1. Introduction
Improving the energy efficiency at all stages of energy systems is considered as a critical action to mitigate climate change while also meeting people’s increasing demand for final energy service [
1]. The IEA (International Energy Agency, Paris, France) claims that the energy efficiency improvement from 2016 to 2018 lowered the energy demand by 4% and avoided 3.5 billion tons of carbon dioxide emissions. It is expected that this energy efficiency improvement will continue to contribute to achieving the 2 °C goal of the Paris Agreement [
2]. At the national level, policies related to energy efficiency have also been the main concern for policymakers, such as in China [
3] and Germany [
4].
As we know, the energy system is a complex system. To improve energy efficiency at different stages in energy systems, many technologies have emerged. For policymakers, given the limitation of time and resources, priority should be given to key technologies that have bigger potential and will deliver better gains [
5]. To identify these key fields of energy efficiency improvements and guide future policymaking, the first step is to estimate the overall energy efficiency performance of the entire energy system.
In previous work, the assessment model of the overall energy efficiency performance of energy systems can be divided into two categories: the top-down energy intensity model and the bottom-up thermodynamic efficiency model [
6]. The energy intensity is defined as the energy consumption per unit of GDP (Gross Domestic Product), providing a top-down approach to connect energy consumption with economic development; however, the energy intensity model cannot fully reflect technological progress in fields underlying energy systems, which will lead to the neglect of some key technologies [
7]. In contrast, the thermodynamic efficiency model can provide a bottom-up approach to observe technological progress underlying energy systems.
Based on different thermodynamic laws, the thermodynamic efficiency model includes the first-law energy efficiency and the second-law energy efficiency (or exergy efficiency). In the first-law energy efficiency model, energy is conserved and cannot be created or destroyed, but the energy quality differences between the inputs and the useful outputs are not considered. This will lead to some unreasonable results. For example, the first-law energy efficiency of a heat pump will be greater than 100%. On the other hand, the exergy efficiency can distinguish the quality difference between 1 kJ electricity and 1 kJ heat by their ability to perform work, where exergy represents the maximum amount of useful work can be obtained when the system is brought to equilibrium with the surroundings [
8]. As a result, exergy is considered as a more scientific metric and the exergy efficiency analysis has been widely used to evaluate the overall energy efficiency performance of energy systems, since exergy can consider both the energy quantity difference and the energy quality difference (see
Section 2.2).
The exergy efficiency analysis of societal energy systems, also referred to as Societal Exergy Analysis (SEA), first divides a societal energy system into several stages, including energy source, energy transformation, and energy end-use, then further analyzes the exergy input and output of each stage, and finally aggregates these stages to evaluate the aggregate exergy efficiency [
9]. Most previous studies of SEA only focus on the energy stages from the energy source to useful energy, as shown in
Figure 1. However, what people need is not energy itself, but the “final services” it provides. For instance, what people really need is not heat energy itself, but the thermal comfort provided by heat energy. Loss not only occurs in the process from the energy source to useful energy but also in providing final services, such as heat losses due to poor insulation of a room [
10]. Therefore, to systematically identify key fields of energy efficiency improvements, the analysis boundary of the exergy efficiency analysis is supposed to be extended to final service.
Moreover, limited attention was paid to the driving factors analysis in the SEA. The analysis of driving factors helps deeply understand the change mechanism of the aggregate exergy efficiency and provide further policymaking interventions. These limited papers mainly analyzed the end-use stage’s driving factors [
11,
12,
13], without considering the final service. Obviously, excessive attention to the end-use stage may overlook other stages’ potential. Therefore, a method of driving factor analysis considering all stages of the whole energy system also needs to be further developed to comprehensively understand changes of the aggregate exergy efficiency.
In the author’s previous studies, a method named “the Logarithmic Mean Divisia Index (LMDI) decomposition method based on energy allocation analysis” was developed ahead to analyzed changes and driving factors of energy consumption (see
Section 2.3), of which the idea can be learnt to fill the research gap mentioned above. In this paper, we develop a high-resolution Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analyse the changes and driving factors of the aggregate exergy efficiency of energy systems, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method considering all stages of energy systems is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency.
China is used as the case study in this investigation. In recent years, China’s economy has experienced rapid development, however with increasing energy demand and carbon emission. The data show that China’s energy consumption and carbon emission have increased at an average annual rate of 3.8% and 2.6% in the past 10 years, respectively [
14]. To tackle this challenge, the improvement of energy efficiency has been given priority and incorporated into China’s national strategy text since the 11th National Five-Year Plan in 2006 [
15,
16,
17]. Further, China is going through a fast transition period with one of the most complex energy systems, and a variety of new technologies are emerging. Therefore, it is essential to have a comprehensive overview of the overall energy efficiency performance of China to evaluate the current efficiency level and find key areas for future improvements.
The key energy-consuming fields in China need to be further analyzed. In recent years, thanks to the efficiency improvement policy in many technical fields, many higher-efficiency devices have been newly built, and most old and low-efficiency devices have been eliminated or reduced [
18]. However, this technology replacement has resulted in the co-existence of a lot of new and old technologies, which resulted in what is known as China’s “Dual Structure” problem. This problem is not only a problem in China but commonly found in many developing countries. Despite the dual structure problem being quite widespread, very little literature has addressed it, and the potential for future improvement has not been clearly identified. Thus, in this investigation, we conducted further analysis of the “Dual structure” problem in China to better guide future efficiency improvement.
The contributions of this paper can be summarized as follows:
The current boundary of SEA is extended to the final service to observe changes of the aggregate exergy efficiency from the energy source to the final service.
A driving factor analysis method considering all stages of the whole energy system is developed to systemically decompose what factors drive aggregate exergy efficiency.
A deep analysis of the “dual structure” problem in China was conducted to provide deep understandings of efficiency improvements in developing countries like China.
The remaining sections of this paper are organized as follows:
Section 2 provides a review of previous studies and identifies gaps in the research.
Section 3 introduces the method and data used in our investigation.
Section 4 presents our results.
Section 5 concludes the paper.
4. Results
4.1. The Aggregate Exergy Efficiency of China from 2005 to 2015
The exergy flow and exergy conversion from the energy source to the final service of China in 2005, 2010, and 2015 are summarized in
Table A1,
Table A2 and
Table A3 and mapped using Sankey diagrams in
Figure 5,
Figure 6 and
Figure 7. As presented in
Figure 5,
Figure 6 and
Figure 7, the primary energy enters the energy system, undergoes different stages and causes losses, and finally outputs useful energy to provide final services, where the arrow represents the direction of exergy flow, the color represents different exergy flows, and the width represents the amount of exergy flow.
According to the diagrams in
Figure 5,
Figure 6 and
Figure 7, the main features of changes of the aggregate exergy efficiency of China’ energy system are identified and discussed:
- (1)
The aggregate exergy efficiency of China from the energy source to final service was just 3.7% in 2005, 4.2% in 2010, and 4.8% in 2015. This shows an increasing trend; however, it is still at a very low level. This means that just less than 5% of exergy input ultimately provided final services, and significant potential for future improvement was identified.
- (2)
Losses mainly occurred in the end-use conversion stage and the power and heat generation sector. The average exergy efficiency was 16% (2005), 19% (2010), and 21% (2015) for the end-use conversion stage and 30% (2005), 34% (2010), and 35% (2015) for the power and heat generation sector. Among these two technical sectors, fuel was upgraded into higher quality energy, such as electricity and mechanical work. Due to the thermodynamic limit, an irreversible loss would inevitably occur, mainly as a result of combustion and heat transfer losses. On the other hand, limited by inappropriate operation and unpredicted conditions in practice, the actual operating efficiency of these conversion devices never reaches the theoretical design value, resulting in more losses. Thankfully, with the continuous promotion of efficiency improvement in these fields in China, the technical design and operation level of conversion devices have constantly been improving to reduce the loss.
- (3)
There is considerable potential for the improvement of passive systems. We found that just 32% (2005), 34% (2010), and 34% (2015) of the exergy input of passive systems were delivered to final services. In contrast to conversion devices, passive systems do not actively convert energy to another form, instead, they hold useful energy in order to provide a level of final service. The efficiency of a conversion device is related to how they convert fuel into useful energy; however, the efficiency of a passive system is based on avoiding unintended losses of useful energy in order to provide final services, e.g., reducing the friction or drag of a car, and or increasing the seal or insulation of a house. For example, in China, over 80% of useful energy of building passive systems were lost without providing needed services. Several factors inhibit the deployment of more efficient technical solutions in buildings: the variety of building designs, the existence of a large number of old buildings with poor seal and insulation, improper setting of cooling or heating temperature, and so on.
4.2. LMDI Decomposition Results of Driving Factors
Relative contributions of efficiency and structure factors on the aggregate exergy efficiency are quantitatively decomposed by the LMDI decomposition method, as illustrated in
Table 2 and
Figure 8. The efficiency improvement of the end-use conversion stage and power and heat generation sector has always been the most important driving factors, and contributions of passive systems were considerable. In this section, we discuss and explain the driving factors of each stage.
4.2.1. Energy Source
The energy source utilization coefficient is defined as the ratio of exergy used by direct fuel use and power and heat generation to the total exergy input, which was 0.98 (2005), 0.93 (2010), and 0.96 (2015), with contributions of −4% (2005–2010) and 3% (2010–2015) to the aggregate exergy efficiency. In short, reducing fuel loss is helpful, such as coal preparation losses, and oil and gas transportation pipeline losses.
As for the energy source structure, there was a negative decrease of −1% (2005–2010) and −4% (2010–2015). Due to China’s continuous efforts of promoting renewable energy and reducing fossil energy in recent years, the share of renewable energy has increased rapidly as the share of coal and oil fell sharply; however, the exergy efficiency of the whole energy chain of fossil energy was higher than renewable energy. That is why the adjustment of energy sources has negative effects on the aggregate exergy efficiency.
4.2.2. Power and Heat Generation Sector
The transformation structure represents how much energy was delivered to the power and heat generation sector, which was 0.41 (2005), 0.45 (2010), and 0.46 (2015), with contributions of −0.1% (2005–2010) and 1% (2010–2015). Since there is one more exergy conversion process in the power and heat generation sector, more energy being delivered to this sector, more losses are caused. However, this negative effect can be diluted by the efficiency improvement of power and heat generation.
The efficiency improvement of the power and heat generation sector has significant contributions of 4% (2005–2010) and 2% (2010–2015). As shown in
Figure 9 (Left), the exergy efficiency of the whole sector increased from 30% to 35% from 2005 to 2015, contributing 5.4%. This is closely related to the recent efforts to improve the efficiency of the power and heat generation sector. For the power and heat generation sub-sectors, the exergy efficiency of all sub-sectors except oil increased year by year; coal-fired power and heat generation has the largest contribution, reaching 4.3% as shown in
Figure 9 (Right). This is because that coal has always been the most important source of power and heat generation in China, accounting for more than 70% of the total power and heat generation. The efficiency improvement of the coal-fired power and heat generation is crucial to aggregate efficiency improvement.
4.2.3. End-Use Conversion Device
The contribution of the end-use conversion device is important to the improvement of aggregate exergy efficiency. Concerning end-use structure, its contribution increased from 0.3% (2005–2010) to 1% (2010–2015). As
Figure 10 (Left) shows, more energy was converted into motion energy in devices (e.g., energy converted by Otto engines, aircraft engines, and electric motors), which increased from 23% (2005) to 26% (2010), and 28% (2015). As these motion devices have a higher efficiency than other devices, this adjustment contributed most to aggregate improvement.
The improvement of end-use conversion efficiency has always been the most important driving factor. Thanks to the continuous attention to the efficiency improvement of end-use conversion devices, its contribution was far more than other driving factors, with 11% (2005–2010) and 13% (2010–2015). As shown in
Figure 10 (Right), the more energy the end-use conversion device consumed, the more significant its contribution to the aggregate improvement was. For example, coal burners always occupied the largest proportion of energy-use and contributed the most, at 7.9%. Diesel and gasoline engines consumed the most fuel oil and contributed 3.6% and 1.8%. In short, improving the efficiency of end-use conversion devices is still the most important task to improve the aggregate efficiency of the whole energy system.
4.2.4. Passive System
The contribution of passive systems is considerable and cannot be ignored moving forward. Regarding the passive system structure, it contributed 0.2% (2005–2010) and –3% (2010–2015). As
Figure 11 (Left) shows, the share of factory passive systems increased first and then fell from 60% to 62% and 57%, respectively; however, the vehicle passive systems increased from 22% to 25%. Since the factory passive system accounts for a bigger share, it has a greater impact on aggregate efficiency improvement.
The contribution of passive efficiency improvement is rising with contributions of 2% (2005–2010) and 3% (2010–2015). As
Figure 11 (Right) and
Table A5 show, small efficiency changes in passive systems can make significant contributions as the passive efficiency was still relatively low; therefore, the efficiency improvements of passive systems cannot be ignored and holds incredible potential for future improvements in aggregate efficiency.
4.2.5. Final Service
The contribution of the final service structure is not clear; this is mainly due to the offsetting among different final services. As
Figure 12 shows, the proportion of structure and freight transport services dropped significantly, while passenger transport, communication, and hygiene grew. Obviously, rapid development in the early stage in China led to significant increases in energy consumption, mainly due to infrastructure construction. Then, as China entered the high-quality development stage, the demand for such final services increased, e.g., passenger transport, communication, and thermal comfort. For example, high-speed railways were rapidly constructed, and car sales began to increase. However, because these energy flows delivering to final services were mostly with relatively low efficiency, effects of these structure adjustment among these final services were offset each other.
4.3. Further Decomposition Results of “Dual Structure” Problem in China
The “Dual structure” problem in China, the co-existence of new and old technologies, is further analyzed using the method in
Section 3.3. The results are listed in
Table 3 and illustrated in
Figure 13 and
Figure 14.
For the industrial coal boiler, the aggregate exergy efficiency increased by 23.6%, and the adjustment of the capacity structure was the main driving factor, contributing 15.8% (2005–2015). Interestingly, from 2005 to 2010, the adjustment of the capacity structure was the main driving factor contributing 10.8%, while the improvement of conversion efficiency contributed only 4.7%; however, from 2010 to 2015, the contribution of efficiency improvement rose to 5.9%, catching up with the capacity structure adjustment of 4.9% to become the main driving factor. It is obvious that the drastic capacity structure adjustment in the early stage played a significant role in the aggregate efficiency improvements; however, with the reduction of the structure adjustment potential, its contributions decreased and fell behind the efficiency improvement in the later stage.
For the coal-fired power and heat generation, the aggregate exergy efficiency increased by 10.5%. The improvement of conversion efficiency has always been the main driving factor, contributing 9.7% (2005–2015). Since coal-fired power and heat generation units are operating at a higher efficiency level in the early stage, the capacity structure adjustment played a role, but its contribution was limited, even less than that of efficiency improvement. Later, contributions of both decreased, and the contribution of capacity structure adjustment was negligible.
In short, for the energy-intensive sectors that have low efficiency, e.g., industrial coal boilers, the adjustment of capacity structure has a significant effect and will continue to contribute for a while. At the same time, there is still much room to improve the conversion efficiency, as most industrial coal-fired boilers are operating at a low level of efficiency. In contrast, the efficiency of coal-fired power units is generally at a relatively high level, and the contribution of internal capacity structure adjustment is limited.
5. Discussion
5.1. International Comparison
The results found in this study can be compared with previous works. In this study, we extended the boundary of the SEA to the final service, as most studies have only concentrated on the energy chain from the energy source to useful energy. In order to make a meaningful comparison, the aggregate exergy efficiency from the energy source to the useful energy is listed separately—see
Table 4; our results are similar to previous studies. The main discrepancy lies in the aggregate exergy efficiency from the energy source to the final service, likely due to the introduction of passive systems where huge energy losses were identified.
Comparing the driving factor analysis with previous studies is not easy—the analysis of driving factors in the SEA is limited, and most do not cover all stages of the whole energy system and instead just the end-use conversion stage. Looking into these limited studies, Brockway et al. [
13] conducted a similar study in China, but they concluded that the structure change was the main contributor to the aggregate improvement. This is because they defined the structural change as a combined effect of the structure of two different stages. If we look at these stages separately, the improvement of end-use efficiency is still the main driving factor, which is in line with results obtained in this study.
5.2. Improvement of Model Resolution
The improvement of model resolution can be helpful to better understand the efficiency improvement potential of energy systems.
In this paper, the analysis boundary of the exergy efficiency model was extended to the final service to trace energy flow and conversion from the energy source to the final service. In contrast to previous studies that mostly focused on the end-use conversion stage, the energy chain of useful energy output passing through passive systems to provide final services was further analyzed. The results show that just less than 5% of exergy input ultimately provided desirable final services. The results also indicate huge improvement potential in passive systems besides end-use conversion devices.
A driving factor analysis method that considers all stages of the whole energy system was developed to understand relative contributions of each stage of an energy system. In previous studies, excessive attention was paid to the end-use conversion stage. The decomposition results in this study indicated that efficiency improvements in the end-use conversion stage and power and heat generation sector were important, but improvements in passive systems were also considerable. The results of the decomposition analysis show that we should pay attention to both how to convert fuel into useful energy more efficiently, and also how to avoid unintended losses of useful energy when providing final services.
Further, a deep analysis of key technical fields may yield different insights, such as a deep analysis of the “Dual Structure” problem in China. If we observe decomposition results from the view of the end-use conversion stage, the efficiency improvement contributed most, and contributions of structure adjustment were limited; however, a deep analysis of the “dual structure” problem of coal-fired power and heat generation sector and industrial coal boilers implied that internal structural adjustments are equally important for aggregate improvements. Especially for energy-intensive devices with low efficiency, like industrial coal-fired boilers, internal structure adjustment using high-efficiency boilers to replace low-efficiency boilers played a greater role than efficiency improvement in general.
5.3. Uncertainty and Limitation
The main uncertainty of this study lies in the data accuracy. Data used in this paper were mainly sourced from Chinese government authorized sources, literature reviews, and expert interviews. However, rigorous data are not always directly available, and the best available data are adopted based on reasonable estimation. Despite this data uncertainty, this study provides a comprehensive framework to observe changes and driving factors of aggregate exergy efficiency to direct priorities now. If in the future, more accurate data sources are available, future studies should take them into account.
The main limitation of this paper is that the final service loss has not been taken into consideration. This loss is not the physical loss but is more related to human behavior, e.g., improper use of space heating and cooling, waste of food, and ineffective of private cars. In the future, the waste of final services should be further explored.
6. Conclusions
In this paper, a high-resolution SEA-LMDI method was developed to systemically and comprehensively analysis changes and driving factors of the aggregate exergy efficiency of energy systems. First, we extended the current boundary of the SEA to include passive systems and final services, and the results are visualized by the Exergy Efficiency Sankey diagram, which details the energy flow from the energy source to the final service. Then, we applied the LMDI decomposition method to quantify the relative contributions of the structure factor and the efficiency factor of each stage of the whole energy system. Moreover, we conducted a deep analysis of key fields, taking the “Dual Structure” problem of coal use in China as an example.
With China as the case study, the results allow several key insights. (1) Only less than 5% of exergy input ultimately provided the final services people need. Although the aggregate exergy efficiency from the energy source to the final service showed an increasing trend, it is still at a low level. (2) Decomposition results reveal that the efficiency improvement of the end-use conversion stage and the power and heat generation stage have significant contributions to the aggregate improvement, but the contribution of the passive system is noteworthy. As just around 30% of useful energy passed through passive systems and finally provided final services, small improvements in passive efficiency can make a considerable contribution to the aggregate efficiency improvement. (3) Deep analysis of the “Dual Structure” problem of coal use in China indicated that, for energy-intensive and low-efficiency devices like industrial coal boilers, the internal structure adjustment, using high-efficiency devices to replace low-efficiency devices, also played an important role in improving aggregate exergy efficiency.
Based on this study, the following implications can be drawn:
The overall energy efficiency performance of China’s energy system is still at a low level. Significant potential for future efficiency improvement exists and deserves to be explored, especially in the context of carbon neutrality and sustainable development.
Energy efficiency improvements in technology devices, including end-use conversion devices and power and heat generation, will continue to make a considerable contribution to the aggregate improvements. Attention should be paid to the improvement of the conversion of fuel into more useful energy, such as optimizing thermodynamic designs, reducing heat transfer and combustion losses, and improving the equipment operation levels.
Sufficient attention should be paid to the role of passive systems. The efficiency of a passive system depends on how well unintended losses of useful energy providing final services can be addressed, such as reducing the friction or drag of a car and promoting the seal and insulation of a house.
For key energy-consuming fields, it is also a good idea to replace low-efficiency equipment directly with high-efficiency equipment.
This study provides a high-resolution view to identify key technological fields for future energy efficiency improvements of energy systems. This can play a positive role in the policymaking of energy-saving and carbon emission reduction. In the next step, work can be performed to estimate the waste of the final service. This loss relates more to human behavior than technical systems, e.g., food wastage. Given the emphasis on reducing unnecessary waste, future work on this front would reveal more avenues moving forward.