Carbon emission scenarios of China’s power sector Impact of controlling measures and carbon pricing mechanism LIU Qiang 11 *, ZHENG Xiao-Qi 1,2 , ZHAO Xu-Chen 1 , CHEN Yi 1 , Oleg LUGOVOY 3 1. National Center for Climate Change Strategy and International Cooperation, Beijing 100038, China; 2. School of Environment 3. Environmental Defense Fund China Program, Beijing 100007, China Abstract The study constructs a low-carbon path analysis model of Chinas power sector based on TIMES model and presents a comparative analysis of carbon emissions under Reference, Low-Carbon and Enhanced Low-Carbon scenarios ， and the main difference of the three scenarios is manifested by policy selection and policy strength. The conclusions are drawn as follows 1 The peak of carbon emission in China’s power sector will range from 4.0 GtCO 2to 4.8 GtCO 2 , which implies an increment of 0.5‒1.3 billion or 14‒35 from the 2015 levels; 2 Introducing carbon price is an effective way to inhibit coal power and promote non-fossil fuels and Carbon Capture, Utilization and Storage applications CCUS. The carbon emission reduction effects will gradually increase with carbon price. When the carbon price attains to CN 150 t －1 CO 2 , the CO 2emission can decrease by 36 than that without carbon price. 3 CCUS is one of important contributing factor to reduce CO 2emission in power sector. Generally speaking, the development of non-fossil fuels and energy efficiency improvement are two main drivers for carbon mitigation, but once the carbon price reaches up to CN 106 t －1 CO 2 , the CCUS will be required to equip with thermal power units and its contribution on carbon emission reduction will remarkably increase. When carbon price increases to CN 150 t －1 CO 2in 2050, the application of CCUS will account for 44 of total emission reduction. 4 In the scenario with carbon price of CN 150 t －1 CO 2 , power sector would be decarbonized significantly, and the CO 2intensity will be 0.22 kgCO 2 kW h －1 , but power sector is far from the goal that achieving net zero emission. In order to realize the long-term low greenhouse emission development goal that proposed by the Paris Agreement, more efforts are needed to be put to further reduce the carbon emission reduction of power sector. Based on the above scenario analysis, the study proposes four recommendations on the low-carbon development of Chinas power sector 1 improve the energy efficiency proactively and optimize the energy structure of power sector gradually; 2 promote the low-carbon transition of power sector by using market-based mechanism like carbon emission trading scheme to internalize the external cost of carbon emission; 3 give more emphasis on and support to the CCUS application in power sector. Corresponding author Liu Q., Keywords Power sector; TIMES model; Scenario analysis; Carbon peak; Carbon pricing; Policy recommendations 1 Introduction As the Paris Agreement has been reached, countries around the world are moving towards a low-emission and climate-resilient world and the majority prefer to the low-carbon path for development IPCC, 2014; Du, 2014; Li, 2015. In 2015, the Chinese government announced the Enhanced Actions on Climate Change – Chinas Intended Nationally Determined Contributions and pledged to peak CO 2emissions around 2030 and strive to peak early NDRC, 2015. To achieve these targets, we must vigorously press ahead with the low-carbon transation of economy and society, especially the energy sector. The power sector is the largest carbon emitter and non-fossil energy user among Chinese economic sectors. According to preliminary estimates, the power sector produced about 3.55 GtCO 2in 2015 ,accounting for 38 of the countrys carbon emissions from energy consumption. In view of more stringent binding targets for carbon emissions, the Chinese government has adopted a number of policies and measures that remarkably improve the energy structure and energy efficiency in the power sector. The share of renewable generation in total generation increased from 16.1 in 2005 to 22.4 in 2015, while the fuel use per power generation in coal-fired plants fell by 14.9 to 315 gce kW h －1CEC, 2017; NBSC, 2016a. However, it should not be overlooked that carbon emissions are still taking an upward trend in the power sector. More specifically, the carbon emissions increased by 69 from 2.1 GtCO 2 to 3.55 GtCO 2over the ten years NBSC, 2016b. Given this, only through low-carbon transation of the power sector can we radically change the high-carbon energy system and achieve low carbon in end users in China. There have been many studies on the low-carbon transition of power sector with the utilization of various models and scenarios, and these studies provided valuable insights into hot topics, such as carbon emission peak, carbon tax, carbon price, influence factors of carbon emission and emission abatement potential Cheng and Xing, 2016; Wang and Wang, 2016; Liu et al. 2014; Song et al. 2013; Zhang, 2011; Peng and Wang, 2016; Zhu, 2011. The ologies and conclusions of these studies are instructive for our analysis. Our study constructs a low-carbon path analysis model of Chinas power sector based on The Integrated MARKAL-EFOM System TIMES model, conducts a comparative analysis of carbon emissions scenarios and further, probes into the targets, paths, policies and their effects regarding the control of carbon emissions in the power sector. 2 Model and ology The TIMES model is an energy system model that can provide detailed technical analysis for long-term, multi-period, and dynamic energy development in a country or region Loulou et al., 2005a. It is generally used for the study of the entire energy system and also individual-specific sectors such as the power sector. Based on the TIMES model, this study builds the Low-Carbon Path Analysis Model for Chinas Power Sector which is a refined dynamic linear programming model for power system Fig. 1. Driven by future power demand, the proposed model objectively describes all aspects of the real energy system, such as primary energy supply, power generation facility operation, power demand, and offers detailed characterization of current or future applicable technologies to a complete reference energy system RES Loulou et al., 2005b. The Low-Carbon Path Analysis Model for Chinas Power Sector simulates future development trends of the power sector on the RES. Under the constraints of energy supply, process capacity, production operation and pollutant emissions, as well as user-defined constraints, the model applies the linear programming to produce minimum-cost technological combinations and calculates energy consumption and carbon emissions of power system under different scenarios Liu et al., 2011; Wang et al. 2010. The analysis sets 2050 as target year with a one-year time interval, and uses China’s national historical statistic data from 2007 to 2012 to calibrate the data in the model. In order to clearly present and compare the result for each 5 years, the analysis use year 2010 as the beginning year. The model examines nine energy carriers, namely coal, oil, natural gas, nuclear energy, hydro energy, wind energy, solar energy, biomass energy, and geothermal energy. It depicts a total of 201 existing and prospective technologies in different links of the national power generation system. The model data is divided into five types, including natural sources data, technologies data, emission factor data, system setting parameters and demand data. The first three types of data mainly come from China Statistical Yearbooks NBSC, 2016a, China Energy Statistical Yearbooks NBSC, 2016b and other publicly accessible data; system setting parameters usually are set by default or by users; and demand data is cited from Liu et al. 2017, 2016. Fig. 1. Diagram of the Low-Carbon Path Analysis Model for Chinas Power Sector 3 Scenario design 3.1 Scenarios with different controlling measures This study sets three scenarios, i.e. reference REF scenario, low-carbon LC scenario and Coal, Oil, Natural gas, Nuclear, Hydropower, Wind power, Solar energy, Biomass Primary energy supply Power generation Power demand External research Energy system cost Optimal technical option enhanced low-carbon ELC scenario, and by comparing carbon emissions in these scenarios, identifies different paths to carbon emission peak in the power sector and policy implications. In the REF scenario, the power sector is free from additional abatement targets and maintains energy conservation and non-fossil energy development as during the 11th and 12th Five-Year Plan FYP periods. The LC scenario strengthens the measures for energy conservation and emissions reduction, and promotes power generation from non-fossil energy sources while intensifying the elimination and replacement of backward coal-fired generators. In the ELC scenario, the power sector is subject to more stringent constraints of carbon emissions, and steps up the control of total installed capacity from coal-fired generators and the large-scale development of renewable energy generators. The demand for electricity will grow, but at different rates in the three scenarios, which reflects the increased efforts of energy demand-side management. To 2050, the per capita power consumption will reach 8500, 7500 and 7000 kW h in the REF, LC and ELC scenarios respectively Fig. 2 Liu et al. 2017; Liu et al., 2016; Zhou et al., 2011; IEA, 2014; Wang and Watson, 2010; Zhang and Cheng, 2015; Jiang, 2011. The three scenarios are set and compared, as shown in Table 1. Fig. 2. Power demand trends from 2010 to 2050 in China Table 1. Scenarios with different controlling measures Measure REF LC ELC Emissions control targets Governmental-set targets for carbon emission controlling by 2020; no additional emission Governmental-set targets for carbon emission controlling by 2020 and 2030; gradually control Enhanced control of carbon emissions beyond governmental-set constraints beyond 2020 of total carbon emissions targets by 2020 and 2030; strengthen control of total carbon emissions; early peak of carbon emissions Demand-side management Moderate demand-side m anagement; power demand up to 7.0, 9.0 and 11.5 trillion kW h and per capita power consumption up to 5000, 6300 and 8500 kW h by 2020, 2030 and 2050 respectively Proactive demand-side managemen t; power demand down to 6.8, 8.3 and 10.2 trillion kW h and per capita power consumption down to 4800, 5800 and 7500 kW h by 2020, 2030 and 2050 respectively Efficient demand-side managem ent; power demand down to 6.5, 7.7 and 9.5 trillion kW h and per capita power consumption down to 4600, 5400 and 7000 kW h by 2020, 2030 and 2050 respectively Production-s ide management Government-set targets for non-fossil energy by 2020; relatively loose constraints on installed capacity from coal-fired plants; modest targets for installed capacity from renewable energya Government-set targets for non-fossil energy by 2020 and 2030; moderately stringent constraints on installed capacity from coal-fired plants; proactive targets for installed capacity from renewable energya Stringent control of non-fossil energy beyond government-set targets by 2020 and 2030; extremely stringent constraints on installed capacity from coal-fired plants; ambitious targets for installed capacity from renewable energya Note aIn order to limit the excessively development of coal-fired power capacity, leaving enough space for the development of non-fossil fuels, the analysis set several constraints in the model to represent the controlling force for coal-power units and promoting force for renewable energy and use the descriptive words modest, proactive, and ambitious to represent the policy strength of constraints. For example, modest, proactive and ambitious constraints on coal-fired capacity respectively represent the controlling of coal-fired capacity under 1200, 600 and 550 GW in 2050. 3.2 Scenarios with different carbon pricing The carbon price scenarios are set by introducing carbon pricing to the above-mentioned scenario, in order to uate the effects of carbon price on carbon emissions of the power sector. Comparatively speaking, LC scenario is a moderate scenario that covers all of controlling measures set by Chinese government but exclude the further stringent measures to be adopted. It is therefore most possible scenario under current policies on carbon emission controlling, and selected to be a benchmark to assess the effect of carbon price. A series of incremental carbon prices are set in this study with reference to carbon price levels in the seven pilot carbon markets in ChinaZheng and Sun, 2017. It is initially set to CN 30 t －1CO 2 -eq in 2017, and then increases linearly year by year, up to CN 50, 100 and 150 t － 1 CO 2 -eq respectively in 2050, which correspond to LC-IL50 1 , LC-IL100 and LC-IL150 scenarios, as shown in Table 2. Table 2. Scenarios with different carbon pricing Scenario Carbon price CN t －1 CO 2 2017 2020 2030 2040 2050 LC-IL50 30 32 38 44 50 LC-IL100 30 36 58 79 100 LC-IL150 30 41 77 113 150 4. Analysis results of scenarios with different controlling measures 4.1 CO 2emissions In the REF scenario, the carbon emissions of the power sector tend to increase rapidly before 2030 and slowly after to the peak of about 4.86 GtCO 2in 2040, and then fall to 4.80 GtCO 2in 2050 Fig. 3. In the LC scenario, the carbon emissions will grow slowly before peaking at 4.09 GtCO 2in 2027, and then reduce quickly to 3.76 GtCO 2in 2050. In the ELC scenario, the carbon emissions will reach the peak of about 3.92 GtCO 2in 2024, followed by a rapid decline, down to 3.50 GtCO 2in 2050. In general, the peaking of carbon emissions in the power sector requires a large time span, depending on major measures that cover demand-side management, coal consumption restriction, and renewable energy development. If the measures are appropriate, the peak will arrive before 2025 under an economically effective condition. Many research institutions at home and abroad forecast that Chinas power sector will reach peak emissions at 4.0‒5.0 GtCO 2Yin and Chen, 2013; Liu, 2011; Zhu et al., 2015 before 2030. This study shows the peak varies with the year of arrival or more specifically, the earlier arrival, the lower peak. The peak will range from 4 GtCO 2 to 4.8 GtCO 2 , which means an increment of only 0.5‒1.3 GtCO 2or 14‒35 compared to 2015 about 3.55 GtCO 2 . Fig. 3. Carbon emissions of the power sector in different scenarios 4.2 Power generation and installed capacity The power generation structure is very different in the REF, LC and ELC scenarios Fig. 4. Non-fossil fuels accounted for 20.6 of the power generation in 2010, and then the proportion will rise gradually at different speed. In 2020, the propo