Under the "dual carbon" target， the mechanisms and operating conditions of low-carbon and electricity markets are undergoing frequent and rapid changes， complicating the analysis of market value coupling and transmission. Starting from the development trajectories of the carbon emissions trading market， green certificate market， and green power market， key components of the low-carbon market， and combining these with the recent operational status of the low-carbon market， this study investigates the relationship and value transmission mechanisms between the carbon-electricity markets from both static and dynamic perspectives. By examining the underlying value transmission logic between these markets， this paper explores pathways for their coordinated development， identifies existing issues in market integration， and proposes corresponding improvements. The findings offer effective analytical approaches and insights for promoting synergy and value transmission between China's carbon-electricity markets.

Green electricity certificates （GECs） and carbon market are the key points to promote green and low-carbon development in China. China has achieved positive results in improving nationwide green and low-carbon consumptions and construction of a green development responsibility system. Typical international green certificate trading mechanisms and development courses， as well as construction and operation modes of overseas carbon trading markets in EU，US，etc.， are summarized. And the policy system， trading mode and operation mode of domestic green certificate and carbon market are also described. The necessity of China's green certificate and carbon trading mechanisms to the "double carbon" target is demonstrated from the supply side and the demand side. Based on the fact of the coexistence of mandatory and voluntary carbon markets in China， detailed connection plans for GECs and the mandatory carbon market and GECs and voluntary carbon market are proposed， respectively. And the challenges of the plans are analysed. Finally， considering the experience and the cognition on international and domestic carbon market entities， as well as the possible connecting plans for GECs and carbon markets， a specific policy that is feasible at the operational level is given.

To promote low-carbon and cost-effective operations of regional integrated energy systems（RIES）， a low-carbon economic dispatch model under green certificate and carbon trading mechanisms was proposed considering tiered demand response. Carbon capture and power-to-gas technologies were introduced into combined heat and power（CHP） units to establish an integrated operation model for CHP units， carbon capture systems， and power-to-gas equipment. The carbon and green certificate trading mechanisms and their interactive models were analyzed. Additionally， tiered demand response was employed on the user load side to achieve peak load shaving for electricity， heat， and gas loads. The system's total operating cost over a single day was set as the objective function， and various case scenarios were analyzed using the Gurobi solver. The results demonstrate that the proposed model effectively enhances the system's low-carbon performance and economic efficiency， facilitates the output and consumption of renewable energy units， and provides superior peak-shaving effects.

The Virtual Power Plant （VPP） is a key focus for energy management optimization and green， low-carbon operations. With the increasing participation of VPPs in green certificate and carbon trading markets， the volatility of distributed renewable energy and emerging business models have a significant impact on VPPs' optimization scheduling and trading strategies. To enhance the overall profitability of VPPs and further explore the scheduling potential of distributed resources， this paper proposed a robust optimization scheduling strategy for VPPs considering demand response and leasing shared energy storage in the green certificate-electricity-carbon coupled market. First， a price difference factor between green certificates and carbon quotas was introduced， and a coupled market operation framework was constructed. Second， considering the interest balance between VPPs and flexible loads under demand response， as well as the capacity leasing model of energy storage， a two-layer deterministic optimization scheduling model based on a leader-follower game was proposed. On this basis， a two-stage robust optimization model was further developed to account for the uncertainties of wind and photovoltaic power generation. Finally， the KKT conditions and column-and-constraint generation algorithm were applied to solve the model. Simulation results showed that the proposed strategy effectively addressed the uncertainties of wind and photovoltaic power， and through the integration of the green certificate-electricity-carbon coupled market， demand response， and leasing shared energy storage model， the potential for distributed resource scheduling was further explored， significantly enhancing the overall profitability of VPPs.

Driven by the "dual carbon" target，the deep integration of carbon trading mechanisms，green certificate trading mechanisms，and integrated energy systems is beneficial for accelerating the energy transition and reducing carbon emissions.A scheduling method for integrated energy systems with demand response considering carbon-green certificate joint trading was proposed. When the integrated energy system holding green certificates participated in the carbon trading market， the carbon-green certificate recognition mechanism converted green certificates into carbon emission reductions corresponding to China Certified Emission Reductions，thereby establishing a new framework for the carbon-green certificate joint trading mechanism. Based on the sensitivity to price signals and the substitutability of energy，a demand response model for electricity，gas，and heat loads was developed.A scheduling model for integrated energy systems was constructed，incorporating both carbon-green certificate joint trading and demand response.Simulation results demonstrate that considering the carbon-green certificate joint trading mechanism in scheduling can effectively reduce both the total system cost and carbon emissions， while demand response can further lower the total cost and achieve peak shaving and valley filling effects. Further analysis of the impacts of the carbon trading unit price，green certificate unit price，and new energy quota allocation indicators on the system reveals that reasonable adjustments to these indicators can further reduce both the total system cost and carbon emissions.

As market mechanisms in energy-related markets continue to improve， it has become increasingly challenging for thermal power entities to synergize their operations in multiple markets. To support the effective participation of thermal power entities in market decision-making， factors influencing trading decisions in the electricity market， carbon market， and the integrated electricity-carbon market were analyzed. Based on the decision-making principles of the integrated market， the trading decision-making logic for both the electricity market and carbon market was developed. Subsequently， the analysis and modeling of thermal power entities' participation in carbon market trading decisions provided processes， objectives， and constraints for carbon market trading decisions. With the goal of maximizing the benefits for thermal power entities， a short-term and long-term collaborative decision-making model for the electricity-carbon market was developed. Through case studies and calculations， the effectiveness of the proposed model for the participation of thermal power entities in the electricity-carbon market was validated.

To improve the accuracy of bid selection for PV and energy storage charging stations（PECS） in market transactions， an innovative strategy is proposed， where the optimal trading strategy is determined by PECS and electric vehicles（EV） through a leader-follower game during the pre-clearing period. This approach aims to maximize revenue during the official clearing period. Considering the uncertainties of PV output and users' willingness to charge that influence the transaction results in the game process， a robust optimization uncertainty set and the Takagi-Sugeno-Kang（TSK） fuzzy model were employed to address these uncertainties. A leader-follower market trading model was established， with PECS as the leader and EV as the follower， to improve the market income of PECS. A case study simulated two scenarios： one where PECS and EVs participated in the day-ahead market through game optimization， and another where they did so without game optimization. The game model was solved by the commercial solver CPLEX and intelligent optimization algorithm. PECS operating results showed that the profits of three operators increased by 12.59%，29.13%，20.37%，respectively，while the charging volatility of EV users decreased by 4.4，3.6 and 5.2 percentage， respectively. The results validated the effectiveness of the model in improving operating revenue and reducing charging volatility.

In a power system with a high wind power share， due to the strong uncertainty of wind power forecasts， the traditional model of joint optimization of the spot market for electric energy and standby in accordance with the maximum load optimization of standby clearing is no longer able to take into account the requirements of security and economy of system operation. Therefore， this paper constructs a joint spot market clearing model considering wind power uncertainty on the basis of wind power forecast error analysis. Firstly， a hybrid skewed distribution model based on the normal cloud model is proposed to accurately characterize the distribution of short-term wind power output forecast errors； secondly， the impact of wind power output forecast errors on power balance constraints and system spinning standby is taken into account in the joint clearing model， and a joint market clearing model based on the opportunity constraints planning is established； subsequently， the wind power output forecast error distribution model is sampled several times and the sampling result is used to match the real-time supply and demand in the market clearing model with the wind power output forecast errors. Subsequently， the wind power forecast error distribution model is sampled several times and the sampling results are used to transform the market clearing model deterministically so that the model can be solved quickly. Finally， a simulation analysis is carried out with the actual data of a region with high wind power share， and the results show that the model proposed in this paper can effectively improve the economy of system operation under the premise of guaranteeing the safety of system operation.

In the context of the electricity trading market， optimizing renewable energy consumption strategies is an important approach for improving the efficiency of renewable energy utilization. The integrated scheduling of photovoltaic （PV） and thermal power generation was taken as the research subject. An electricity trading system model was established， and the scheduling strategy was optimized using the particle swarm optimization（PSO）algorithm. Through simulation of PV power generation data and electrical load datasets， the objective functions and constraints were set， and the practical effects of the optimized strategy were analyzed. The results showed that reasonable coordinated scheduling of PV and thermal power generation not only significantly improved consumption efficiency of renewable energy generation but also enhanced the stability and economic efficiency of the power system. The effectiveness of the PSO algorithm in optimizing renewable energy consumption strategies was validated. It provides a theoretical basis and practical guidance for electricity market reform and renewable energy utilization.