Impact of the carbon market on investment benefits of power-grid enterprises in China: a system dynamics analysis

0 Introduction

Carbon trading markets serve as a mechanism to coordinate resources and reduce costs,providing companies with the opportunity to transition smoothly towards lowcarbon practices.In 2021,the Ministry of Ecology and Environment officially issued The Measures for the Administration of Carbon-emission Trading (Trial ) [1],signifying the establishment of a national carbon market in China.To further solidify its implementation,the Ministry of Ecology and Environment issued the Implementation Measures for Voluntary Carbon-emission Reduction Trading (Trial ) in 2023 [2],aiming to promote voluntary emissions reduction trading and establish a diversified carbon market system.In 2024,the State Council issued The Provisional Regulations on Carbon-emission Right Trading [3],which formally established a carbon-emission rights trading system through administrative regulations for the first time.

The electricity sector holds a crucial position in carbon reduction efforts due to its significant energy consumption and associated emissions.Since 2015,Chinese powergrid enterprises have embarked on a new phase of power reform aimed at fostering an effectively competitive power market and facilitating the transition to low-carbon energy.This initiative,guided by the overarching framework of‘controlling the middle and releasing the two ends’ [4,5],highlights their active engagement in the carbon market.In 2023,the National Development and Reform Commission issued The Notice on Provincial Grid Transmission and Distribution Prices and Related Matters for the third regulatory cycle,marking the commencement of this new phase in transmission and distribution pricing [6].The pricing of these services not only determines the revenue generated from power-grid investments but also plays an important role in guiding the development of powergrid enterprises.Moreover,the carbon market influences the operational costs of these enterprises through carbon pricing,which subsequently affects electricity prices and the overall energy structure in the power sector.

Currently,many studies focus on the interaction between the carbon and power markets [7-9].In [10],carbonemission costs were incorporated into real-time electricity pricing leveraging the German electricity market as the foundation.This study demonstrates the transmission of carbon costs to electricity prices.In [11],the quantification of carbon-emission costs within the framework of the Spanish electricity market was conducted,providing evidence that the full transmission of carbon costs to power generation costs and electricity prices may not be realized.In addition,an investigation in [12] explored the impact of the carbon trading mechanism on the power supply structure,revealing its potential to promote the diversified development of power supply structures.In [13],a multimarket game equilibrium model was established that considered the uncertainty of renewable energy and the coupling of electric-carbon-green certificate transactions.However,the above studies primarily focused on the perspective of the power generation industry,overlooking the participation of power-grid enterprises in the carbon market.

Currently,several power-grid enterprises in China,including Beijing,Shanghai,Guangdong,and Fujian,actively participate in carbon market pilot programs,employing different methods to account for carbonemissions [14,15].For instance,Beijing power-grid enterprises adopt a historical intensity method,calculating carbon-emissions as the product of the emission factor,the average value of the current year’s power supply,the baseline annual line loss rate,and the emission control coefficient [16].Similarly,Shanghai Power-grid enterprises implement an industry benchmark transmission line loss rate that decreases annually.Fujian,like Beijing,utilizes the historical intensity method to allocate its total carbonemission quota [17].Notably,these carbon-emission accounting approaches vary among power-grid enterprises based on the specific circumstances within each province.

With the introduction of new electricity reforms,power-grid enterprises have shifted their operational focus from traditional dependence on power demand growth to achieving effective asset growth and improved operational efficiency.The government strictly supervises powergrid investments,making investment benefits a key consideration for these enterprises [18,19].In [20],a grid investment ranking model based on an improved prospect theory was constructed,enabling power-grid enterprises to prioritize project investments according to the size of the comprehensive prospect value.In [21],an investment mechanism model was developed to adapt to investment changes and load forecasting risks.In addition,in [22],a relationship model was established to examine the interplay among power-grid investment,social and economic benefits,and power transmission and distribution prices.System Dynamics (SD) is a computer simulation method that accurately reflects causal feedback relationships by addressing the challenges of multivariable and nonlinear time-varying large systems [23,24].It is widely used in the electricity market [25],power-grid investments [26],and other applications.A dynamic evaluation model was established in [27] to evaluate the impact of transmission and distribution pricing reforms on power-grid investment using the SD method.In [28],an SD model of the transmission and distribution price and a grid investment plan considering maximum investment capacity constraints were developed.Additionally,in [29],an SD evaluation model for power-grid investment decisions was constructed from the perspectives of investment demand,transmission and distribution prices,grid profit,and investment capacity.Notably,few studies have examined the interaction between carbon and electricity prices on the investment benefits of power-grid enterprises using SD models,highlighting a research gap in this area.

To address these issues,this study introduces a novel SD model to examine the effects of the carbon and electricity markets on the investment benefits of powergrid enterprises.Compared to existing methods,the main contributions of this study are summarized as follows:

• The carbon-emissions accounting index is more comprehensive.This study includes carbon dioxide emissions resulting from transmission and distribution losses,as well as emissions generated during SF6 equipment maintenance and retirement,in the carbonemission accounting.In contrast,most existing studies have considered only the carbon dioxide emissions resulting from transmission and distribution losses.

• A new SD model framework is developed that considers the causal feedback mechanism of the carbon market on transmission and distribution pricing.This framework captures the interaction between the carbon and electricity markets,accounting for the annual approval of carbon-emission quotas and the strong dynamic attributes of carbon prices within the carbon-emission trading market.

• A quantitative analysis of the impact of carbonemissions on the investment benefits of a provincial powergrid is conducted.This analysis offers decision support for efficient investment strategies for power-grid enterprises operating under dual carbon targets in China.

The remainder of this paper is organized as follows.Section 1 describes the causal feedback of the carbon market on investment in power-grid enterprises.The SD model is presented in Section 2.The numerical results are described and discussed in Section 3.Finally,the conclusions are presented in Section 4.

1 Causal feedback analysis of the carbon market on investment of power-grid enterprises

1.1 Carbon-emission accounting method for power-grid enterprises

According to the Guidelines for accounting greenhouse gas emissions for China Power-grid Enterprises (Trial Implementation) [30],the greenhouse gas emissions of power-grid enterprises include carbon dioxide emissions caused by transmission and distribution losses and emissions generated during the maintenance and retirement of SF6 equipment.These emissions are accounted for as follows:

where Apgc is the total carbon dioxide emissions;Aloss is the carbon dioxide emissions caused by transmission and distribution losses; and ASF6 is the SF6 emissions generated and converted into carbon dioxide emissions (hereafter referred to as infrastructure carbon-emissions).

The emission ASF6 is calculated as follows:

where RECC and RECA are the SF6 capacity of the retired equipment and the SF6 actual recovery capacity from decommissioned equipment,respectively;REPC and REPA refer to the SF6 capacity of the repaired equipment and the actual recovery of SF6 from the repaired equipment,respectively;and GWPSF6 is the greenhouse gas potential of SF6.

The emission Aloss generated by the power transmission and distribution losses of power-grid enterprises can be calculated as follows:

where dloss is the actual network loss rate,Q is the annual power supply,and Bp is the carbon-emissions factor of the annual average power supply of the power-grid.

1.2 Carbon-emission quota allocation for powergrid enterprises

Two commonly used free allocation rules in carbon markets are grandfathering and benchmarking [31].Under the grandfathering approach,the amount of free carbon allowance is predetermined based on a company’s historical carbon-emissions in a specific base year.In contrast,the benchmarking approach links the allocation of free carbon allowances to industry-specific benchmark emission intensity and total output.To adhere to the “Polluter-Pays”principle,this paper adopts the benchmarking method based on historical emission intensity for power-grid enterprises,as it allows for fair distribution of carbon allowances in accordance with past emission levels.The carbon-emissions quotacan be calculated as follows [32]:

where dloss.B is the benchmark value of the power-grid loss rate and kf is the coefficient controlling the emission intensity of power-grid enterprises.According to the practice of pilot carbon markets,the coefficient kf is set to 92%,indicating an 8% reduction from its benchmark value.

In this study,carbon-emissions from SF6 were also considered.Therefore,the carbon-emission quota in Eq.(4)can be expressed as follows:

From Eq.(4) and Eq.(5),the power supply is one of the factors influencing the carbon-emission quota for powergrid enterprises.

1.3 Causal feedback analysis of carbon market on investment decision of power-grid enterprises

Carbon and electricity markets are intricately interconnected.Carbon prices and carbon-emission trading capacities are crucial determinants that impact electricity prices and the energy structure within the carbon market.Conversely,fluctuations in electricity prices and changes in energy structure also influence the dynamics of the carbon market.Fig.1 illustrates the interaction between these two markets.

Fig.1 Interaction between the carbon market and electricity market

The high investment and construction costs associated with renewable power generation often result in an electricity market mechanism that favors cheaper transactions over traditional power generation methods.The carbon market imposes substantial costs on traditional power generation due to carbon-emissions,whereas renewable power generation can attain significant emission reduction benefits,thereby encouraging its development.Consequently,a mutual influence exists between the carbon and power markets.

Fig.2 shows the causal feedback relationship between the carbon market and the investment decision-making process of power-grid enterprises.

Fig.2 Causality diagram of the impact of the carbon market on power company investment

The carbon-emission cost of power-grid enterprises is affected by the carbon price in the carbon market and the carbon-emissions from these enterprises.Following the calculation method for transmission and distribution electricity prices,the cost associated with carbon-emissions raises the overall cost of transmitting and distributing electricity.This,in turn,increases the investment cost of power-grid enterprises and subsequently affects their investment capacity.Conversely,the investment capacity of power-grid enterprises has an impact on their carbonemissions and feeds back into carbon-emission cost accounting.

Based on Eqs.(1) -(5) and the causal feedback analysis of the carbon market on the investment decisions of power-grid enterprises,Fig.3 depicts the SD model for carbon-emissions accounting in power-grid enterprises.Specifically,the power supply is determined as the product of power demand and maximum utilization hours.The carbon-emission quota for power-grid enterprises can be calculated using Eq.(5).Equation (1) details the carbonemissions of power-grid enterprises,comprising two components: carbon dioxide emissions due to transmission and distribution losses,and emissions from the maintenance and retirement of SF6 equipment.Fig.3 shows that the carbon-emissions quota is a key factor in designing the carbon market mechanism.Different carbon-emission quotas would directly affect the emission reduction costs for carbon market participants.

Fig.3 SD model of carbon-emission accounting for power-grid enterprises

2 System dynamics model of the carbon market on the investment evaluation of power-grid enterprises

Following the recent electricity reforms in China,the calculation method for transmission and distribution electricity prices has transitioned to a “permitted cost +reasonable income”mode [4].If power-grid enterprises are also participating in the carbon market,the cost associated with carbon-emissions must be considered.This alteration in permitted costs further influences transmission and distribution prices,thereby affecting the investment capacity of power-grid enterprises.

This study constructs an evaluation index system using the analytic hierarchy process to analyze the comprehensive benefits of investment and operations in power-grid enterprise.The index system incorporates the requirements of power-grid enterprises,regulatory authorities,and power consumers [33],as shown in Fig.4.By integrating various evaluation indices across different levels and considering their interrelationships and hierarchical structure,a multilevel analytical model was developed.

Fig.4 Evaluation index system for comprehensive benefits of investment and operation of power-grid enterprises

The comprehensive performance indicator system comprises six subindices: carbon-emissions,financing capacity,economic benefits,reliability,social responsibility,and user satisfaction.The carbon-emission index was calculated using Eq.(1),whereas the remaining five 5 indices can be found in [5].Specifically,the financing index reflects the investment capability of power-grid enterprises,considering self-owned funds,loan funds,and balanced account investments.The economic benefit indicator assesses the revenue and investment return rates of these enterprises.The reliability index measures the power supply capability,typically evaluated using a capacity-to-load ratio.In addition,current considerations include indices such as ecological construction investment,service quality,and job creation,all of which further affect the investment and operation of power-grid enterprises.

By calculating the values of the six indices and determining their respective weights through chromatographic analysis,the comprehensive performance is obtained as follows:

where V is the comprehensive performance, j is the index number,n is the total number of indices,and vj and wj denote the performance score and weight for each index,respectively.

Based on the causal relationships among carbonemissions,financing ability,economic benefits,reliability,social responsibility,and user satisfaction,a novel SD model(as shown in Fig.5) has been developed to dynamically evaluate the comprehensive performance of power-grid enterprises.The details of each module shown in Fig.5 are presented as follows.

Fig.5 SD model of power-grid enterprise investment and operation considering carbon-emissions

2.1 Financing ability

The financing ability of power-grid enterprises refers to their investment capability,comprising three components:self-owned funds Iown,t ,loan funds Iloan,t and balanced account investments Ibal,t .Self-owned funds are determined by the previous year’s income of the power-grid enterprise and its distribution ratio rown .Loan funds depend on the own funds of enterprises rloan and its asset-liability ratio.Balanced account investments are based on income derived from the balanced account,expressed as follows:

where Lt is the total income of the power-grid,Dt is the electricity demand,h is the maximum load utilization hours,rm is the marketization rate,ptr is the electricity price for transmission and distribution,pd is the difference between purchases and sales,and the subscript t represents year t.

2.2 Economic benefit

Economic benefit for power-grid enterprises encompasses their income and return on investment.Income forms the core of their operations,particularly in the context of the new electricity reform environment.This income includes fees for using transmission and distribution lines,and guaranteed income based on the difference between power purchases and sales.Given the characteristics of large-scale and long-term power-grid construction projects,evaluating the investment returns of these projects in the market environment is crucial.The return on investment it for year t is calculated as follows:

where pτ is the newly permitted income,Aτ is the new asset,r is the permitted rate of return,Qτ is the new investment,and the subscript τ indicates the year of τ.

The economic benefit index of power-grid enterprises is calculated as follows:

where kL is the weight coefficient of power-grid enterprise income,ki is the weight coefficient of return on investment,Lt is the performance score of power-grid revenue,andit is the performance score of return on investment.

2.3 Social responsibility

The social responsibility index Rt refers to the responsibility that power-grid enterprises,such as stateowned enterprises,bear towards society.In this study,the evaluation of social responsibility in power-grid enterprises is based on two main factors: The number of jobs provided and the investment in ecological environmental protection.The details are as follows.

whereis the performance score for the number of jobs provided by the power-grid company;Ic ,t is the investment in ecological construction;is the score for the performance of ecological construction investment;kb and kc are the weight coefficients of the number of jobs and ecological construction,respectively;and kpc is the proportion of investment in ecological construction.

2.4 Reliability

For power-grid enterprises,providing a reliable and stable power supply to consumers is a key responsibility,making reliability a crucial indicator in their performance evaluation.

The capacity-load ratio of the regional power grid,a key indicator of power supply capacity and reliability,is expressed as follows:

where Ct is the capacity determined for the total amount of power-grid equipment,Cm ,t is the production capacity,Cr ,t is the decommissioned capacity,rre is the retirement rate,and ra is the growth rate of the electricity demand.

2.5 Carbon-emission

Carbon-emissions serve as a crucial index for evaluating the comprehensive benefits of power-grid enterprises,serving as a measurement standard.Further details are presented in Section 1.1.

2.6 User satisfaction

Customer satisfaction in power-grid enterprises includes factors such as the reduction in electricity prices and expectations regarding the quality of power-supply services.It is expressed as follows:

where St is the user satisfaction,is the score electricity price performance,Is ,t is the investment in improving service quality,is the core service quality investment performance,kp and ks are the weight coefficient of electricity price and the weight coefficient of service quality,and kps is the proportion of investment used to improve service quality.

3 Simulation and analysis

An SD model was constructed for a specific provincial power-grid in China using data collected in 2023.Parameter values used in the SD model are summarized in Table 1,where Ip is the carbon-emission factor of the infrastructure;Pc is the carbon price;h is the maximum load utilization hours; P0 is the initial transmission/distribution price;rm is the marketization rate; r is the allowed rate of return;kL is the income weight of the power-grid enterprise;ki is the weight of investment return rate;rre is the retirement rate;ra is the growth rate of power demand;kpc is the proportion of investment in ecological construction; m is the number of jobs provided by power-grid enterprises;kb and kc are the weight of the number of job creation and the investment rights in ecological construction,respectively;kps is the proportion of investment used to improve service quality;kp and ks are the weight of electricity price and the weight of service quality,respectively;and T is the construction period of power-grid investment projects.To encourage power-grid enterprises to reduce carbon-emissions,the freeemission quota coefficient was set to 0.92.

Table 1 Parameter setting in the SD model

Taking 2023 as the base year,the SD model was simulated to formulate investment and operational planning for the provincial power-grid over the next 10 years.

3.1 Carbon-emission results

Figures 6 and 7 depict the trends in carbon-emissions and carbon-emission costs of provincial power-grid enterprises over a 10-year period.

Fig.6 Carbon-emission trend

Fig.7 Carbon-emission cost trend

1) The primary source of carbon-emissions for provincial power-grid enterprises is transmission and distribution losses,which significantly outweigh emissions from infrastructure.Furthermore,advancements in SF6 recovery and recycling technologies are expected to reduce the proportion of carbon-emissions from infrastructure.

2) The annual increase in total carbon-emissions of the provincial power-grid is primarily due to continuous growth in power demand and a consistent power-grid loss rate.

3) Carbon-emissions costs also increase annually.This is because the provincial power-grid enterprise operates under a free quota coefficient of 0.92,implying that the power-grid enterprise was responsible for covering 8% of the carbonemission costs.Assuming a constant carbon price,carbonemission costs demonstrate a nearly linear relationship with the volume of carbon-emissions.

3.2 Transmission and distribution price and investment capacity results

Figure 8 illustrates the trends in transmission and distribution prices and investment capacity of the tested power-grid enterprises over a 10-year period.

Fig.8 Trend of permitted cost,transmission/distribution price,and investment capacity

Key observations from Figures 6 and 7 are as follows:

Key observations from Figure 8 are as follows:

1) The trends in transmission/distribution prices and investment capacity show an overall downward trajectory.Specifically,during the first regulatory cycle of the electricity market (2024-2026),transmission/distribution price decreases whereas investment capacity increases.This growth in the investment capacity is driven by the rising power load.However,project completion delays affect revenue growth,leading to a decline in transmission and distribution prices.As the third regulatory cycle (2030-2032)approaches,transmission/distribution prices stabilize with a gradual reduction in investment and construction projects.Subsequently,the investment capacity of the power-grid continues to decline until stabilizing.

2) Comparing scenarios where carbon-emissions are considered versus those where they are not,including carbon-emission costs leads to an increase in allowable cost and transmission/distribution prices.This increase is due to the high transmission/distribution price resulting from factoring in carbon-emission costs.Consequently,investment capacity weakens,leading to a decrease in overall investment capacity.

3.3 Comprehensive performance results

Figure 9 presents the trends in financing ability,economic benefits,reliability,social responsibility,user satisfaction,and carbon-emission indicators in Figs.9 (a) -(f),with comprehensive performance shown in Fig.9 (g).

Fig.9 Comprehensive benefits of power-grid enterprise

From Fig.9,the following observations can be made:

1) Carbon-emissions show an overall decreasing trend,resulting in lower scores.This decline is primarily due to increasing demand for power load.Given a fixed power-grid loss rate,carbon-emissions from transmission/distribution losses increase significantly each year,contributing to the decrease in carbon-emission scores.

2) The costs associated with carbon-emissions leads to an increase in transmission/distribution prices.This increase impacts the financing ability and user satisfaction of power consumers negatively,while also contributing to an increase in economic benefits.The investment capability of power-grid enterprises weakens as a result,which in turn affects reliability.However,bearing the costs of carbonemissions significantly enhances the social responsibility of the enterprises,ultimately improving their scores in this aspect.

3) When considering carbon-emissions,the comprehensive performance initially improves during the early stages of oversight due to a significant improvement in social responsibility.The effects of new carbon-emission costs on transmission/distribution prices and investment capacity were initially delayed.However,in the middle and later stages of supervision,transmission/distribution prices increased significantly.The user-satisfaction index score decreased,and the financing ability of the power-grid markedly declined.Consequently,the overall performance of the power-grid enterprise suffered due to reduced financing capacity.

3.4 Suggestions

Therefore,within the context of the carbon market,the key to enhancing the overall performance of power-grid enterprises is to effectively reduce carbon-emissions.It is suggested that power-grid enterprises proceed as follows:

1) Strengthen the management of transmission and distribution line power loss by applying advanced technology and equipment to ensure the efficient operation of power systems.

2) Construct intelligent power systems with a high ratio of renewable energy sources to satisfy clean energy demands.In the future,by tightening the free carbonemission quota,power-grid enterprises can increase their clean power to reduce carbon-emissions from power consumption.To better fulfill large-scale,highly proportionate,and point-to-point accurate access to clean energy demands,power-grid enterprises should reinforce smart grid construction and flexibly allocate resources to ensure the effective integration of new energy sources while maintaining system safety and stability.

3) Develop new carbon financial businesses.In the future,power-grid enterprises can actively engage in comprehensive carbon asset management by investing in carbon-emission quotas and developing and investing in China-certified emission reduction projects to reduce their own carbon-emission costs.

4 Conclusions

This study focuses on analyzing the causal feedback relationship between the carbon/electricity market and the investment and operation of power-grid enterprises in China.A novel SD model was developed to comprehensively evaluate the impact of the carbon market on the investment and operation of power-grid enterprises.Using a specific provincial power-grid as a case study,this study utilizes the SD model to simulate trends in the transmission/distribution of electricity prices and investment decision-making for power-grid enterprises over a 10-year period following the base period.The simulation results were compared before and after considering the carbon-emissions.The findings highlighted that the inclusion of carbon-emission costs leads to an increase in transmission/distribution electricity prices,affects investment capacity,and reduces the comprehensive performance of power-grid enterprises.Therefore,in the carbon market,power-grid enterprises should enhance management practices related to transmission line losses,continuously improve technological and equipment levels,and ensure the efficient operation of power-grid enterprises.

This study investigated the impact of the carbon market on the investment benefits of power-grid enterprises.However,in the 10-year simulation for a specific Chinese provincial power-grid based on the SD model,fixed values of carbon prices and carbon-emission factors were used,while their actual values should be time-varying.Therefore,the introduction of dynamic carbon prices,dynamic carbon-emission factors,and other parameters into the SD simulation will be the focus of future work.

Acknowledgments

This study was supported by the National Natural Science Foundation of China (Grant No.52107087).

Declaration of Competing Interest

The authors have no conflicts of interest to declare.