains to be estimated. To this end, the purpose of this paper is to capture the nonlinear characteristics of RE on electricity-related carbon emissions by using panel smooth transition regression (PSTR) model and provincial panel data covering the period 1991–2020 under the background of provincial RE quota system. The estimation results indicate that, (i) in the four transition variables of PSTR model such as the installed capacity of power generation, substation equipment capacity, total electricity consumption and total power generation, the nexus between RE deployment and electricity-related carbon emissions was detected as nonlinear. (ii) The heterogeneous RE carbon abatement effect is reflected in its increasing penetration in provincial power systems. (iii) Carbon abatement performance of RE generation decreases in the negative range with the increase of transition variables. (iv) The estimation coefficient of RE is positive at the higher value of the transition variable in the PSTR model of carbon emissions per capita. As a result, the RE quota with the best emission abatement performance should be designed based on the provincial power resource endowment and the medium and long-term expected electricity consumption.

Research on Carbon Peak Prediction in Electric Power Industry Based on DeBruyn and System Dynamics Model

As a critical field of carbon emission, the clean and low-carbon transformation of power industry is extremely critical to the smooth realization of country’s "dual carbon" goal. From the perspective of the whole power industry chain, the DeBruyn decomposition method was firstly used to determine critical influence factors of carbon emission in the power industry. Next, the response relationship between the influence factors and carbon emission was established. Finally, the peak value and its occurrence time under various scenarios were identified through designing four typical scenarios. The obtained results demonstrated that, under the context of interactive influence among positive driving factors (population size, thermal power generation, industrial structure, GDP), negative driving factors (forest area, energy structure, science and technology investment) and other factors, the carbon-emission amounts of the power industry under baseline scenario were increased continuously; conversely, the peak value of carbon emission under two single carbon reduction policy scenarios (i.e. carbon trading policy and renewable energy quota policy) and their composition scenario would become decrease, being 5.46×109 tons, 5.61×109 tons and 5.16×109 tons, respectively. Correspondingly, the occurrence time of peak value under three scenarios was in 2029, 2029 and 2028, respectively.

Optimized allocation of renewable energy quota in Chinese provinces

A fair and efficient renewable energy quota allocation scheme is essential for China to implement the Renewable Portfolio Standards policy. Therefore, based on the principles of fairness and efficiency, this paper comprehensively considers the differences among provinces and then proposes and adopts an improved zero-sum gains data envelopment analysis method to reallocate quotas. Furthermore, for verifying the superiority of the proposed method, this paper establishes a composite index based on the Gini coefficient and the Theil index to compare the rationality of the distribution results. Finally, this paper discusses the relevant advice for the development of renewable energy. The results validate that the proposed method is superior to the traditional method. Additionally, according to the final quota distribution scheme, there are fewer renewable energy quotas in the northern provinces and more in the southern provinces. The quota of most provinces is lower than 50 × 109 kWh, while Guangdong, Sichuan, Yunnan, Jiangsu, and Hunan are the five provinces with the most renewable energy quota of over 100 × 109 kWh. In general, this study provides a more rational renewable energy quota redistribution approach, which will help the government to establish an efficient and fair mechanism of renewable energy quota allocation.

Influence mechanism of renewable portfolio standard on energy producers

Renewable energy Portfolio Standard (RPS) policy plays a significant role in reducing carbon dioxide emissions and promoting the development of renewable energy. Based on bounded rationality, this paper constructed an evolutionary game model to analyze energy power production decision-making, involving both fossil and renewable power producers as participants. Through the discussion of evolutionary game equilibrium, the study revealed the following findings: (1) marketised TGC price benefits the reduction of fossil energy power production: (2) Tire implementation of RPS policy does not necessarily lead to an increase in total renewable energy production; (3) Under RPS policy, the higher proportion of renewable energy quota is not always advantageous for reducing fossil energy power production.

Investment and Production Strategies of Renewable Energy Power under the Quota and Green Power Certificate System

In order to study the impact of a renewable energy quota and green power certificate system on the strategies of energy suppliers, this paper constructs a multi-stage game model of renewable energy power investment and production from the renewable energy interest chain and its stakeholders. Through the calculation and solution of the model, the optimal renewable energy utilization level, pricing and production strategies of renewable energy power of energy suppliers are calculated under the scenarios of direct sale of power and purchase and sale by power grids. The results show that the quota ratio, green certificate price and investment cost are the key influencing factors of energy suppliers’ strategies, and changes in the values of the three factors will completely change the renewable energy investment, pricing and production levels of energy suppliers in equilibrium. In addition, the study found that the impact of the renewable energy quota on renewable energy utilization levels of energy suppliers depends on the relative size of investment cost and green power certificate price. At the same time, it was also found that with a change in investment cost, green power certificate price and user preference, the market share and renewable energy utilization level of traditional energy suppliers and new energy suppliers also change.

How dynamic renewable portfolio standards impact the diffusion of renewable energy in China? A networked evolutionary game analysis

Renewable portfolio standard is an effective administrative tool to guide the behavior of electricity producers and impact the renewable energy diffusion. However, currently the renewable energy quota is generally set to be static and the efficiency is limited. In this paper, we proposed a dynamic renewable portfolio standard policy and we aimed to analyze how it will impact the renewable energy diffusion in China. The connections between electricity producers were simulated under both the perfectly competitive market and monopoly market. And a networked evolutionary game approach is applied considering dynamic linking between the electricity producers. The results show that dynamic quota policy is effective in promoting the proportion of wind power generation from 20% to 59.17% and promoting the proportion of solar power generation from 20% to 79.25%. With the sensitivity analysis, we found that renewable energy quota and the on-grid price are the most influential parameters. The proportion will reach 76.47% if quota is 0.7 and 68.1% if on-grid price is 630 Yuan/MWh. And the influence of tradable green certificate prices and generation cost is limited in promoting renewable energy diffusion. This paper offers the Chinese government a potential implementation for the perfection of national renewable energy diffusion.

A Methodological Proposal for Implementing Demand-Shifting Strategies in the Wholesale Electricity Market

The energy transition has shown that fossil generation can be complemented with renewable energy and other resources capable of providing flexibility to the energy system’s operation, in compliance with the wholesale electricity market’s rules. This paper proposes a market-based methodology for introducing flexible demand in the energy dispatch, optimizing the scheduling of electricity system operation in the short-term, and considers the challenge of implementing an incentive scheme for participants in demand-response programs. The scheme includes the criteria of the elasticity of substitution and a renewable energy quota. This methodology is focused on a strategic demand shift to minimize the cost of supply; increase the dispatch of renewable energy; control CO2 emissions; and satisfy the generation, demand, and transmission operating constraints. These conditions encourage the development of a simulation tool that allows a sensitivity analysis to aid decision-making by operators and agents. The proposed methodology optimizes the operational cost of generation supply and specific performance indicators to determine the percentages of demand shift, the amount of CO2 emissions, the ratio of unserved power, the demand benefits obtained from an incentive scheme, and the natural market behavior.

Research on Trading Optimization Model of Virtual Power Plant in Medium- and Long-Term Market

In the medium- and long-term market, the power generation side and the power purchase side ensure to avoid the fluctuation of delivery prices through the medium- and long-term power contract, to avoid some market risks. This paper combines virtual power plants to aggregate distributed renewable energy to participate in market transactions. Firstly, this paper analyzes the two operation modes of power markets and combs the transaction varieties and modes in the medium- and long-term market. Secondly, the common contract power decomposition methods in the medium- and long-term market are analyzed, and the revenue model of virtual power plants is established. Then, combined with the renewable energy quota system and the green certificate trading mechanism, this paper constructs an optimization model of medium- and long-term contract trading of virtual power plants considering renewable energy derivatives. Finally, different renewable energy output scenarios are designed to analyze the benefits of virtual power plants in centralized and decentralized power markets. The example analysis shows the effectiveness of price difference contract for virtual power plants to ensure the renewable power revenue, which provides a certain reference for virtual power plants to participate in the power market.

Regional allocation of renewable energy quota in China under the policy of renewable portfolio standards

Renewable energy policy plays an important role in achieving carbon neutrality which is main goal for climate change mitigation. China is striving to promote the implementation of renewable portfolio standards under the goal of carbon neutralization in 2060. Thus, based on the principles of equality and efficiency, we apply zero sum gains data envelopment analysis (ZSG-DEA) model combined with entropy model to allocate China's renewable energy quota from provincial perspectives. Further, we introduce an environmental Gini coefficient to evaluate the rationality of allocation results. The allocation results show that Guangdong, Jiangsu, Sichuan and Shandong are four provinces with the most renewable energy quota, while Hainan, Guizhou, Gansu, and Xinjiang are four provinces with the least quota. In addition, the quota allocation results have achieved the goal of transferring the responsibility of renewable energy quota from western provinces to eastern provinces. Last, managerial suggestions in promoting renewable energy development are discussed.

Research on an optimization model for wind power and thermal power participating in two-level power market transactions

In 2015, “Several Opinions on Further Deepening the Reform of the Power System” was issued. The new round of power system reforms proposes to give full play to the vitality of the power generation-side bidding market, which will help to establish a fair, reasonable, and active power market. Due to factors such as a lack of peak shaving capacity and imperfect market mechanisms, China's renewable energy participation in the power market faces many problems. To solve these, this paper proposes a two-level optimization model for a wind power plant and thermal power unit to participate in the medium and long-term electricity market, and day-ahead market transactions. First, the paper proposes the electricity quantity and electricity price determination method of annual bilateral negotiated transactions, monthly centralized bidding transactions and listings, and delisting transactions, and briefly describes how to decompose contract electricity into the day-ahead market in the medium and long-term market. Then, two ways for the wind power plant and thermal power unit to participate in the power market are proposed. With maximization of the market benefits as the objective function, and through comprehensive consideration of the system reserve, wind curtailment penalty, green certificate trading, and other issues, the two models of independent participation and joint participation in market transactions were established to study the problem of maximum profit on the power generation side. Finally, the analysis results of the calculation example show that the joint participation of the wind power plant and thermal power unit in the power market has additional benefits compared to independent participation. The wind power plant can complete the assessment index of the renewable energy quota for the thermal power unit, which does not need to purchase green certificates to complete the assessment indicators. The thermal power unit can provide reserve services for the wind power plant, avoiding output whenever necessary, reducing the cost of the curtailment penalty, and overcoming the threat of wind power plant output fluctuations to the system. The two alliances have greater profit margins.

Exploring Opportunities and Challenges of Solar PV Power under Carbon Peak Scenario in China: A PEST Analysis

China has experienced rapid social and economic development in the past 40 years. However, excessive consumption of fossil fuel energy has caused an energy shortage and led to severe environmental pollution. To achieve sustainable development, China is striving to transform its growth mode. Adopting renewable energy (RE) including solar photovoltaic (PV) power is an effective measure. How to promote the further development of solar PV power under the scenario of China’s aspirational target of carbon peak by 2030 and 20% RE ratio in the energy mix remains a theme that need to be addressed. This paper analyzes the potential opportunities and challenges confronting solar PV power in China. The analysis covers the dimensions of political, economic, social, and technological (PEST). The results revealed a significant prospect for the further deployment of solar PV power in the coming decades. The aggressive estimated installed capacity of solar PV power is expected to reach 80+ GW annually. To successfully achieve the goal of 80+ GW, barriers that hinder the further development of solar PV power have to be eliminated. Suggestions for policymakers include maintaining enforceability and continuity of policies, favorable financial supports, mandatory RE quotas for all parties, and supporting fundamental R&D. Suggestions for the solar PV industry include full utilization of integrated applications, set up an after-sales service network, collaborative innovation among the industry chain, and engaging in storage and hydrogen technology. The findings are greatly beneficial for policymakers and the solar PV industry.

Optimal scheduling of multi-park integrated energy system under renewable energy quota considering demand side response

The integrated energy system (RIs) is composed of electricity/gas/cold/heat and other energy sources, which can realize the coordinated utilization of different forms of energy. RIs is conducive to promoting the rational utilization of clean energy, and the mutual coupling between different energy sources can effectively improve the overall energy utilization efficiency and operation economy of the system. The diversity of energy supply and demand makes the system operation complex and diverse, so it is indispensable to optimize the system operation scheduling. Demand response is an effective means to optimize the multi-objective scheduling of regional comprehensive energy system. RPS and green certificate trading mechanism are new methods to promote the consumption of renewable energy. In the process of green certificate trading, considering the load side demand response is conducive to realizing the maximum utilization of renewable energy power generation and improving the absorption rate of renewable energy power generation.