Tradable Certificates Research Articles

Optimization strategies for green power and certificate trading in China considering seasonality: An evolutionary game-based system dynamics

China has adopted renewable portfolio standards and tradable green certificates (including hydropower) to increase the proportion of green power used and reduce carbon emissions. However, hydropower generation is affected by seasonal factors, making it difficult to increase green power consumption in water-scarce areas. Trading electricity and green certificates in regions with different resource endowments can effectively solve this problem. Therefore, this study uses evolutionary game theory to explore the impact of the change in the policy of issuing green certificates for hydropower on the strategic choices of the trading parties. Based on the evolutionary game model, a system dynamics model is established to explore the optimization strategies of green power and certificate trading under the influence of seasonal factors. The results of the case study show that (1) the price of green certificates varies with seasonal changes. (2) Sellers with abundant hydropower resources should increase the amount of hydropower connected to the grid during the water-abundant period to help deficit areas achieve their consumption targets (3) Expanding the scope of green certificates can gradually eliminate government subsidies and incentives and reduce the government's financial pressure.

Navigating the energy transition with the Carbon-Energy-Green-Electricity scheme: An industrial chain-based approach for China's carbon neutrality

In exploring the intricate dynamics of China's energy transition towards a national certificate trading market, this study harnesses a two-stage game model to unravel the nuanced decision-making within the intertwined carbon emissions trading, energy-consumption permit trading, and electricity markets. A novel industrial chain-based policy framework, i.e., the Carbon-Energy-Green-Electricity (CEGE) scheme, is introduced to address the complexity inherent in aligning these trading markets towards carbon neutrality goals. Findings reveal that the current isolated energy transition policies lead to increased electricity prices and imposes redundant regulatory burdens on power companies. By advocating for the CEGE scheme, the study presents a strategic approach to alleviate these challenges, highlighting its potential to lower electricity costs and foster more efficient carbon reduction efforts. Furthermore, it underscores the importance of integrating energy transition policies, including CET, ECPTS, the renewable portfolio standards (RPS), and the tradable green certificate program (TGC), to enhance renewable energy adoption, offering a path to relieve financial pressures on households while supporting broader environmental and economic welfare improvements.

Optimal scheduling of a multi-energy complementary system simultaneously considering the trading of carbon emission and green certificate

This paper uses a multi-energy complementary system composed of thermal, wind, photovoltaic power generation, and electric energy storage units to participate in four market mechanisms and construct the optimal scheduling model of these trading mechanisms. These four mechanisms are carbon emission trading, green certificate trading, these two trading that are not joint, and joint. Under the latter two mechanisms, the excess carbon emissions of the system can be reduced to 9258t, and the utilization rate of renewable energy can reach 100 %. However, the operating costs under the fourth mechanism are 9695.80 $ lower than the third one because 5947 pieces of green certificates are converted into carbon emission rights. When the carbon price rises, the cost of the fourth mechanism increases slower than that of the third mechanism. The conversion volume of green certificates increases from 5947 to 10947, and the cost difference between the two increases to 67558.33 $. When green certificate prices rise, the cost under the fourth trading mechanism decreases faster. As that cost steadily declines, the carbon emission rights are converted into 907 green certificates, and the cost difference between this and the third mechanism increases to 4695.52 $.

Research on optimal scheduling of virtual power plant considering demand response under carbon-green certificate trading mechanism

Research on optimal scheduling of virtual power plant considering demand response under carbon-green certificate trading mechanism

A Non-Transferable Trade Scheme of Green Power Based on Blockchain

Power consumers can obtain authoritative green environmental value certification through green electricity trading, which plays an important role in improving the production competitiveness of enterprises, especially for international product trade affairs. However, the credibility of green electricity transactions faces serious challenges in the enterprise green authentication affairs, especially the user’s identity authentication, the traceability of green electricity transactions, and the standardization of green electricity transactions. Aiming to solve the certification and traceability problem of tradable green certificates, this paper proposes an integrated green certificate trading protocol, which solves its double-trading problem and helps to improve the credibility of renewable energy use. The main contribution is providing a solution based on the consortium blockchain technology to solve the main challenges mentioned above. The main solved scheme designs a series of protocols, which includes a purchase protocol, payment protocol, and non-transferable protocol. The whole process ensures the credibility, traceability, and non-transferability of green certificate trading. Multiple verification measures are adopted to address security and privacy challenges in green certificate management. Through security analysis, the protocol effectively defends against attacks such as double payments, transaction rollback, and transaction replays while ensuring users’ privacy.

Optimal Bidding Strategies for Wind-Thermal Power Generation Rights Trading: A Game-Theoretic Approach Integrating Carbon Trading and Green Certificate Trading

In response to the challenges of low wind power consumption and high pollution emissions from thermal power, the implementation of wind-thermal power generation rights trading is a proactive attempt to reduce wind power curtailment and promote its consumption. This study first regards the alternating bidding process between the two parties as a dynamic game, using the Rubinstein bargaining game model to determine the incremental profit allocation and optimal bidding for both parties in power generation rights trading. Secondly, an energy conservation and emission reduction model is constructed to analyze the benefits from the perspectives of standard coal consumption saving and the carbon emission reduction caused by power generation rights trading. Finally, a combined trading revenue model is established to analyze the final profit of both parties involved in the trading. The results show that the combined trading of wind-thermal power generation rights, incorporating carbon trading and green certificate trading, can effectively promote coal consumption savings in thermal power units and reduce the carbon emissions of the power industry. Moreover, it significantly increases the final profit for both parties, stimulating the enthusiasm of generators for participating in power generation rights trading, and ultimately promoting wind power consumption.

The optimization and dispatch of regional multi-energy complementary power system in green certificate Trading - Carbon emission trading

Abstract This proposal of the “double carbon” goal underscores the pressing need to reduce carbon emissions. To address this issue, the utilization of an optimal scheduling model for an integrated multi-energy complementary system, comprising wind, solar storage, and thermal power generation, is proposed. Two renewable energy generating units, wind and photovoltaic power, cooperate with thermal power units to generate electricity to meet urban base load requirements. Energy storage units compensate for the instability of power generation from renewable energy units. To significantly decrease system carbon emissions, a green certificate trading-carbon emission trading system is introduced. The carbon emission reduction facilitated by the green certificate can offset a portion of the carbon emissions, and the quantities of tradable green certificates and carbon emissions in their respective markets are adjusted accordingly. This model aims to maximize the system’s comprehensive operating earnings while considering the low-carbon economy aspect. The proposed model undergoes simulation analysis, and the results demonstrate its reasonableness and efficacy in terms of carbon reduction and economic viability.

Cross-provincial collaborative transaction that considers both the green electricity and the green certificate markets under a renewable portfolio standard policy

In the current implementation of the Renewable Portfolio Standard (RPS), various quota entities are facing challenges, including high costs and limited flexibility within a non-collaborative, single green certificate market mechanism. To address these issues, we developed a cross-provincial collaborative transaction model that considers both the green electricity and the green certificate markets. It consists of five sub-models: a green electricity production net revenue maximization sub-model, a green electricity consumption net benefit maximization sub-model, a green electricity and green certificate market categorization sub-model, a cooperative game sub-model for green electricity and green certificate buyers and sellers, and a cooperative benefits allocation sub-model. The roles of each province (i.e., green electricity and certificate buyers and sellers), along with the optimal green electricity generation, green certificate trading volume, and cost of achieving RPS objectives for each province, can be determined by utilizing the first four sub-models. Ultimately, the cooperative benefit allocation sub-model promotes cooperation among the provinces. To validate the model's effectiveness, we chose five representative provincial-level regions of China for empirical analysis. We found that the cooperative mode decreased the cost by 238.554 × 108 CNY (15.9%) compared with each province independently achieving RPS targets in a non-cooperative mode. Moreover, cooperation increased green electricity generation by 447.94 × 108 kWh (13.3%). The cooperative mode will therefore encourage provincial governments to formulate cooperative strategies for achieving RPS objectives, ultimately reducing implementation costs and increasing flexibility and effectiveness.

Research on multi-time scale integrated energy scheduling optimization considering carbon constraints

To address the challenge of grasping carbon emission costs in different dispatching cycles under multiple time scales of the Integrated Energy System (IES), a carbon-constrained multi-time scale optimization method for integrated energy systems is proposed. First, a novel mechanism was proposed, Carbon Constraint Mechanism, which includes carbon tax, green certificate trading, and tiered carbon trading mechanism. Second, the carbon constraint mechanism was introduced into multi time scale scheduling optimization, and an IES multi time scale low-carbon optimization scheduling model was established. Third, the economic cost, carbon emissions, and primary energy consumption were considered as objective functions in multi-objective optimal scheduling. Moreover, utilized day ahead scheduling results and real-time load forecasting to dynamically adjust the output power of IES equipment in combination with power change penalties and carbon constraints. The simulation results showed that, compared to dispatch optimization strategies that solely prioritized economy, this study reduced carbon emissions by 28.38 % across multiple time scales while enhancing the economic performance of IES by considering carbon constraints. The multi-time scale dispatch optimization, incorporating carbon constraint mechanisms, improved the system's stability and low-carbon economy, proving the feasibility and effectiveness of the proposed optimal dispatch strategy.

Research on the cost allocation method of deep sea wind power considering carbon trading and green certificate trading

Climate change imposes tighter limits on carbon emissions, which require the development of more green electricity. Deep sea wind power has the advantages of high wind energy density, high power generation utilization hours, no land occupation, and near to power load centers for easy on-site consumption, which lead to a broad market prospect. In the foreseeable future, deep sea wind power will usher in large-scale construction and development. The initial investment and construction cost of deep sea wind power is high, subsidies are gradually decreasing, and there is a lack of full life cycle economic analysis combined with various market policies, resulting in a lack of guidance for its investment and construction. In order to promote the development of deep sea wind power, relevant cost recovery mechanisms must be found. This paper proposes a system cost allocation method based on the comparative difference method and load similarity with consideration of the transformation and operation costs of thermal power, demand-side response, and energy storage; a cost allocation method based on carbon trading and green certificate trading income is proposed; and a time sequence optimization operation simulation model is established to maximize the deep sea wind power income. A case study is proposed for a 300 MW deep sea wind farm, the results show that the cost allocation method and cost allocation model proposed in this paper have a significant effect on wind power cost recovery, and the effectiveness of the proposed method and model is verified.

Benchmarking and contribution analysis of carbon emission reduction for renewable power systems considering multi-factor coupling

The renewable power system serves as a vital path towards achieving carbon peaking and neutrality goals. Accurately quantifying the carbon reduction emissions of renewable power systems and evaluating the contribution of various influencing factors to carbon reduction is quite important, which is related to the formulation of energy policies and regional power planning by the power grid or relevant departments. However, in the current research, there are few studies related to the quantification of carbon emission reduction, and in terms of optimal scheduling, the existing studies often only consider a single factor, ignoring the coupling effect between multiple factors, which makes the contribution of each optimization strategy to carbon emission reduction unclear. Therefore, based on the current power system scheduling mechanism and dual-carbon background, this paper optimizes the carbon emission reduction benchmark factor and its corresponding weight, proposes a new carbon emission reduction benchmark of renewable power system, and verifies the accuracy of this benchmark based on the classical scheduling model. On this basis, the mathematical models of thermal power deep peak shaving (DPS), electricity export (ELE) and green certificate trading (GCT) are established. Each factor is introduced into the classical scheduling model to simulate and verify the promoting effect of each influencing factor on carbon emission reduction. Finally, the above different influencing factors were constructed in different coupling scenarios to calculate the carbon emission reduction under each scenario, and the contribution degree of each influencing factor to carbon emission reduction was analyzed sharply according to the value of cooperation game instead of the traditional calculation method. The results show that the proposed benchmark can reduce the error by 2.6%–15.5 %. In the carbon emission reduction contribution simulation, the three factors have coupling effects, and deep peak shaving and electricity export are more sensitive to carbon emission reduction contribution. This study provides valuable insights for the development of carbon reduction strategies for renewable power systems.

Grappling with the trade-offs of carbon emission trading and green certificate: Achieving carbon neutrality in China

Although our knowledge of national carbon emission trading system and green certificate trading system are powerful incentive instruments that can deliver on increasingly ambitious climate targets in China, there remains an uncertainty of systems' structural reforms. This study builds on and extends a well-established dynamic computable general equilibrium (CGE) model to incorporate carbon trading system and green certificate trading system into the modeling framework, simulating a diverse of system development pathways further allows an exploration of the many possible policy effect. Then, using total factor productivity as a comprehensive indicator to asses policy effectiveness, the evolutionary trend of comprehensive effects under different paths are separately evaluated to discover the reforms’ optimal range. Our work offers main results: First, these instruments provide a price signal. The introduction of a carbon allowance auction drive up carbon prices, while the implementation of a green certificate punishment and the expansion of the trading scope promote an increase in green certificate prices. Second, all policy scenarios that help reduce carbon emission intensity and optimize the power supply structure. However, in achieving the net-zero goal, the green certificate policy incurs more economic costs than the carbon trading policy. Indeed, the combination of multiple policy tools alleviates the decline of social welfare levels. Third, synergism design among policy tools: the focus should be on carbon trading policy from 2021 to 2030, green certificate trading policy from 2030 to 2050, and strengthened policy from 2050 to 2060. Reform measures within policies may need to be introduced in a timely manner. This study offers specific insights and tailored policy proposals to support policymakers in balancing environmental goals with economic and social needs in light of the aforementioned findings.

Enhancing renewable energy certificate transactions through reinforcement learning and smart contracts integration

Given the complexity of issuing, verifying, and trading green power certificates in China, along with the challenges posed by policy changes, ensuring that China’s green certificate market trading system receives proper mechanisms and technical support is crucial. This study presents a green power certificate trading (GC-TS) architecture based on an equilibrium strategy, which enhances the quoting efficiency and multi-party collaboration capability of green certificate trading by introducing Q-learning, smart contracts, and effectively integrating a multi-agent trading Nash strategy. Firstly, we integrate green certificate trading with electricity and carbon asset trading, constructing pricing strategies for the green certificate, carbon, and electricity trading markets; secondly, we design a certificate-electricity-carbon efficiency model based on ensuring the consistency of green certificates, green electricity, and carbon markets; then, to achieve diversified green certificate trading, we establish a multi-agent reinforcement learning game equilibrium model. Additionally, we propose an integrated Nash Q-learning offer with a smart contract dynamic trading joint clearing mechanism. Experiments show that trading prices have increased by 20%, and the transaction success rate by 30 times, with an analysis of trading performance from groups of 3, 5, 7, and 9 trading agents exhibiting high consistency and redundancy. Compared with models integrating smart contracts, it possesses a higher convergence efficiency of trading quotes.

Multi-timescale optimization of integrated energy system with diversified utilization of hydrogen energy under the coupling of green certificate and carbon trading

Promoting renewable energy and developing low-carbon integrated energy systems are noteworthy in the energy sector. However, in existing works on the integrated energy system, the coupling of green certificate and carbon trading mechanism under diversified utilization of hydrogen energy has not been fully considered to provide an incentive effect for uncertain renewable energy resources. Based on these considerations, a multi-timescale optimization of an integrated energy system with diversified utilization of hydrogen energy is studied under the coupling of green certificate and carbon trading mechanism. First, the coupled interaction mechanism of green certificate trading-stepped carbon trading is proposed by linking stepped carbon trading to green certificate trading through green certificates. Furthermore, the establishment of the diversified utilization unit of hydrogen energy addresses carbon emissions from the perspective of energy application and offers fresh concepts for a low-carbon economy. Then, an optimized scheduling model for multiple time scales of day-ahead/intraday/real-time is developed to reduce the impact of renewable energy prediction errors on system operation. Results acquired from case studies demonstrate the effectiveness in terms of achieving economic and low carbon. The accommodation level of renewable energy with a coupling mechanism improves by 3.08% compared to that without considering coupling. In addition, the diversified utilization of the hydrogen energy model enables the reduction in total cost and carbon emission by 5.14% and 2.4927 tonnes in comparison to the traditional power-to-gas mode.

Market instrument for the first fuel and its role in decarbonizing Indian industrial production

India introduced Perform, Achieve, and Trade (PAT) scheme in 2012; it assigns targets to energy-intensive industries with estimated energy savings of 11–16% to enhance energy efficiency and allows energy-saving certificates trading. We qualitatively review India's energy efficiency policy landscape, including the institutional structure, operational trajectory, and outcomes of the PAT scheme's completed cycles. We identify four research themes: 1) Industry-wise specific energy consumption correlation with various factors of the industrial sector under PAT should be identified; 2) PAT scheme impact on aluminium, chlor alkali, textile, etc. Lacks exploration; 3) Realistic baseline target setting should be done for designated consumers under PAT scheme, and 4) machine learning based monitoring and verification for PAT scheme is still nascent but appears promising. We find a lack of ambition in the targets, which are easily met and could harm future investments in energy efficiency.

Blockchain Integration and Its Impact on Renewable Energy

This paper investigates the evolving landscape of blockchain technology in renewable energy. The study, based on a Scopus database search on 21 February 2024, reveals a growing trend in scholarly output, predominantly in engineering, energy, and computer science. The diverse range of source types and global contributions, led by China, reflects the interdisciplinary nature of this field. This comprehensive review delves into 33 research papers, examining the integration of blockchain in renewable energy systems, encompassing decentralized power dispatching, certificate trading, alternative energy selection, and management in applications like intelligent transportation systems and microgrids. The papers employ theoretical concepts such as decentralized power dispatching models and permissioned blockchains, utilizing methodologies involving advanced algorithms, consensus mechanisms, and smart contracts to enhance efficiency, security, and transparency. The findings suggest that blockchain integration can reduce costs, increase renewable source utilization, and optimize energy management. Despite these advantages, challenges including uncertainties, privacy concerns, scalability issues, and energy consumption are identified, alongside legal and regulatory compliance and market acceptance hurdles. Overcoming resistance to change and building trust in blockchain-based systems are crucial for successful adoption, emphasizing the need for collaborative efforts among industry stakeholders, regulators, and technology developers to unlock the full potential of blockchains in renewable energy integration.

An integrated energy system “green-carbon” offset mechanism and optimization method with Stackelberg game

The low-carbon economic operation of integrated energy systems (IES) cannot be separated from the carbon trading and green certificate trading market. Therefore, a low-carbon market mechanism and optimization method for IES is proposed. First, we establish a “green-carbon” offset mechanism to realize the conversion from tradable green certificate (TGC) to carbon quotas to offset system's carbon emissions. Second, considering the impact of market incentives and users' consumption behavior on IES, an energy management method of IES is put forward based on Stackelberg game. IES operators as leaders decide energy prices and trading strategies of carbon, TGC and multi-energy. Energy users as followers participate in the integrated demand response based on energy price. The game is solved by an improved adaptive catastrophic genetic algorithm and CPLEX solver. Finally, we take an industrial park in China as an example to analyze. The results show that the proposed method can significantly reduce the system's carbon emissions while improving the benefits for both IES and consumers.

Model construction of coordinated operation mechanism of energy supply chain based on operations research big data algorithm

During rapid modernization, the policy of technological upgrading of the coordinated operation of the energy supply chain has been tested over many years of practice, with limited potential for future development, and further emission reductions are facing greater technological and cost pressures. Market trading policies mainly include the carbon emissions trading mechanism and the guaranteed mechanism for renewable energy power consumption, and the above policies will be formally implemented in 2020, which will be the main direction of development in the future. After introducing the low-carbon policies, this paper will focus on the coal-power energy supply chain considering the carbon credit quota and renewable electricity consumption limitations and analyze the impacts of the relevant parameters on the coal-power energy supply chain returns under the above policies in both non-cooperative and cooperative game scenarios. Finally, a preferential price-based green power certificate trading mechanism is constructed to propose a cost-reducing trading proposal for power users to purchase green power certificates to fulfill the amount of renewable energy power consumption.

Two-stage low-carbon optimal dispatch of the power system considering demand response to defend large uncertainties and risks

Introduction: In order to promote the consumption of renewable energy, reduce carbon emissions, and take into account the uncertainty of renewable energy output and load fluctuations in the new power system that can affect the normal operation of market mechanism, a two-stage low-carbon optimization scheduling method for power system that considers demand response under multiple uncertainties is proposed in this paper.Methods: Uncertain scene sets are generated through Latin hypercube sampling and heuristic synchronous backpropagation method is used to reduce scenes to obtain typical scenes and their probabilities. Then, a one-stage optimization model is established with the goal of maximizing energy efficiency and corresponding demand response strategies are obtained. Green certificate carbon trading joint mechanism model consisting of tiered green certificate trading and time-sharing tiered carbon trading are established, and the output of two-stage units are optimized with the goal of minimizing comprehensive operating costs.Result: The simulation results show that the carbon emissions are decreased by 251.57 tons, the consumption rate of renewable energy is increased by 8.64%, and the total costs are decreased by 124.0612 million yuan.Discussion: From this, it can be seen that the dual layer low-carbon optimization scheduling strategy for power system considering demand response under multiple uncertainties can effectively reduce the operating costs and carbon emissions of the system, while balancing the economic and environmental aspects of power system operation.

Optimal bidding strategy of a wind power producer in Chinese spot market considering green certificate trading.

In China, wind power producers will participate in the spot market as strategic producers. They should submit offering prices and forecasted production to the independent system operator. Intraprovincial and interprovincial green certificate trading, as a mechanism to promote the development of wind power, is advanced in parallel with the spot market. Studying the bidding strategies of wind power producers in the spot market, especially with the introduction of intraprovincial and interprovincial green certificate trading, has great practical significance for the stable operation of wind power producers and the construction of a renewable energy-friendly electricity market. This paper proposes a bi-level stochastic model to simulate the bidding strategy of a wind power producer in the spot market. The upper level problem of the model describes the decision-making process of the wind power producer, and the lower level problems include the clearing process of the spot market and the TGC market, in which the spot market includes the day-ahead market and the balance market, and the TGC market includes the intraprovincial and interprovincial TGC markets. Then, using Karush-Kuhn-Tucker (KKT) conditions, the strong duality theorem, and the big M method, the bi-level model is recast into a mixed integer linear (MIL) model convenient to be solved. Finally, an example is given to analyze the wind power producer's optimal bidding strategy under different electricity market environments and different wind power penetration levels.