Optimal reduction and equilibrium carbon allowance price for the thermal power industry under China’s peak carbon emissions target

As the largest source of carbon emissions in China,the thermal power industry is the only emission-controlled industry in the first national carbon market compliance cycle.Its conversion to clean-energy generation technologies is also an important means of reducing CO_(2)emissions and achieving the carbon peak and carbon neutral commitments.This study used fractional Brownian motion to describe the energy-switching cost and constructed a stochastic optimization model on carbon allowance(CA)trading volume and emission-reduction strategy during compliance period with the Hurst exponent and volatility coefficient in the model estimated.We defined the optimal compliance cost of thermal power enterprises as the form of the unique solution of the Hamilton–Jacobi–Bellman equation by combining the dynamic optimization principle and the fractional It?’s formula.In this manner,we obtained the models for optimal emission reduction and equilibrium CA price.Our numerical analysis revealed that,within a compliance period of 2021–2030,the optimal reductions and desired equilibrium prices of CAs changed concurrently,with an increasing trend annually in different peak-year scenarios.Furthermore,sensitivity analysis revealed that the energy price indirectly affected the equilibrium CA price by influencing the Hurst exponent,the depreciation rate positively impacted the CA price,and increasing the initial CA reduced the optimal reduction and the CA price.Our findings can be used to develop optimal emission-reduction strategies for thermal power enterprises and carbon pricing in the carbon market.

How to auction carbon emission allowances?A dynamic simulation analysis of spatiotemporal heterogeneity

There is notable variability in carbon emission reduction efforts across different provinces in China,underscoring the need for effective strategies to implement carbon emission allowance auctions.These auctions,as opposed to free allocations,could be more aligned with the principle of“polluter pays.”Focusing on three diverse regions—Ningxia,Beijing,and Zhejiang—this study employs a system dynamics simulation model to explore markets for carbon emissions and green certificates trading.The aim is to determine the optimal timing and appropriate policy intensities for auction introduction.Key findings include:(1)Optimal auction strategies differ among the provinces,recommending immediate implementation in Beijing,followed by Ningxia and Zhejiang.(2)In Ningxia,there’s a potential for a 6.20%increase in GDP alongside a 21.59%reduction in carbon emissions,suggesting a feasible harmony between environmental and economic objectives.(3)Market-related policy variables,such as total carbon allowances and Renewable Portfolio Standards,significantly influence the optimal auction strategies but have minimal effect on carbon auction prices.

Pricing and decision of carbon emission reduction for closed-loop supply chain considering carbon trading mechanism

To determine the optimal pricing and carbon emission reduction decision, a closed-loop supply chain with a manufacturer and a retailer is investigated. In this system, the manufacturer manufactures new products and remanufactures used products while the retailer is responsible for selling new products and remanufactured products. The profit functions of the manufacturer and the retailer are developed, and the corresponding solution formulae for decision variables are given by the Stackelberg game model. Finally, a numerical example is given, and the optimal wholesale price, retail price, carbon emission reduction and others are obtained. Through the sensitivity of the unit carbon allowance price, some significant managerial insights are derived.