Spatial and temporal uncertainty in the technological pathway towards a low-carbon power industry: A case study of China

Journal of Cleaner Production 230 (2019) 720e733

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Spatial and temporal uncertainty in the technological pathway towards a low-carbon power industry: A case study of China Bao-Jun Tang a, b, c, d, e, Ru Li a, b, c, Biying Yu a, b, c, d, *, Yi-Ming Wei a, b, c a

Center for Energy and Environmental Policy Research, Beijing Institute of Technology, Beijing, 100081, China School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China c Beijing Key Lab of Energy Economics and Environmental Management, Beijing, 100081, China d Sustainable Development Research Institute for Economy and Society of Beijing, Beijing, 100081, China e Collaborative Innovation Center of Electric Vehicles in Beijing, Beijing, 100081, China b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 17 November 2018 Received in revised form 30 April 2019 Accepted 14 May 2019 Available online 15 May 2019

The low-carbon transition of power industry plays a vital role in China's energy system revolution. Both policy support and cost reductions have greatly driven the development of renewable energy technologies, especially wind and solar power generation technologies. Considering the cost uncertainty of renewables, we developed a National Energy Technology-Power model to assess the possible low-carbon transition pathways for six regional power industries using four renewable energy cost change scenarios. Resource endowments and technology developments trends were also considered to achieve an effective and coordinated utilization of various resources. The results show that declining renewable energy costs have a great impact on the spatial and temporal development of power generation technologies, and on the interregional clean power transmission. If the investment costs of renewable energy technologies continue to decline at a high speed and the renewables could be dramatically developed, the CO2 emissions of China's power industry is expected to peak at 3.12 GtCO2 in 2026. Accordingly, the capacity share of renewable energy technologies in regional power industries would exceed 50% except in East China, and the total installed coal-fired technology capacity would fall to 760.2 GW in 2050. In addition, to promote the optimal allocation of resources, the total amounts of interregional clean power transmission are suggested to be 416 TWh in 2035 and 587 TWh in 2050, i.e., 4.9% and 5.5% of the total amount of power generation, respectively. 106 TWh of wind power is expected to be exported from Northwest to Center and East regions in 2050; and 112 TWh of solar power is suggested to be exported from North to Center, East and South regions. The Northwest region is the largest exporter of clean power while the East region is the main importer. These conclusions could support the regional plan of power transmission network. © 2019 Elsevier Ltd. All rights reserved.

Keywords: Spatial and temporal uncertainty Cost uncertainty Regional low-carbon transition Technological pathway Power industry National energy technology-power model

1. Introduction Sustainable development is challenged by energy consumption of traditional fossil energy resources (Mundaca et al., 2018); therefore, accelerating the transition to alternative energy sources has become a new trend in several countries (Suzuki et al., 2016). As a fundamental industry in socioeconomic development, the power industry is not only a key industry focused on energy conservation

* Corresponding author. Center for Energy and Environmental Policy Research, Beijing Institute of Technology, 5 South Zhongguancun Street, Haidian District, Beijing, 100081, China. E-mail addresses: [email protected], [email protected] (B. Yu). https://doi.org/10.1016/j.jclepro.2019.05.151 0959-6526/© 2019 Elsevier Ltd. All rights reserved.

and emissions reduction, but also an important carrier of lowcarbon transition for other industries. In 2016, China's total energy consumption was 4.36 billion tons of coal equivalent (tce), of which fossil energy consumption was 3.78 billion tce. About 31.2% of the total fossil energy was used for power generation (SGERI, 2017). Therefore, the low-carbon transition of power industry is conducive to sustainable development, facilitates the diversification of China's energy supply structure, and is significant for adaptions to climate change. An important method for the low-carbon transition of power industry is to accelerate the development and utilization of renewable energy (Khan, 2018; Tu et al., 2018). In 2017, China was the largest consumer of hydro, wind, and solar energy worldwide,

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with installed capacities of 343.6 GW, 163.5 GW and 129.4 GW, respectively (Shu et al., 2018; CEC, 2018). China's complex terrain means that its energy resources are distributed unevenly. For example, Fig. 1 shows the distribution of wind and solar energy resources in China, which have been mostly used for power generation in recent years (CNREC, 2015). The Northwest and North are the regions have the most wind energy resources, followed by the Northeast and South regions. The solar energy resources are mainly concentrated in the Northwest and North regions. This uneven resource distribution means significant differences in power structures among these six regions (Tang et al., 2018); therefore, the low-carbon transition of China's power industry has regional characteristics. Thus, it is of great practical significance to study the low-carbon transition of power industry from a regional perspective. With the development of smart grids in particular, natural resource allocations result in a larger uncertainty for the power industry's technological development. One of the main drivers for developing the renewable energy technology is to reduce its investment costs (NDRC, 2017). Since 2010, reductions in investment costs have driven the fall in the levelized cost of electricity (LCOE) for wind and solar power technologies to varying extents. Reduction in investment costs of wind contributes 34% of the total reduction in the LCOE. The capacity weighted average LCOE of solar decreased 58% between 2010 and 2015. If the costs maintain a steady decrease in the future, renewable energy power generation technologies will be more competitive than traditional coal-fired technologies (IRENA, 2018). Therefore, changes in the investment costs of renewable energy will affect the power industry's investment plans and the layout of national power grids, which also creates uncertainty in the multisource coordinated development of China's power industry. Targeting this potential uncertainty in the low-carbon transition of power industry caused by factors such as resource endowment, resource reallocation, technology efficiency improvement, etc., we establish a National Energy Technology-Power (NET-Power) model to investigate the spatial and temporal technological pathways and assess the corresponding environmental impacts. China was taken as the empirical context and different cost change scenarios were designed to answer the following questions from the regional level: (1) How will renewable energy technologies, such as wind and solar power generation technologies, compete and coordinate with traditional power generation technologies in six regions under the context of different renewable energy costs? (2) How can resource allocation be optimized to achieve resource complementation

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through interregional power transmission? (3) What are the impacts of different pathways on low-carbon development of China's power industry? Section 2 of this paper reviews the research literature for the domestic and international status of low-carbon transition of the power industry. Section 3 introduces the research framework, modeling approach and data we used, and scenarios we designed. The detailed results of low-carbon transition pathways for six regional power industries and their impacts are discussed in Section 4. Finally, Section 5 concludes with policy implications are given.

2. Literature review The low-carbon transition of power industry has been studied widely. Yuan et al. (2012) developed multilevel perspective transitions and proposed some possible transition pathways (e.g., substitution, reconfiguration, transformation) in China's power industry during 2010e2030. Price et al. (2018) analyzed the impacts of energy, land, and water resources on the levelized cost of electricity and then designed a pathway and space distribution of low-carbon power technology with minimum costs for Great Britain. Targeting the minimum cost, Lenzen et al. (2016) simulated the space-time distribution of low-carbon power technologies to meet the electricity demand per hour in Australia, under the situation where renewable energy can reach the maximum potential while coal-fired capacity is limited. In addition, the impact of carbon price fluctuations on power generation with biomass fuel was analyzed. Shiraki et al. (2016) developed a multiregional optimal-generation planning model to estimate siting and scale of power plants under CO2 emissions reduction target. Foxon et al. (2010) outlined three basic pathways of ‘Market Rules’, ‘Central Co-ordination’ and ‘Thousand flowers’ for low-carbon power system in the UK and Barton et al. (2017) studied the impact of those pathways on the carbon emission reduction target. The above literature all explored the low-carbon transition of power industry at the national level; therefore, they did not propose low-carbon transition pathways for regional power industries with regional characteristics. Mileva et al. (2013) and Sanchez et al. (2015) studied the transition of the power system in western North America using the SWITCH model. Mileva et al. (2013) found that the realization of the ‘SunShot’ program would generate solar power to comprise over onethird of the total power in that region; therefore, it could replace the technologies of natural gas, nuclear, and carbon capture and

Fig. 1. The distribution of wind1 and solar energy resources in China.

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storage (CCS) technologies on a large scale. Sanchez et al. (2015) argued that biomass energy and CCS technologies were critical for the transition to a carbon-negative power system in the region. Cheng et al. (2015) and Guo et al. (2017) studied the pathways of power systems with minimum cost in the context of low-carbon development in China. However, their planning results were not the same due to different factors considered (such as regional division criteria, electrical load, power generation technology, CO2 emission restrictions). Hui et al. (2017) thought that both high power generation costs and insufficient power transmission capacity hindered the development of clean energy technology. They suggested that the government should increase subsidies for wind and solar power technologies and increase the capacity of interregional power transmission to peak the CO2 emissions of power industry prior to 2030. However, they ignored the effect of uncertainty in renewable energy costs on the low-carbon transition of regional power industry, although they considered the interregional power transmission and exploring the potential of regional resources. In conclusion, most researchers studied the low-carbon transition of power system at the national level but ignored the interregional power transmission. If the power supply and transmission optimization models are combined, the results will be more in line with the status of the power system. The investment costs, and technical and energy efficiency will change with socioeconomic and technology development; therefore, the ignorance of dynamic changes in key parameters will certainly affect the accuracy of the results. The rapid decline in the investment cost of renewable energy currently greatly affects the power industry's decisionmaking. If these future changes in cost are not considered, renewable energy technologies will be seriously underestimated when substituting for traditional carbon-intensive technologies. In addition, technology improvement, resource complementarity, and substitution will also impact the progress of low-carbon transition of power industry. To solve the above problems, a NET-Power model was established in this study to explore the spatial and temporal impacts of cost uncertainty of renewable energy on the low-carbon transition and propose a pathway for regional power industries with regional characteristics. Thus, this study will help realize China's climate change goals, promote the effective use of different resources for power generation in the medium or long term, and coordinate multisource development between regions. Hence, these results are valuable for theory and practice. 3. Methodology 3.1. Research framework The regions’ resource endowment and technological development were considered in proposing pathways conforming to regional characteristics for regional power industries (see Fig. 2). First, we collected the data on the power demand and potential capacity for renewable energy to ensure that the low-carbon transition of each region could meet the physical capacity and balance the power supply and demand. Due to the differences in power structure, geographical environment, energy resources, and socioeconomic structure in different regions, the key parameters such as energy consumption, investment costs, power transmission costs, and fuel prices differ in the dimensions of region and technology. The above data were summarized and built into a data module. Second, the green and low-carbon transition of energy systems is an inevitable trend worldwide. To ensure that the simulation results met the policy orientation, we identified many green policies, such as upgrading coal-fired technology for energysaving, measures to solve wind and solar power curtailments, and

the promotion of renewable energy. A policy module was established. Technology improvements, competitive procurement, and a large base of experienced developers can then drive a continuous decline in the investment cost of renewable energy. The inclination of power industries to invest in renewables depends on the degree of the cost reduction. Therefore, we established the NET-Power model with the objective of minimizing costs to simulate how the uncertainty of renewable energy costs could impact the lowcarbon transition of regional power industry. Based on the forecasts of renewable energy costs by some major institutions2, four scenarios describing renewable energy cost changes were designed: business as usual (BAU), low-speed decline (LSD), medium-speed decline (MSD) and high-speed decline (HSD). Finally, the possible development paths for different technologies from the dimensions of time, space, and capacity were presented for each region. Furthermore, the optimal scheduling of interregional clean power transmission was analyzed. Based on the result from six regions, the CO2 emissions and their reduction for the national power industry in 2015e2050 were discussed.

3.2. NET-power model We used the NET-Power model (Tang et al., 2018; An et al., 2018; Chen et al., 2018) to study the impact of changing investment costs of renewable energy on the low-carbon transition of six regional power industries. The NET-Power model gives a detailed description of cost change during each process in which various primary energy are processed and converted into electricity and finally transmitted to the end users. Compared with the previous work (Tang et al., 2018), we further enhanced the description of spatial heterogeneity and spatial interaction.

3.2.1. Objective function The objective function of NET-Power model is to minimize the annualized total cost TCt :

Min

TCt ¼

n X

ICi;t;g þ OMi;t;g þ ECi;t;g þ TRCi;t;g;g0

(1)

i¼1

The initial investment costs ICi;t;g , operation and maintenance (O&M) costs OMi;t;g , energy costs ECi;t;g and transmission costs TRCi;t;g;g0 are included in the total costs. The calculation methods for each cost are shown in Eqs (2)e(5).

ICi;t;g ¼

X

i.h h i ð1 þ rÞLeni  1 Xi;t;g  ici;t;g  hi;t  rð1 þ rÞLeni

g

(2) The initial investment cost incurred for building or retrofitting power generation technology i in region g at year t is calculated as the installed (or retrofitted) capacity size Xi;t;g multiplied by the capital cost ici;t;g and the decline rate of capital cost hi;t . In addition, the investment cost is annualized according to the internal rate of return r and life cycle time Leni .

1

Land-based wind resource potential at heights of 70 m. Including the International Energy Agency (IEA), International Renewable Energy Agency (IRENA), Energy Research Institute National Development and Reform Commission (ERI), The United States Department of Energy (USDOE) and European Wind Energy Association (EWEA). 3 The Wind website is available at the following URL: http://www.wind.com.cn/. 4 The Global Economic Database is available at the following URL: https://www. ceicdata.com/zh-hans/products/global-economic-database. 2

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Fig. 2. Research framework.

OMi;t;g ¼

X

li;t  Di;t;g  hi;t;g

(3)

g

The O&M costs are calculated as the operation capacity Di;t;g multiplied by the annual operational hours hi;t;g and the unit O&M cost in RMB/kWh, li;t . The operation hour hi;t;g are diverse in each region.

ECi;t;g ¼

X Di;t;g  hi;t;g  bi;t;g  epi;t;g

(4)

The self-generating electricity plus the net importing electricity should be greater than or equal to the region's power demand edt;g .

Di;t;g  Si;t;g ; Si;t;g ¼ Si;t1;g ð1  1 = Leni Þ þ Xi;t;g  Yi;t;g

(7)

The stock capacity Si;t;g must be greater than or equal to the actual running capacity, and it is calculated as the capacity in the previous year plus newly-built capacity and minus the retired capacity Yi;t;g .

g

The energy costs are calculated as total power generation in kWh, Di;t;g  hi;t;g , multiplied by energy consumption rate bi;t;g and fuel price epi;t;g .

TRCi;t;g;g0 ¼

0 gsg X

g

X tpi;t;g;g0  luct;g;g0

(5)

3.2.2. Constraints The NET-Power model includes five main constraints: ensuring the power demand satisfied, requiring the running capacity maintained, enforcing the policy targets, conforming to environmental capacity, and imposing interregional clean power transmission. The constraints are shown in in Eqs (6)e(10). n X

g0

i¼1

Di;t;g  hi;t;g  tpi;t;g;g0 þ tpi;t;g0 ;g  edt;g

(6)

(8)

Considering the spare capacity and green policies, the capacity of some power generation technologies should not be used outside the lower bounds, SLi;t;g , or upper bounds, SU i;t;g .

,

g0

The transmission costs are calculated as electricity transmitted from region g to region g 0 in kWh, tpi;t;g;g0 , multiplied by the cost of transmission line usage in RMB/kWh, luct;g;g0 .

0 gX sg

SLi;t;g  Si;t;g  SU i;t;g

fmin i;t;g  Di;t;g  hi;t;g

X Di;t;g  hi;t;g  fmax i;t;g

(9)

i

Besides, the share of electricity generated by technology i should max meet the policy targets. The fmin i;t;g and fi;t;g are the minimum and maximum shares. 0 gsg X

g0

X tpi;t;g0 ;g

!, edt;g  jg

(10)

i

With the promotion of smart grids, regional interconnection will increase gradually. Therefore, we assume that the share of electricity imported from other regions will be no less than that in the base year, jg . Each region can transmit only its well-heeled type of electricity to other regions.

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3.3. Data In this study, we take China as the empirical context and apply NET-Power model to explore a cost-minimized technological pathway towards a low-carbon power industry, by including the spatial and temporal uncertainties. The power generation technologies we considered are shown in appendix Table A1. The parameters not mentioned in this section (i.e., regional power demand, lifetime of technologies, the curtailment ratios of wind and solar power, newly-built or closing down capacity) are the same as in Tang et al.‘s (2018) work. 3.3.1. Renewable energy and fuel costs Table .1 shows the investment costs of wind and solar technologies in six regions in 2015. Overall, the investment cost of solar power technology was higher than that of wind power technology. The development of wind power technology in Northwest is more mature than that in other regions. The Northwest region's unique geographical advantage is very suitable for the construction of large-scale wind power stations, which helps to reduce costs with economics of scale. In addition, Northwest has an arid and semiarid climate that is exposed to the sun for long periods with high radiation; therefore, it is also one of the regions most suitable for the construction of solar power stations. However, due to the inconvenient and relatively costly transportation, the investment cost of solar power in Northwest is high. Current power generation in China mainly relies on coal. The coal resources are concentrated in North (e.g., Shanxi, Inner Mongolia) and Northwest (e.g., Shaanxi, Ningxia, Xinjiang). However, coal resources are scarce in the most economically developed region, East, which requires the most energy. Therefore, this uneven distribution of production and consumption of coal resources determines its flow from the West to the East and from the North to the South. Coal prices are greatly affected by their logistics costs, which results in large differences in coal prices between the six regions (Table 2). Natural gas in China is mainly used by residents and industries. The price of natural gas in this paper refers to the price of industrial gas in different regions. 3.3.2. Energy consumption and annual operation hours of technologies The energy consumption of power generation technologies is affected by its own performance, such as the steam temperature, steam pressure, feed-water temperature, exhaust gas temperature, or boiler efficiency. The supercritical (SC) and ultra-supercritical (USC) technologies with high capacity, high parameters, and high efficiency have lower energy consumption and better environmental performance than do the conventional coal-fired power generation technologies. Therefore, the energy consumptions between different power generation technologies are not the same. Both the own use rate of the power industry and ambient temperature affect the energy consumption of technologies (e.g., ambient temperature affects the exhausted gas temperature), even if the same technologies may have different energy consumptions in different locations. Table 3 shows the technical and regional

Table 1 The initial investment costs of wind and solar power technologies in six regions in 2015.

WPa SPb a b

Unit

North

East

Center

South

Northwest

Northeast

RMB/kW

8419 8660

8368 8309

8311 8547

8529 8251

8080 9352

8430 8466

NEA (2016b). CNREC (2015).

dimensions of the energy consumption of different power generation technologies. Different socioeconomic and natural environments, such as the growing rate of economies, electricity demand, growth rate of installed capacities, power grid loads, and resource endowment all objectively affect the annual operation hours in different regions. Therefore, we considered the diversity of operation hours (Table 4). 3.4. Scenario design Renewable energy power generation technologies, especially wind and solar power technologies, currently have no cost advantage over traditional coal-fired technologies. Therefore, it is difficult to promote the development of renewable energy technologies through growing the electricity demand. According to the data from some major institutions in recent years (see Fig. 3), the investment costs of wind and solar power technologies have been reduced significantly and have the potential to continue declining in future (Morthorst and Awerbuch, 2009; Varro et al., 2015; Taylor et al., 2016). Governments in recent years have been concerned with reducing the cost gap between renewable energy and traditional coal-fired technologies to promote the development of renewable energy industry, especially the wind and solar power industries. Significant differences can be observed in the institutions’ assessment of the investment costs of renewable energy technologies because of their differing information or positions. To avoid the limitation caused by a single judgment, this paper combines the information given by different institutions to establish four possible scenarios for the investment costs of renewable energy (mainly wind and solar energy) in the future (see Table 5 for the scenario settings). (1) The BAU scenario. The BAU scenario is the reference for other scenarios. It assumes that policies and technologies will maintain the current changing trend. We assume that technology and energy efficiencies will be improved, and the problem of wind and solar power curtailment will be resolved. The investment cost of each technology will not change under the BAU scenario. (2) The LSD scenario. We assume that investment costs of wind and solar energy based on the BAU scenario fall at the lowest rate predicted by the institutions in the LSD scenario where the investment costs of wind and solar energy in 2030 will fall by 6% and 38%, respectively, and in 2050 by 14% and 67%, respectively, compared with those in 2015. (3) The MSD scenario. The MSD scenario is based on the BAU scenario, with the assumption that the investment costs of wind and solar energy will fall at medium speeds as predicted by the institutions. In the MSD scenario, the investment cost of wind energy will fall by 13% and 28% in 2030 and 2050, respectively, than that in 2015, while the investment cost of solar energy will drop even faster. In 2030 and 2050, the investment costs of solar energy will be only 52% and 22%, respectively, of that in 2015. (4) The HSD scenario. The HSD scenario is based on the BAU scenario, with an assumption that the investment cost of wind and solar energy will fall at the highest rate predicted by the institutions. In the HSD scenario, the investment costs of wind and solar energy in 2050 will be 44% and 83% lower than those in 2015 respectively. It should be noted that the data before 2030 adopts the actual value predicted by the institutions, and the data after that time is from the simulated trend based on the existing data. The data for the MSD scenario is the average value of the LSD and HSD scenarios.

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Table 2 The energy price in six regions in 2015.

Coal Natural gas

Unit

North

East

Center

South

Northwest

Northeast

RMB/tce

395.8 2631.6

456.9 3082.7

744.6 2706.8

439.1 3157.9

395.8 1729.3

585.5 3082.7

Data source: We sorted out the price of coal and natural gas according to WIND3 and CEIC.4

Table 3 Energy consumption ratesa of power generation technologies in six regions in 2015 (Unit: gce/kWh).

IPC300L SUBC300L SUBC300 SUBC300 after retrofitted SUBC600 SUBC600 after retrofitted SC300L SC300 SC300 after retrofitted Newly-built SC300 SC600 SC600 after retrofitted Newly-built SC600 USC300 USC600 USC600 after retrofitted Newly-built USC600 USC1000 USC1000 after retrofitted Newly-built USC1000 CFB IGCC a b c

North

East

Center

South

Northwest

Northeast

328 323 318 309b 309 304b 314 307 302b 299c 295 287b 292c 294 288 280b 285c 280 275b 272c 285 246

326 321 316 307b 307 302b 312 305 300b 297c 293 285b 290c 292 286 278b 283c 278 273b 270c 283 244

344 339 334 324b 324 319b 329 322 317b 314c 310 301b 307c 309 302 294b 299c 294 289b 286c 299 258

345 340 335 325b 325 320b 330 323 318b 315c 311 302b 308c 310 303 295b 300c 295 290b 286c 300 259

358 353 348 337b 337 332b 343 335 330b 327c 323 313b 319c 321 314 306b 311c 306 300b 297c 311 269

358 353 348 337b 337 332b 343 335 330b 327c 323 313b 319c 321 314 306b 311c 306 300b 297c 311 269

CEPYEB (2017) and Tang et al. (2018). The energy consumption rate of the technology after retrofitted. The energy consumption rate of newly-built technology.

Table 4 Annual operation hoursa of power generation technologies in six regions in 2015.

IPC300L SUBC300L SUBC300 SUBC600 SC300L SC300 SC600 USC300 USC600 USC1000 CFB IGCC NP HP WP a

North

East

Center

South

Northwest

Northeast

4228 4228 4399 4682 4228 4399 4682 4399 4682 5192 7199 6927 821 1849

3855 3855 4012 4269 3855 4012 4269 4012 4269 4735 6565 6317 7611 1592 2008

3450 3450 3590 3820 3450 3590 3820 3590 3820 4237 5874 5652 3452 2051

3457 3457 3597 3828 3457 3597 3828 3597 3828 4246 5887 5664 7661 3290 1900

4287 4287 4461 4747 4287 4461 4747 4461 4747 5265 7300 7024 3497 1667

3561 3561 3705 3943 3561 3705 3943 3705 3943 4373 6063 5834 5815 1449 1577

NEA (2016a), CEPYEB (2017), and Tang et al. (2018).

According to the proposed scenarios in this paper, the cost advantage of renewable energy technologies relative to that of the coal-fired technology will gradually become prominent (shown in Fig. 4). The investment cost of coal-fired technology is between 2777 RMB/kW and 7325 RMB/kW. Among the relevant technologies, PC300L technology has the lowest investment cost with 2777 RMB/kW, USC technology has lower average investment cost with 3456 RMB/kW, the second to PC300L technology, and integrated gasification combined cycle (IGCC) technology has the highest investment cost with 7325 RMB/kW. In the LSD scenario, the investment cost of wind energy will be lower than that of IGCC

technology in 2046. If the investment cost of wind energy continues to decline at a high speed, wind power technology will have a cost advantage over the IGCC technology by 2020 and it will be more cost-effective than circulating fluid bed (CFB) technology in 2035. The investment cost of solar energy declines faster than that of wind energy, and it will be lower than that of CFB technology around 2020. If the investment cost of solar energy continues to decline at a high speed, solar technology will be more cost-effective than SC technology in 2024, and the investment cost of solar technology will be about 3393 RMB/kW, i.e., lower than that of USC technology in 2032.

4. Result analysis and discussion The technological pathways to a low-carbon power industry, interregional clean power transmission, CO2 emissions, and CO2 emission reductions are discussed in this section based on the results from the NET-Power model.

4.1. Low-carbon transition of power industry in six regions The replacement of traditional coal-fired technologies by renewable energy technologies in six regions is analyzed (see 4.1.1), followed by an exploration of the synergistic development among renewable energy technologies (see 4.1.2). Finally, the power structure in each region is discussed under different scenarios (see 4.1.3).

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Fig. 3. Changes in investment costs of wind and solar technologies during 2015e2050. Note: The LSD, MSD and HSD scenarios are explained in detail below.

Table 5 Renewable energy investment cost change scenarios. Years

WP

SP

2020 2025 2030 2040 2050 2020 2025 2030 2040 2050

Scenarios LSD

MSD

HSD

2% 4% 6% 10% 14% 29% 34% 38% 55% 67%

7% 11% 13% 21% 28% 31% 45% 48% 66% 78%

13% 20% 22% 34% 44% 34% 57% 57% 72% 83%

Fig. 4. Comparison of investment costs comparison between renewable energy and coal-fired technologies.

4.1.1. The spatial and temporal development of coal-fired technologies Renewable energy power generation technologies in the six regions substitute for traditional coal-fired technologies in different spatial and temporal dimensions. The installed capacities of different types of coal-fired technologies in 2030 and 2050 under the LSD, MSD, and HSD scenarios are shown in Fig. 5. From the perspective of temporal dimension, the faster the cost of renewable energy technology declines, the more coal-fired technologies will be eliminated. In the LSD scenario, the installed capacity of coalfired technology in the whole country will be 870.8 GW in 2050, which accounts for 21.5% of the total installed capacity. When the investment costs of wind and solar energy technologies are reduced by 44% and 83%, respectively, compared with the values in 2015 under the HSD scenario, the installed capacity of coal-fired technologies in 2050 will be 760.2 GW, which is 12.7% less than

that in the LSD scenario. USC1000 and SC600 are the main coalfired technologies used in all regions. The conventional PC300L and SUBC300L technologies with high energy consumption will be phased out. From the perspective of spatial dimension, the USC1000 technology capacity in North and East regions and that for SC600 technology in Center will increase in 2050 compared to those in 2030, but the capacity of all the other technologies will be reduced. The electricity demand of the North and East regions is relatively higher than that of other regions and the installed capacity of coalfired technology is also higher. Compared with the LSD scenario, the capacity of coal-fired technology will be reduced by 23.9 GW in North in 2050 under the HSD scenario. In 2050, the SUBC technology is not used anymore in the South region and only 11.4 GW of USC1000 technology and 0.6 GW of CFB technology existed in the HSD scenario. The renewable energy resources in the Northwest region are the most abundant and the cost decline of renewable energy has a significant effect on the replacement of the coal-fired technology. In 2050, when the investment costs of wind and solar energy technologies are reduced by 44% and 83% respectively compared with the values in 2015(the HSD scenario), there will be only 0.8 GW of coal-fired technology left in Northwest. The development of coal-fired technologies in the Northeast is also sensitive to changes in the cost of renewable energy. In 2050, the capacity of coal-fired technology will be less than 1 GW in Northeast region. 4.1.2. The spatial and temporal development of renewable energy technologies The installed capacities of renewable energy technologies in different regions develop differently (see Fig. 6). Overall, due to the rapid decline of the investment costs, wind and solar energy technologies will grow dramatically around 2030. The more cost reductions of renewable energy, the earlier development of renewable energy technologies will be. With its technological maturity and cost advantages, hydro power technology will also maintain its steady growth. Considering the regions, wind power technology in the North region will grow substantially around 2028. In the LSD and MSD scenarios, it will reach 329.4 GW and 359.9 GW, respectively, in 2050. Solar power technology will develop rapidly after 2035. The wind power technology in the East region will increase significantly around 2040. Due to the lack of wind resources, the total installed capacity of wind power technology is small in the East region. Even if the cost of wind power technology is reduced rapidly, the installed capacity of wind power technology in the East region is only 31.5 GW in 2050. The installed capacity of hydro power technology in the Center and South regions is among the highest because of their geographical advantages. The development of wind and solar power technologies will be the fastest in Northwest.

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Fig. 5. Installed capacity of coal-fired power generation technologies under three scenarios.

If the investment costs of wind and solar power technologies fall by 44% and 83%, respectively, compared to 2015, the installed capacity of wind power technology in the Northwest will reach 251.9 GW in 2050. The rapid decline in cost will simultaneously promote the development of solar power technology, and the installed capacity will be 100 GW more than that in the LSD scenario. Due to less electricity demand, the Northeast has a relatively smaller installed capacity of power generation technology. 4.1.3. Power structure Due to their different resource endowments of renewable and nuclear energy, the six regions show different trends of technological development. The power structures of the six regions under the three scenarios in 2035 and 2050 are shown in Fig. 7. It is obvious that the wind and solar power technologies will develop greatly in the North and Northwest regions while hydro power technology is used mostly in the South and Center regions and nuclear power technology is mainly used in the East, Northeast, and South regions because of the limitation of land resources. We take the HSD scenario as a demonstrative example because it can show the maximum potential and the largest needed effort. To meet the largest demand of electricity in North China, the

installed capacity of power generation technology in that region is significantly more than that in other regions. In the HSD scenario, the installed capacity of wind power technology in North will be 129.2 GW in 2035, and will increase to 393.7 GW in 2050, which is a more than double increase. Nuclear power technology is mostly used in the East region. In the HSD scenario, the installed capacity of nuclear power technology in the East region will grow by a rate of 4.4% annually between 2015 and 2050. Due to the lack of renewable resources in East China, coal-fired technology will continue to grow and dominate its power structure during the planning period. Water resources are abundant in Center. In the HSD scenario, the installed capacity of hydro power technology will maintain a growth rate of 1.1% per year, up to 168.3 GW in 2035, and will continue to grow to 193.8 GW in 2050. The renewable energy technology develops rapidly in the South region. In the HSD scenario, the installed capacity of coal-fired technology will account for 15.5% of the total installed capacity in 2035 and will fall to 1.6% in 2050. By that time, the electricity in South mainly comes from clean energy. In Northwest, a 100% power supply from renewable energy could be achieved by 2050. The installed capacity of wind and solar power technologies in that region accounts for 31.9% and 65.9%, respectively, in the HSD scenario. The Northeast region has

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Fig. 6. Installed capacity of renewable energy power generation technologies under three scenarios.

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Fig. 7. Power structure of six regions under three scenarios in 2035 and 2050. (Unit: GW).

Fig. 8. Interregional power transmission under three scenarios in 2035. Note: The values in parentheses indicate the power transmission in the LSD, MSD, and HSD scenarios, respectively. Unit: TWh.

the least capacity of power generation technology due to its smallest electricity demand among the six regions. In the HSD scenario, all electricity in the region will come from non-fossil energy resources by 2050. The installed capacity of wind, solar, hydro, and nuclear power technologies will account for 35.6%, 57.0%, 3.9%, and 3.5%, respectively. 4.2. Interregional power transmission Interregional power transmission is conducive to the overall

coordination of the power industry's energy resources and green development. When the investment costs of renewable energy technology are maintained at LSD, MSD and HSD, the interregional power transmission for 2035 and 2050 is shown in Fig. 8 and Fig. 9, respectively. The result of interregional power transmission shows that a rapid reduction in the investment cost of renewable energy is conducive to the spatial optimizing allocation of resource. In the LSD, MSD, and HSD scenarios, the total amount of interregional power transmission will be 355 TWh, 380 TWh, and 416 TWh,

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Fig. 9. Interregional power transmission under three scenarios in 2050. Note: The values in parentheses indicate the power transmission in the LSD, MSD, HSD scenarios, respectively. Unit: TWh.

Fig. 10. CO2 emissions of China's power industry under different scenarios.

respectively, accounting for 4.2%, 4.4%, and 4.9% of the total amount of power generation in 2035. The Northwest is the largest exporter of clean power. In the HSD scenario, 162 TWh of renewable electricity will be exported from Northwest in 2035, accounting for 38.9% of the total interregional power transmission in China. East is the main importer of clean power. In 2035, its imported power will be 273 TWh, accounting for 65.8% of the total interregional power transmission, and accounting for 11.9% of electricity consumption in the region. Interregional power transmission will continue to expand as the investment costs of renewable energy continue to decrease and the demand for electricity continues to grow. Compared with the LSD scenario, the expansion of transmission capacity from North to South is needed for solar power transmission in 2050 under MSD and HSD scenarios, which will undertake solar power transmission of 31 TWh and 63 TWh respectively. In the LSD, MSD, and HSD scenarios, the total amount of interregional power transmission in 2050 will comprise 4.2%, 4.8%, and 5.5%, respectively, of the total

power generated. The interregional power transmission in 2050 will be 91 TWh, 129 TWh and 171 TWh more than that in 2035, respectively. The Northwest is the main exporter of wind power. In the HSD scenario, 106 TWh of wind power will be exported from the Northwest in 2050, an increase of 24.7% over that in 2035. North is the largest exporter of solar power. In the HSD scenario, 112 TWh of solar power will be exported from North in 2050, 72 TWh more than that in 2035.

4.3. CO2 emissions The competitive advantage of wind and solar power technologies becomes more obvious with the cost decline. With the investment cost of renewable energy continuing to decline, there are significant temporal differences in CO2 emissions peak under the different scenarios. The faster the investment cost declines, the more significant the effect of CO2 emission reductions will be (see Fig. 10). If the investment cost of wind and solar power keeps MSD

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Fig. 11. Share of installed capacity and interregional power transmission in 2050. Note: From the inner to outer rings are the LSD, MSD and HSD scenarios, respectively. The numbers in doughnuts are percentages (Unit: %). The values in parentheses indicate the proportion of power transmitted in the total generated electricity in the region under the LSD, MSD, and HSD scenarios, respectively.

(the investment costs of wind and solar energy technologies are 28% and 78% lower than those in 2015), compared with that in the BAU scenario, it will bring a CO2 emission reduction for about 10.79 GtCO2, which is about 32.8% of the total CO2 emissions of the power industry in 2015. If the investment costs of wind and solar energy technologies are reduced by 44% and 83% respectively compared with the values in 2015 (the HSD scenario), the cumulative CO2 emissions will be reduced by 4.01 GtCO2, more than that in the MSD scenario. In the HSD scenario, with the promotion of renewable energy technologies, traditional coal-fired technologies will be gradually replaced, and CO2 emissions will drop rapidly after 2026, with a declining rate of 0.8% per year. Reducing the investment cost of renewable energy could lead to a power industry that uses lowcarbon technologies economically. 5. Conclusions and policy implications 5.1. Conclusions Due to diverse resource endowments, the low-carbon transition of regional power industries might show distinctive performances. Taking China as an example, we established a NET-Power model to simulate the optimization of power generation technology selection and transmission considering regional characteristics and interregional power transmission. We analyze the spatial and temporal uncertainties of low-carbon transition in China's power industry under the uncertain cost of renewable energy and propose some possible technological pathways for each regional power industry. The following conclusions are drawn: (1) The faster the cost of renewable energy reduces, the more prominently it replaces traditional coal-fired technology. In regions with relatively abundant renewable energy resources, such as in the Northwest, South, and Northeast regions, when the investment cost of renewable energy drops

at a high speed, its PC300L and SUBC technologies will be greatly replaced by wind and solar power technologies. In 2050, when investment costs of wind and solar power technologies fall by 44% and 83% respectively of those in 2015 under the HSD scenario, the installed capacity of coalfired technologies will be less than 1 GW in Northwest and Northeast and 12.0 GW in South. Coal-fired technology will still dominate in East. (2) The investment cost reduction of renewable energy will enable wind and solar power technologies to be developed quickly starting from around 2030. The faster the cost declines, the earlier the development of wind and solar power technologies in various regions is practiced. The power structure in each region varies greatly in the future. In 2050, the capacity of renewable energy technology in the other regions will exceed 50% (see Fig. 11), except for East. If the investment costs of wind and solar energy technologies are 44% and 83% lower than that of 2015, respectively (the HSD scenario), the share of installed capacity of wind power technology in North, Northwest and Northeast will be 37.0%, 31.9%, and 35.6%, respectively, in 2050. In 2050, the share of installed capacity of solar power technology in North, Northwest, and Northeast regions will be 31.2%, 65.9%, and 57.0%, respectively, under the HSD scenario. In 2050, the installed capacity of nuclear power technology in East will be highest under the HSD scenario, accounting for 69.3% of the total installed capacity of nuclear power technology in China. The installed capacity of hydro power technology in Center is in the largest scale, accounting for 44.5% of the total installed capacity of hydro power technology in China in 2050. (3) The decline in the degree of the investment cost of renewable energy will affect the scale of interregional clean power transmission. The more the cost falls, the greater the scale of interregional power transmission increases. In 2050, in the LSD, MSD, and HSD scenarios, the total amount of

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interregional power transmission will be 446 TWh, 509 TWh, and 587 TWh, respectively. The Northwest is the main exporter of clean power. In the LSD scenario, 162 TWh of power will be exported in 2050, accounting for 13.9% of the power generated in Northwest. Compared with the LSD scenario, an additional 3.1% of the electricity will be exported in the HSD scenario (see Fig. 11). Electricity generated in North is mainly transmitted to the Center and East regions. In the HSD scenario, the electricity exported from North is 92.3% more than that in the LSD scenario and 37.0% more than that in the MSD scenario. The amount of electricity delivered from the Northeast and Center regions will also increase with the decline in renewable energy costs. (4) The decline in investment costs of renewable energy will promote CO2 emission reductions in the power industry. If the investment cost of renewable energy and the existing policy trends remain the same, the CO2 emissions of the power industry will peak by 2040. If the cost of renewable energy drops at a high speed, even if the existing policy trend is maintained and government intervention is not strengthened, the promotion of renewable energy technologies will be expected to peak the CO2 emissions of the power industry at 3.12 GtCO2 in 2026, and then decline at the rate of 0.8% annually.

5.2. Policy implications Based on these results, the changes in the investment cost of renewable energy were shown to have a great impact on the lowcarbon transition of power industry. To promote the coordinated development of coal-fired and renewable energy technologies, and to optimize the allocation of resources between regions, we propose the following suggestions for the low-carbon transition of China's power industry: (1) Reducing the investment cost of renewable energy can increase the competitive advantage of renewable energy through market instruments. Therefore, to reduce the cost of renewable energy, on the one hand, the government could enlarge their research and development investments to improve the technology efficiency; on the other hand, the government could increase its subsidies to the renewable energy industry. To peak the CO2 emissions of China's power industry prior to 2030, the investment cost of wind power technology is suggested to be reduced to 6518 RMB/kW in 2030 and 4679 RMB/kW in 2050, and the investment cost of solar power technology is suggested to be reduced to 3697 RMB/kW in 2030 and 1462 RMB/kW in 2050.

(2) Cost reduction of renewable energy can not only improve the economic benefits of power industries, but also help optimal allocation and complementation of resources. With the cost reduction of renewable energy, electricity exported from the North, Northwest, and Center regions will increase greatly. In 2050, renewable electricity exported from Northwest to Center, South and East regions is suggested to be 205 TWh, 51.7% of which comes from wind power. Solar power transmission line from North to the South could be proposed, via which 63 TWh of solar power could be exported. Considering the regional resource endowment, it is suggested that the main exporter of wind, solar and hydro power are Northwest, North and Center regions respectively. Therefore, transmission capacity needs to be expanded to promote the power industry's optimum distribution of resources and lowcarbon development. (3) To peak the CO2 emissions earlier, the promotion of clean energy in each region is needed. In 2050, the installed capacity of wind power technologies is suggested to be 393.7 GW in North region. The capacity of coal-fired technology needs to be controlled in East region, up to 372.2 GW in 2050. Meanwhile, the installed capacity of nuclear power technology in East region is recommended to maintain a growth rate of 4.4% annually between 2015 and 2050. With the abundant water resource, the total capacity of hydro power technologies in Center and South regions is proposed to be 370.3 GW in 2050. For Northwest region, 100% renewable electricity generated by 789.1 GW of renewable energy technology is expected by 2050. The primary mission in Northeast region is to develop the wind power technologies, followed by the solar power technology.

Acknowledgments The authors acknowledge financial support received through National Key R&D Program of China (2016YFA0602603) and from the National Natural Science Foundation of China (Grant Nos. 71822401, 71573013, 71603020, 71642004), the Beijing Natural Science Foundation of China (Grant No. 9152014), Special Items Fund for Cultivation and Development of Beijing Creative Base (Grant No. Z171100002217023), Key Project of Beijing Social Science Foundation Research Base (Grant Nos.15DJA084 and 18JDGLB039), and Special Items Fund of Beijing Municipal Commission of Education.

Appendix

Table A.1 Acronyms of power generation technologies in this paper (Tang et al., 2018). Acronyms

Technologies

Acronyms

Technologies

PC300L SUBC300L SUBC300 SUBC600 SC300L SC300 SC600 USC300 USC600

Conventional pulverized coal technology less than 300 MW Subcritical coal technology less than 300 MW Subcritical coal technology of 300 MW Subcritical coal technology of 600 MW Supercritical coal technology less than 300 MW Supercritical coal technology of 300 MW Supercritical coal technology of 600 MW Ultra-supercritical coal technology of 300 MW Ultra-supercritical coal technology of 600 MW

USC1000 CFB IGCC NGCC NP HP BP WP SP

Ultra-supercritical coal technology of 1000 MW Circulating fluid bed technology Integrated gasification combined cycle technology Natural gas combined cycle Nuclear power technology Hydro power technology Biomass power technology Wind power technology Solar power technology

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