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Article

Time Limit of Environmental Benefits of Renewable Energy Power Projects—Analysis Based on Monte Carlo Simulation

by
Nan Shang
1,
Guori Huang
1,
Yuan Leng
1,
Jihong Zhang
2 and
Angxing Shen
2,*
1
Energy Development Research Institute, China Southern Power Grid Co., Ltd., Guangzhou 510663, China
2
Institute of Quality Development Strategy, Wuhan University, Wuhan 430072, China
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(20), 14687; https://doi.org/10.3390/su152014687
Submission received: 23 August 2023 / Revised: 24 September 2023 / Accepted: 9 October 2023 / Published: 10 October 2023
(This article belongs to the Special Issue Public Policy and Green Governance)
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Abstract

:
The supply of green electricity certificates (GECs) exceeds the demand, leading to companies being more willing to purchase GECs to meet their emission reduction obligations. However, concerns have been raised about the environmental impact of renewable energy (RE) projects labeled as “greenwashing”. Drawing on the “additionality” theory, we developed a cost model with construction, operation, and discount rates. We utilized cost data from China’s onshore wind and photovoltaic power generation in our study. After 10,000 Monte Carlo simulations, we made the following findings: (1) The environmental benefits of RE power generation diminish over time, and the time limit for judging whether RE projects have additional costs compared with traditional thermal power should be considered; (2) The time limit for marginal environmental effects of China’s onshore wind and photovoltaic power generation is estimated to be 7.65–10.78 years and 5.44–7.25 years, respectively. The analysis methods and ideas proposed in this paper can provide reference for the development of the GEC system in China and even other countries.

1. Introduction

Addressing climate change has become the consensus among most countries. Since the Paris Agreement came into force in 2016, 193 countries and the European Union have signed the agreement [1]. The transition to a low-carbon energy structure is crucial for promoting green economic and social development. To expedite this transition, governments worldwide have implemented subsidy policies and plans to support renewable energy projects. Notable examples include Europe’s “20-20-20 by 2020” plan [2], China’s five-year plans, and the feed-in tariff policy [3].
The global renewable energy (RE) power generation industry has experienced significant market expansion under the incentives of relevant policies. According to statistics from the International Renewable Energy Agency (IREA), the installed capacity of global onshore wind power has rapidly increased from around 300 GW to 835 GW since 2013. Photovoltaic power generation has also expanded nearly eight times [4]. The growing market demand has encouraged numerous power generation companies to enter the competition, leading to increasingly prominent cost and price advantages in the RE power generation industry [5]. Sufficient market competition has driven the progress of related technologies in global onshore wind and photovoltaic power generation. Core components such as wind turbines and photovoltaic (PV) cells have significantly improved in efficiency and cost control [6,7]. The industry’s rapid expansion has prompted enterprises to enhance their competitiveness through large-scale and standardized production, further amplifying the market’s scale effect. As a result, the cost of global RE power generation is decreasing annually [8], with many new RE power generation projects even having huge cost advantages over traditional thermal power.
A green electricity certificate (GEC) is an associated product of the rapid global development of RE power generation. These certificates serve as proof of the environmental benefits of RE power and are a key policy tool for enterprises to achieve sustainability and fulfill voluntary emission reduction commitments [9]. However, the current use of GECs to meet enterprises’ green goals is facing widespread scrutiny from society. It is argued that purchasing GECs is a form of ‘greenwashing’ [10]. For instance, in 2015, 97 listed companies worldwide claimed to have achieved an average annual emission reduction of over 20 Mt by purchasing GECs, which accounted for only 1% of the global RE power in that year [11]. However, the actual emission reduction achieved was almost negligible. The oversupply of GECs in the market, due to long-term preferential policies and subsidies for RE power projects globally, has led to extremely low prices for GECs [12]. Consequently, companies lack the ‘additional’ motivation to achieve their own emission reductions and instead opt to purchase inexpensive GECs to fulfill their commitments. In such cases, the circulation of GECs becomes a form of ‘creative accounting’ with no actual environmental benefits.
With the gradual decline in global preferential policies for RE feed-in tariffs [13] and the rapid development of the carbon market, attention has shifted to the relationship between green power and the carbon market. The question arises: can green electricity consumption offset carbon emission reduction? Different regions have different policies, but regardless of their approach, if green power can be recognized and offset by carbon allocations, it will provide significant additional carbon benefits to RE generation companies. However, if a large number of GECs without proper additionality are used for carbon offsets, the actual environmental benefits of this mechanism will disappear, jeopardizing the effectiveness of carbon emission reduction and the achievement of nationally determined contribution (NDC) goals [14].
This paper examines the concept of ‘additionality’ in carbon voluntary emission reduction projects, specifically focusing on the clean development mechanism (CDM) [15,16,17]. It proposes the underlying logic for RE power generation projects (or corresponding greenhouse gas emission certificates) to achieve environmental benefits through ‘additionality’. The United Nations Framework Convention on Climate Change (UNFCCC) provides an internationally accepted definition of ‘additionality’, which is detailed in Section 3.1. The requirement is that, without external subsidies, the emission reduction project should be less attractive than traditional schemes in terms of cost, finance, and economy. Furthermore, the ‘Guidelines for Validation and Certification of Greenhouse Gas Voluntary Emission Reduction Projects’ emphasize that ‘additionality’ ensures that the project activities are necessary to generate additional emission reductions [18]. It is evident that the concept of additionality in emission reduction projects encompasses both ‘cost additionality’ and ‘effect additionality’.
For the ‘effect additionality’ of RE power, compared with traditional coal power, it is natural to achieve carbon emission reduction. However, with the increase in the proportion of RE power, the old part becomes a component of the power system, and its ‘effect additionality’ will also decrease over time. The focus should shift towards the ‘cost additionality’ of RE projects, which refers to whether they incur additional costs compared with traditional coal power generation. Projects are considered eligible for carbon offsets if they qualify for additionality over a period of time. In order to be eligible for carbon offsets, RE projects must demonstrate additionality over a specific period of time. It is important to determine the duration of environmental benefits obtained from RE power projects and set a time limit for compensation policies. As technology advances, the cost of RE power generation has significantly decreased and can even compete with traditional thermal power [19,20]. Therefore, under the basic theory of the existing power market, will RE power generation projects still have cost additionality? How long can this cost additionality last? Has the government given compensation for environmental benefits over a long period of time? How many years is most reasonable to set the time limit for PV and wind power subsidy? There is little discussion in existing research.
Since China is the country with the fastest development of RE in the world [4,21], it is more representative to use China as the research focus. Therefore, this paper models the cost, investment, and development data of China’s onshore wind power and PV generation industries. We use Monte Carlo simulation to determine a more reasonable compensation period after 10,000 data simulations. The results indicate that the time limit for the environmental benefits of China’s onshore wind and PV power generation is estimated to be 7.65–10.78 years and 5.44–7.25 years, respectively. This can provide a certain reference for the development of China and even the global GEC system. The discussion in this article also makes up for the lack of research on the time limit of environmental benefits.
The remainder of this paper is organized as follows. Section 2 is a theoretical analysis of the environmental benefits of GECs; Section 3 expounds the additionality, cost additionality, and the time limit of environmental benefits; Section 4 is the data and model settings used in this paper; Section 5 discusses the results and of the simulations; and Section 6 presents conclusions and policy implications.

2. Theoretical Analysis of Environmental Benefits of GECs

GEC refers to an electronic certificate with a unique identification code issued by the state for each megawatt-hour of RE grid-connected electricity [22]. In 2017, China’s GEC mechanism was officially launched, allowing one to obtain excess subsidies by selling the environmental benefits of GECs. However, at that time, GECs were only issued for onshore wind power and centralized photovoltaics. On 3 August 2023, the Chinese government updated the policy to include all RE power within the scope of GEC issuance [23]. Since then, a GEC has been the only proof of the environmental attributes of RE power, and also the only certificate for identifying production and consumption. As a result, two GEC trading mechanisms have emerged: voluntary subscription transactions based on the “separation of certificates and electricity” and green electricity transactions based on the “integration of certificates and electricity”.
In addition, as the main source of projects in the world’s carbon credit market, RE power projects are easy to measure and have simple accounting methods, so the corresponding carbon emission reductions can be calculated more conveniently. For instance, the Verified Carbon Standard (VCS), which accounts for 62% of the total issued carbon credits, has registered approximately 2017 projects, with 1244 of them being RE power projects. The issued volume was 480 million tons, accounting for 48% of the total volume of 1095 million tons [24]. As a result, the problem of “double accounting” also arises, which means an RE power project applies for both GECs and carbon credits. Therefore, the emission reductions are reused, and the green effect is greatly reduced. The relationship between GECs and carbon credits is shown in Figure 1.
As illustrated in Figure 1, the use of carbon credits for offsetting is a “result” type of mechanism, resulting in the conversion of green electricity into emission reductions (unit: t CO2e). However, the use of GECs is a “process” type of accounting mechanism. When accounting for indirect emissions, the green power (unit: MWh) in the purchased power part will be calculated as zero emissions or the corresponding power usage will be deducted. At present, the use of GECs or carbon credits issued by RE power to fulfill emission reduction responsibilities is being questioned for “greenwashing” behavior [25]. Therefore, in order to study whether GECs can promote additional RE generation, Brander, M. et al. analyzed the supply and demand curve [11], as shown in Figure 2.
Among Figure 2, the vertical axis represents the price of GECs, and the horizontal axis represents the quantity of GECs. The Supply curve represents the supply of GECs, while D1, D2, and D3 represent different levels of demand for GECs.
From the perspective of supply, the current GEC market is experiencing a serious oversupply situation, resulting in a long-term low price on the Supply curve. This is because, with the rapid decline in the cost of RE power generation [8], most countries, such as China [26], the United Kingdom [27,28], Germany [29], etc., support RE power based on fixed electricity prices and consumption guarantee mechanisms, making the supply quantity of GECs increase continuously. Referring to data of China’s GEC subscription trading platform, as of August 2023, China has issued more than 118 million GECs, but the cumulative transaction volume is only 41.63 million, resulting in a supply demand ratio of 2.83 [30]. Statistics from the National Renewable Energy Laboratory (NREL) on the total size of the U.S. voluntary green electricity market show that the total power generation registered by Green-e is approximately 3–4 times larger than that required by the entire market [31].
From the perspective of demand, the growth of companies that have voluntarily reduced their emissions or committed to using 100% RE power is slow. The current demand for GECs is far from reaching the level of Q1, so the marginal environmental effects of RE power have been questioned to a greater extent. Q1 is the threshold of the “existing” GEC supply on the market (that is, the historical cumulative amount). During the period from 0 to Q1, the transformation of demand D1 to D2 only involves the distribution of “existing” GECs, which is equivalent to only consuming historically accumulated GECs or carbon credits, and the marginal carbon emission reduction effect of RE power projects is almost zero. Once the demand reaches the right side of Q1 (such as D3), the market equilibrium formed will stimulate the “additional” investment and consumption of RE power generation projects, and at the same time its price will rise linearly. Only then will new RE electricity generate marginal carbon reduction effects.
From the earliest perspective, the establishment of green certificates is to reduce the pressure on new energy subsidies and guide green consumption [32,33], which can increase the power generation decisions of renewable energy providers. However, market participants are often told that they increase RE generation and reduce carbon emissions by paying for green labels [34], which in fact currently lacks credibility. The GEC market is unlikely to change the investment decisions of renewable power developers because it does not provide a reliable source of risk-adjusted revenue [35]. In the face of low market prices, companies basically purchase GECs or carbon credits to complete low-cost compliance [14]. However, the environmental benefits of promoting the investment and consumption of RE power generation have not been realized [36]. In short, buying GECs that do not produce additional benefits is just a kind of “smart accounting” [25]. In addition, there are also information errors between GECs and carbon credit issuing organizations. Many RE power generation projects not only apply for GECs, but also apply for carbon credit certification, resulting in the repeated use and deduction of emission reductions [37].
Based on this, if GECs lacking marginal environmental effects are allowed to be used for carbon emission reduction declarations, the actual environmental benefits of this mechanism will disappear, greatly undermining the effectiveness of carbon emission reduction and the achievement of NDC goals. To achieve a balance between fairness and efficiency, it is crucial to ensure that only RE generators in genuine need of subsidies can benefit from GECs, while also preventing the mechanism from being in a state of severe failure. Therefore, the green benefits attached to GECs must be controlled within the effective time limit. This paper will analyze the “additionality” requirements of voluntary carbon emission reduction projects under the CDM.

3. Cost Additionality and Time Limit of Environmental Benefits

3.1. Definition of Additionality

RE power generation has given rise to numerous emission reduction projects, which, in turn, receive subsidies in the form of feed-in tariffs and carbon offset benefits. However, the certification of green attributes requires the presence of ‘additionality’. The United Nations Framework Convention on Climate Change (UNFCCC) defines additionality internationally as the requirement that emission reductions achieved through such projects are additional compared with the ‘baseline’ [38]. Without external subsidies, emission reduction projects face various obstacles related to specific financial efficiency, financing channels, technical risks, market popularization, and resources, which are difficult to overcome on their own. That is, without external subsidy certification, these projects are likely to be less attractive than the alternative scheme in terms of cost, finance, and economy, and may encounter certain commercialization barriers [39]. In addition, China’s policy also emphasizes that “additionality” requires that the additional emission reduction of the project will not be generated without the project activities [18].
In general, the subsidies provided for RE power generation are based on the underlying premise of green attributes. However, the demonstration of green attributes requires further evidence regarding whether the project incurs additional costs and produces additional emission reductions. The demonstration of additionality typically involves four steps: ‘baseline scenario identification’, ‘obstacle analysis’, ‘investment analysis’, and ‘universality analysis’. Following these proofs and investigations, it is essential to confirm and evaluate the ‘baseline’ of the proposed project. It is important to consider whether there are any obstacles to commercialization, whether the investment return meets the relevant standards, and whether the project has promising prospects.

3.2. Cost Additionality

It is evident that RE power generation can receive subsidies such as feed-in tariffs and carbon allowances. These subsidies are granted based on the certification of the green attributes of RE power generation. To qualify for these subsidies, it is necessary to demonstrate cost and emission reduction additionality, as both aspects are essential. Given the controversies surrounding the effectiveness of green electricity in carbon reduction and power grid improvement, it is crucial to investigate the existence and duration of these subsidies from a cost perspective. This research paper aims to examine whether emission reduction projects incur additional costs, which we refer to as ‘cost additionality’.
Generally speaking, most of the benchmark rates of return of China’s power generation industry are not higher than 8% [40,41]. However, relevant data show that the internal rate of return of most wind power and photovoltaic projects in China has already exceeded 8% [42,43,44]. Even for projects with a low internal rate of return, various forms of government subsidies can compensate for it. This implies that these projects do not require additional costs in essence and can be commercialized without obstacles. The market has recognized their rates of return, suggesting the absence of ‘cost additionality’. Currently, due to technological breakthroughs and a substantial increase in industrial scale, the unit production cost of wind power, photovoltaic power generation, and other RE power generation projects has significantly decreased. In fact, they now possess great price competitiveness compared with traditional coal power. Therefore, it is vital to conduct further research on when and how ‘cost additionality’ occurs and how long it can persist.

3.3. Time Limit of Environmental Benefits

In this paper, we refer to the maintenance time of the environmental benefits of RE power generation as its ‘time limit’, which represents the duration for which the cost additionality of the projects can be sustained.
The discussion of “time limit” originated from the requirements of the crediting period of the clean development mechanism (CDM) under the “Kyoto Protocol” and the inheritance of Chinese certified emission reduction (CCER) standards. Various factors, such as technological progress, industrial structure, energy composition, and policies, have a significant impact on the baseline, leading to uncertainties and risks in the emission reductions generated by project activities. Consequently, China’s policy offers two options for the crediting period: a fixed crediting period and a renewable crediting period [18].
The fixed crediting period means that the period and starting date of the project activity can only be determined once, that is, once the project activity is registered, it cannot be renewed or extended. In this case, the crediting period of a proposed CCER project activity can be up to 10 years. The renewable crediting period means that each single period can be up to 7 years, and this can be updated up to two times (a maximum of 21 years). Most photovoltaic and wind power projects use renewable crediting periods when possible.
It is important to note that the cost of RE power generation has significantly decreased in recent years [8]. Under the requirement of cost additionality, is the original renewable crediting period of 7–21 years set too long? Is there a green attribute subsidy given to RE power generation for an excessively long period of time? How long can the cost additionality of RE generation be maintained? How long is most reasonable to set the time limit of photovoltaic and wind power generation? This paper will conduct modeling research in Section 4.

4. Data and Models

4.1. Data Description

China has made significant contributions to the rapid reduction in the cost of global RE power generation through its continuous improvement in the global supply chain and the R&D progress of related technologies. As shown in Figure 3 [8], since 2010, the total installation cost of onshore wind power in China has dropped from 1554 USD/kW to 1157 USD/kW over a span of ten years, resulting in a 25.5% reduction. The average annual operation and maintenance cost of onshore wind power has dropped from 55 USD/kW/year to 15 USD/kW/year, with a drop of 72.8%. In addition, the total installation cost of PV generation in China has dropped from 3796 USD/kW to 628 USD/kW, which leads to a total reduction of 83.45% in ten years. The average annual operation and maintenance cost of PV generation has been reduced from 205 USD/kW /year to 18 USD/kW/year, with a drop of 91.07%.
The initial investment cost and O&M cost of onshore wind power and PV generation are sourced from “Renewable Power Generation Costs in 2021”. The average feed-in tariff and the average annual utilization hours are from the “China Power Industry Annual Development Report” [45]. To account for currency value changes, this paper refers to the average inflation rate data of China in the past ten years from the National Bureau of Statistics [46] to set the discount rate. The specific parameters are shown in Table 1 below.
It is important to note that there may be a time lag in the initial construction of most photovoltaic and wind power projects. However, due to the sharp decline in the cost of RE power generation in the past decade, there will be a significant cost gap for projects put into operation in different years. In other words, there are not only low-cost new RE power generation projects, but also most of the high-cost projects are still in operation. Therefore, whether the data reference period is too early or too late, it is unfair and difficult to be representative. For example, if the calculation is based on the low cost of 2021, the final “time limit” result will be shorter, which is unfair to past high-cost construction projects. As shown in Figure 3, the overall construction cost of wind power and photovoltaic power in 2016 was similar, and both were at relatively moderate levels in recent years. This will strive to balance efficiency and fairness as much as possible. For this reason, this paper uses the cost data from 2016 for model simulation.

4.2. Model Settings

In order to reduce misleading final results, Centeno and Wogrina proposed a cost model for capacity expansion planning that considers overall investment costs and residual value [20]. Referring to their analysis logic, this paper establishes the following unit cost calculation model for power generation:
U C i , n = I C n − ∑ j = 1 i ( P n × h n − O C n ) ( 1 + r ) j  
Among them, U C i , j , n represents the unit cost of the power generation of type n in the i year (CNY/kW); i and n represent the actual operation time (year) and power generation type (thermal power, wind power, or photovoltaic power) of the project, respectively; I C n indicates the initial investment cost of the power generation of type n (CNY/kW); P n represents the average feed-in tariff of the power generation of type n (CNY/kWh); h n represents the annual average utilization hours of the power generation of type n (h); O C n represents the annual average O&M cost of the power generation of type n (CNY/kW); and r represents the discount rate (%).
Due to differences in technology levels, price levels, and natural endowments, this paper sets the average O&M cost and discount rate in the model as a range value, referring to Section 4.1. Considering the volatility of the economy and the uncertainty of service provider prices, the use of range values can improve the reliability of the calculation. For models with uncertain distributions, the Monte Carlo method can reduce errors through randomness [47]. In addition, the accuracy of the Monte Carlo method is proportional to the number of simulations. Therefore, we completed 10,000 Monte Carlo simulations and model operations through Python 3.9 to get as close to reality as possible.

5. Results and Discussion

5.1. Single Operation Results

The output of a single operation of the model is illustrated in Figure 4. The horizontal axis represents the operation time of each power generation project, and the vertical axis represents the change trend of the unit cost of each power generation type. During the initial stage of construction, thermal power, onshore wind power, and photovoltaic power generation need to bear unit costs of 5750 CNY/kW, 9660 CNY/Kw, and 9051 CNY/kW, respectively. However, the cost changes vary depending on the profit recovery levels.
The duration of the environmental benefits of RE power generation can be assessed based on the concept of ‘cost additionality’, which refers to whether additional costs need to be incurred. Currently, thermal power generation is the most common form in China, accounting for approximately 67.5% of total power generation. While RE power generation can indeed achieve green emission reduction effects compared with thermal power, if the cost of RE becomes lower than that of thermal power, it becomes economically inevitable to choose RE in the market. Therefore, the production of green power to achieve carbon emission reduction becomes a natural behavior for all entities. In this regard, companies utilizing RE for electricity generation have not achieved any additional efforts and ambitions. In general, once the cost of onshore wind power and photovoltaic power generation falls below that of thermal power, its “cost additionality” will disappear, and the so-called environmental benefits will also be nothing.
In summary, the x-coordinates of the intersecting points of cost changes of onshore wind power, PV generation, and thermal power in Figure 4 are 9.14 and 5.58, indicating that the time limit of the environmental benefits of onshore wind power and PV generation are 9.14 years and 5.58 years, respectively.

5.2. Multiple Simulation Results

Due to the contingency and limitations of a single result, this paper also carried out 10,000 simulations based on the floating parameter range. The results are shown in Figure 5 and Figure 6.
Figure 5 illustrates the box-line distribution of multiple simulation results of onshore wind power in China. The blue and orange parts represent the concentrated trend and distribution of simulation results, respectively. After removing outliers, the obtained results range from 7.23 to 11.23 years, which generally follows a normal distribution. The box range is 8.46 to 9.57 years, with a median of 8.99 years. For the distribution chart, we can see that the two gray dotted lines represent the confidence interval with a confidence level of 95% (between two black stars). Based on this, this paper suggests that the time limit of environmental benefits of onshore wind power in China should be set at 7.65–10.78 years.
Figure 6 displays the box-line distribution of multiple simulation results of photovoltaic power generation in China. The blue and orange parts represent the concentrated trend and distribution of simulation results, respectively. After removing outliers, the obtained results range from 5.08 to 7.59 years, which generally conforms to the normal distribution. Among them, the value range of the box is 5.9–6.58 years, and the median is 6.23 years. For the distribution chart, we can see that the two gray dotted lines represent the confidence interval with a confidence level of 95% (between two black stars). Therefore, this paper suggests that the time limit of the environmental benefits of PV generation in China should be set at 5.44–7.25 years.

5.3. Discussion

Based on the results in Section 5.1 and Section 5.2, it can be observed that 6–10 years is the approximate range for Chinese RE power generators to obtain environmental benefits. This time limit is an important prerequisite for judging the cost additionality of a project. Referring to the analysis in Section 2, the unlimited issuance of green certificates or carbon credits will only allow developers to sit back and seize “unlimited” profits through “limited” renewable energy projects. In other words, they will not continue to invest in new projects, which will eventually affect the market equilibrium and lead to low efficiency of overall emission reduction. Therefore, from the calculation of this article, developers can obtain considerable subsidies within a 6–10 year period, which aligns with the original purpose of the GEC mechanism. However, once the time limit is exceeded, the environmental benefits will no longer exist. Motivated by the pursuit of profit, developers need to invest in new RE power generation projects for new subsidy qualifications. The substantial changes in the power structure it brings will be beneficial to the long-term development of China’s low-carbon pathway. Due to the advancement of technology and supply chains, the various costs of RE power generation may fluctuate greatly, so the data referenced in the mechanism of this article will also change accordingly. When we find that the “time limit” result is less than or approximately equal to zero, the cost of RE power generation in China will be significantly lower than that of traditional thermal power. It means that, from an economic point of view, the withdrawal of coal power will become an inevitable trend. Therefore, the government should promptly adjust its subsidy policy for RE projects.

6. Conclusions and Policy Implications

6.1. Conclusions

This paper examined the current rapid reduction in the cost of RE generation and the challenges faced by GECs. The concept of cost additionality was used to analyze the time limit for the environmental benefits of RE generation. Modeling and 10,000 Monte Carlo simulations were performed and, finally, the following conclusions were drawn:
Firstly, the environmental benefits of RE power generation, such as carbon emission reduction, enable projects to receive subsidies in the form of feed-in tariffs and carbon offsets. However, in addition to carbon emission reduction, environmental benefit certification also requires ‘cost additionality’. This means that RE power generation projects must incur additional costs compared with traditional power generation in order to be eligible for additional subsidies.
Secondly, the modeling analysis reveals that RE power generation projects do exhibit cost additionality in the initial stages, but only until their costs decrease rapidly to a level lower than that of thermal power generation. This implies that the environmental benefits of RE power have a certain time limit. After conducting numerous simulations, this paper concludes that the time limit of the environmental benefits of onshore wind power should be set between 7.65 and 10.78 years, while the time limit of PV generation should be set between 5.44 and 7.25 years. Once the operation time of the project exceeds the limit, its environmental benefits will disappear, and it will no longer be able to realize the interests of carbon offsets.
In addition, the research based on China in this paper can serve as a valuable reference for other developing countries. The transformation of the energy system and the replacement of fossil fuels are inevitable trends for the vast majority of developing countries. In this process, the government will undoubtedly provide strong support to the RE power generation industry. However, it is important to note that the environmental benefits of electricity from RE sources are not unlimited. This paper focuses on China, the largest developing country and the world’s largest producer of RE power, and finds that the time limit for maintaining green power is only 6–10 years based on modeling. This finding provides a valuable reference for developing countries when formulating subsidy policies.

6.2. Policy Implications

Based on the analysis and conclusions, this paper proposes the following policy recommendations:
Firstly, as the current cost of RE power generation in China and feed-in tariff subsidies are rapidly declining, the focus of the market has shifted towards the deduction mechanism for green power to the carbon market. Once the carbon emission reduction brought by green power can be mutually recognized with carbon allowances, it will bring sustainable carbon benefits to RE power generation companies. However, it is crucial to link this benefit to a time limit; otherwise, unlimited carbon credits will seriously affect the operational efficiency of China’s carbon market and hinder the country’s low-carbon development process. Therefore, this paper concludes that the time limit of the environmental benefits of China’s onshore wind power and PV generation is estimated to be 7.65–10.78 years and 5.44–7.25 years, respectively, which can serve as a reference for the government when implementing the power–carbon linking mechanism in the future.
Secondly, the cost comparison model presented in this paper was analyzed at the national average level, and it can be further refined and improved. When new RE power generation projects are developed in the future, the government can utilize an enhanced model that takes into account unique resource endowment, utilization hours, cost expenditure, and marginal profit to conduct specific calculations for each project. This approach would enable each new project to obtain a distinct time limit label for environmental benefits.
While this article has contributed to the understanding of the environmental benefits of renewable energy power, there are still limitations. The current cost model only considers factors such as initial construction costs, annual O&M costs, discount rate, and feed-on-tariff. Further research can be combined with life cycle analyses to incorporate more details into the model, such as permitting costs, scrapping costs, and recycling. In addition, researchers can also analyze the environmental and economic effects in different scenarios based on the “time limit” results of this article.

Author Contributions

Conceptualization, N.S. and J.Z.; methodology, A.S.; validation, J.Z. and A.S.; formal analysis, J.Z. and A.S.; writing—original draft preparation, A.S.; writing—review and editing, J.Z.; visualization, A.S.; supervision, G.H. and Y.L.; project administration, N.S. and J.Z.; funding acquisition, N.S., G.H. and Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (No. 72174151); the Humanities and Social Science Fund of the Ministry of Education of China (No. 21YJAZH113); and Wuhan University—China Southern Power Grid Project “Research on Green Electricity Consumption, Carbon Emission Reduction Credit Products in Carbon Emission Trading Market”.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available upon request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. UN Climate Change Conference (COP21). The Paris Agreement; The United Nations: Paris, France, 2015. [Google Scholar]
  2. Širá, E.; Kotulič, R.; Kravčáková Vozárová, I.; Daňová, M. Sustainable Development in EU Countries in the Framework of the Europe 2020 Strategy. Processes 2021, 9, 443. [Google Scholar] [CrossRef]
  3. Zhao, H.; Guo, S.; Fu, L. Review on the costs and benefits of renewable energy power subsidy in China. Renew. Sustain. Energy Rev. 2014, 37, 538–549. [Google Scholar] [CrossRef]
  4. International Renewable Energy Agency (IRENA). Renewable Capacity Statistics 2023; International Renewable Energy Agency: Abu Dhabi, United Arab Emirates, 2023. [Google Scholar]
  5. Timilsina, G.R. Are renewable energy technologies cost competitive for electricity generation? Renew. Energy 2021, 180, 658–672. [Google Scholar] [CrossRef]
  6. Borràs Mora, E.; Spelling, J.; Weijde, A.H. Global sensitivity analysis for offshore wind cost modelling. Wind Energy 2021, 24, 974–990. [Google Scholar] [CrossRef]
  7. Ling-Zhi, R.; Xin-Gang, Z.; Xin-Xuan, Y.; Yu-Zhuo, Z. Cost-benefit evolution for concentrated solar power in China. J. Clean. Prod. 2018, 190, 471–482. [Google Scholar] [CrossRef]
  8. International Renewable Energy Agency (IRENA). Renewable Power Generation Costs in 2021; International Renewable Energy Agency: Abu Dhabi, United Arab Emirates, 2022. [Google Scholar]
  9. Verbruggen, A. Tradable green certificates in Flanders (Belgium). Energy Policy 2004, 32, 165–176. [Google Scholar] [CrossRef]
  10. Moodaley, W.; Telukdarie, A. Greenwashing, Sustainability Reporting, and Artificial Intelligence: A Systematic Literature Review. Sustainability 2023, 15, 1481. [Google Scholar] [CrossRef]
  11. Brander, M.; Gillenwater, M.; Ascui, F. Creative accounting: A critical perspective on the market-based method for reporting purchased electricity (scope 2) emissions. Energy Policy 2018, 112, 29–33. [Google Scholar] [CrossRef]
  12. Beliën, J.; De Boeck, L.; Colpaert, J.; Cooman, G. The best time to invest in photovoltaic panels in Flanders. Renew. Energy 2013, 50, 348–358. [Google Scholar] [CrossRef]
  13. Wang, Y.; Lin, B. Performance of alternative electricity prices on residential welfare in China. Energy Policy 2021, 153, 112233. [Google Scholar] [CrossRef]
  14. Ruiz Manuel, I.; Blok, K. Quantitative evaluation of large corporate climate action initiatives shows mixed progress in their first half-decade. Nat. Commun. 2023, 14, 3487. [Google Scholar] [CrossRef]
  15. Schneider, L. Assessing the additionality of CDM projects: Practical experiences and lessons learned. Clim. Policy 2009, 9, 242–254. [Google Scholar] [CrossRef]
  16. Samal, R.K.; Tripathy, M. Cost and emission additionality of wind energy in power systems. Sustain. Energy Grids Netw. 2019, 17, 100179. [Google Scholar] [CrossRef]
  17. Hayashi, D.; Michaelowa, A. Standardization of baseline and additionality determination under the CDM. Clim. Policy 2013, 13, 191–209. [Google Scholar] [CrossRef]
  18. National Development and Reform Commission of China. Guidelines for Validation and Verification of Greenhouse Gas Voluntary Emission Reduction Projects; National Development and Reform Commission of China: Beijing, China, 2012.
  19. Helveston, J.P.; He, G.; Davidson, M.R. Quantifying the cost savings of global solar photovoltaic supply chains. Nature 2022, 612, 83–87. [Google Scholar] [CrossRef] [PubMed]
  20. Centeno, E.; Wogrin, S. Annualized versus Overall Investment Cost in Generation Capacity Expansion Planning. In 2021 IEEE Madrid PowerTech; IEEE: Madrid, Spain, 2021; pp. 1–6. [Google Scholar]
  21. Zhao, J.; Zhang, Q.; Zhou, D. The impact of marketed on-grid price on China’s photovoltaic industry under the background of carbon neutrality. Environ. Sci. Pollut. Res. 2023, 30, 96231–96251. [Google Scholar] [CrossRef] [PubMed]
  22. National Development and Reform Commission of China. Notice on Trial Implementation of Renewable Energy Green Power Certificate Issuance and Voluntary Subscription Transaction System; National Development and Reform Commission of China: Beijing, China, 2017.
  23. National Development and Reform Commission of China. Notice on Promoting the Full Coverage of Renewable Energy Green Electricity Certificates and Promoting the Consumption of Renewable Energy Electricity; National Development and Reform Commission of China: Beijing, China, 2023.
  24. VCM Primer. The Voluntary Carbon Market Explained; VCM Primer: Washington, DC, USA, 2021. [Google Scholar]
  25. Bjørn, A.; Lloyd, S.M.; Brander, M.; Matthews, H.D. Renewable energy certificates threaten the integrity of corporate science-based targets. Nat. Clim. Chang. 2022, 12, 539–546. [Google Scholar] [CrossRef]
  26. National Development and Reform Commission of China. Policy Disclosure; National Development and Reform Commission of China: Beijing, China, 2021.
  27. Castaneda, M.; Zapata, S.; Cherni, J.; Aristizabal, A.J.; Dyner, I. The long-term effects of cautious feed-in tariff reductions on photovoltaic generation in the UK residential sector. Renew. Energy 2020, 155, 1432–1443. [Google Scholar] [CrossRef]
  28. Johnson, R.C.; Mayfield, M. The economic and environmental implications of post feed-in tariff PV on constrained low voltage networks. Appl. Energy 2020, 279, 115666. [Google Scholar] [CrossRef]
  29. Ming-Zhi Gao, A.; Fan, C.-T.; Kai, J.-J.; Liao, C.-N. Sustainable photovoltaic technology development: Step-by-step guidance for countries facing PV proliferation turmoil under the feed-in tariff scheme. Renew. Sustain. Energy Rev. 2015, 43, 156–163. [Google Scholar] [CrossRef]
  30. China National Renewable Energy Centre. China Green Electricity Certificate Subscription Trading Platform; China National Renewable Energy Centre: Beijing, China, 2023. [Google Scholar]
  31. Heeter, J.; Bird, L. Status and Trends in U.S. Compliance and Voluntary Renewable Energy Certificate Markets (2010 Data); National Renewable Energy Lab. (NREL): Golden, CO, USA, 2011. [Google Scholar]
  32. Qubbaj, A.I.; Peiró-Signes, A.; Najjar, M. The Effect of Green Certificates on the Purchasing Decisions of Online Customers in Green Hotels: A Case Study from Saudi Arabia. Sustainability 2023, 15, 5892. [Google Scholar] [CrossRef]
  33. Song, X.; Huang, Y.; Zhang, Y.; Zhang, W.; Ge, Z. An Appraisal on China’s Feed-In Tariff Policies for PV and Wind Power: Implementation Effects and Optimization. Sustainability 2023, 15, 5137. [Google Scholar] [CrossRef]
  34. Gillenwater, M.; Lu, X.; Fischlein, M. Additionality of wind energy investments in the U.S. voluntary green power market. Renew. Energy 2014, 63, 452–457. [Google Scholar] [CrossRef]
  35. Gillenwater, M. Probabilistic decision model of wind power investment and influence of green power market. Energy Policy 2013, 63, 1111–1125. [Google Scholar] [CrossRef]
  36. Delardas, O.; Giannos, P. Towards Energy Transition: Use of Blockchain in Renewable Certificates to Support Sustainability Commitments. Sustainability 2022, 15, 258. [Google Scholar] [CrossRef]
  37. Duan, M.; Wang, Y.; Ma, G. Design of Offsetting Mechanism under Carbon Peaking and Carbon Neutrality Goals; Tsinghua University: Beijing, China, 2023. [Google Scholar]
  38. CDM Excutive Board. Tool for the Demonstration and Assessment of Additionality; United Nations Framework Convention on Climate Change (UNFCCC): Bonn, Germany, 2012. [Google Scholar]
  39. Michaelowa, A.; Hermwille, L.; Obergassel, W.; Butzengeiger, S. Additionality revisited: Guarding the integrity of market mechanisms under the Paris Agreement. Clim. Policy 2019, 19, 1211–1224. [Google Scholar] [CrossRef]
  40. Ye, L.-C.; Rodrigues, J.F.D.; Lin, H.X. Analysis of feed-in tariff policies for solar photovoltaic in China 2011–2016. Appl. Energy 2017, 203, 496–505. [Google Scholar] [CrossRef]
  41. Fu, N.; Mu, H.; Li, N. The impact of carbon trading on China’s renewable energy investment: Case of CDM wind power projects. IOP Conf. Ser. Earth Environ. Sci. 2020, 446, 022054. [Google Scholar] [CrossRef]
  42. Zhang, R.; Shimada, K.; Ni, M.; Shen, G.Q.P.; Wong, J.K.W. Low or No subsidy? Proposing a regional power grid based wind power feed-in tariff benchmark price mechanism in China. Energy Policy 2020, 146, 111758. [Google Scholar] [CrossRef]
  43. Xin-gang, Z.; Zhen, W. Technology, cost, economic performance of distributed photovoltaic industry in China. Renew. Sustain. Energy Rev. 2019, 110, 53–64. [Google Scholar] [CrossRef]
  44. Zhang, Y.; Yuan, J.; Zhao, C.; Lyu, L. Can dispersed wind power take off in China: A technical & institutional economics analysis. J. Clean. Prod. 2020, 256, 120475. [Google Scholar] [CrossRef]
  45. China Electricity Council. China Power Industry Annual Development Report; China Electricity Council: Beijing, China, 2012. [Google Scholar]
  46. National Bureau of Statistics of China. China National Economic Statistics; National Bureau of Statistics of China: Beijing, China, 2023.
  47. Janssen, H. Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence. Reliab. Eng. Syst. Saf. 2013, 109, 123–132. [Google Scholar] [CrossRef]
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Figure 1. Differences between GECs and carbon credits.
Figure 1. Differences between GECs and carbon credits.
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Figure 2. Supply and demand curve of GECs.
Figure 2. Supply and demand curve of GECs.
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Figure 3. Installed cost and average O&M cost of onshore wind power and PV generation in China from 2010 to 2021.
Figure 3. Installed cost and average O&M cost of onshore wind power and PV generation in China from 2010 to 2021.
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Figure 4. Single operation results.
Figure 4. Single operation results.
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Figure 5. Box-line distribution of multiple simulation results of onshore wind power.
Figure 5. Box-line distribution of multiple simulation results of onshore wind power.
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Figure 6. Box-line distribution of multiple simulation results of PV generation.
Figure 6. Box-line distribution of multiple simulation results of PV generation.
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Table 1. Parameter settings.
Table 1. Parameter settings.
2016Initial Investment Cost
(CNY/kW)		Average Annual O&M Cost
(CNY/kW)		Average Feed-in Tariff
(CNY/kWh)		Average Utilization Hours
(h)		Discount Rate
Thermal power5750300–4000.36241862–3%
Wind power9660150–2500.56717452–3%
Photovoltaic9051100–2000.91811292–3%
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Shang, N.; Huang, G.; Leng, Y.; Zhang, J.; Shen, A. Time Limit of Environmental Benefits of Renewable Energy Power Projects—Analysis Based on Monte Carlo Simulation. Sustainability 2023, 15, 14687. https://doi.org/10.3390/su152014687

AMA Style

Shang N, Huang G, Leng Y, Zhang J, Shen A. Time Limit of Environmental Benefits of Renewable Energy Power Projects—Analysis Based on Monte Carlo Simulation. Sustainability. 2023; 15(20):14687. https://doi.org/10.3390/su152014687

Chicago/Turabian Style

Shang, Nan, Guori Huang, Yuan Leng, Jihong Zhang, and Angxing Shen. 2023. "Time Limit of Environmental Benefits of Renewable Energy Power Projects—Analysis Based on Monte Carlo Simulation" Sustainability 15, no. 20: 14687. https://doi.org/10.3390/su152014687

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