Scenario analysis of energy system transition - A case study of two coastal metropolitan regions, eastern China

Energy Strategy Reviews 26 (2019) 100423

Contents lists available at ScienceDirect

Energy Strategy Reviews journal homepage: http://www.elsevier.com/locate/esr

Scenario analysis of energy system transition - A case study of two coastal metropolitan regions, eastern China Mengzhu Xiao *, Sonja Simon, Thomas Pregger German Aerospace Center (DLR), Institute of Engineering Thermodynamics, Department of Energy Systems Analysis, Germany

A R T I C L E I N F O

A B S T R A C T

Keywords: Energy system transition Renewable energy Eastern China Scenario analysis CO2 targets Regional integration

The scenario analysis focuses on two metropolitan regions of eastern China which are characterized by high energy consumption and related CO2 emissions. Current policies are rather short-term driven and weak regarding sectoral coupling and regional integration. As in China economic activities and population on the one hand and renewable energy resources on the other have a very imbalanced distribution, long-term integrated energy system modelling needs to consider specific regional challenges of efficiency improvement, coal reduction, transport decarbonization and multi-sector electrification. Three scenarios are constructed, namely a Current Policy Scenario (CPS), Natural Gas & Nuclear Scenario (NGNS) and Renewable & Import Scenario (RIS) based on a normative storyline-and-modelling approach. The simulation results show that regional CO2 emissions could be significantly reduced in all sectors with the adjustment of economic structure, adopted efficiency measures, fuels to replace coal and oil products and multi-sector electrification supported by enhanced power import capacity. The scenario analysis provides insights for a strategic implementation of long-term integrated energy transition options towards decarbonization for metropolitan regions both from supply and demand sides.

1. Introduction The Paris agreement aims to restrict global temperature rise to well below 2 � C during this century. The energy sector, with contributing almost 80% of all CO2 emissions, is a primary focus for strategies to tackle global climate change challenges [1]. Under the Paris agreement, in 2015 China’s first “Nationally Determined Contributions” (NDCs) policy set targets to achieve peak CO2 emissions at around 2030, lower carbon intensity per GDP, and increase the share of energy from non-fossil fuel sources by 2030 [2]. With the acceleration of urbaniza­ tion and industrialization expected to continue until 2050, China is facing the challenge of simultaneously mitigating CO2 emissions while supplying a continuously increasing energy demand. This is especially true for the eastern coastal metropolitan regions with dense populations and where economic activities are concentrated. Studies providing en­ ergy scenarios for China are predominantly focused at a national level and lack a perspective on specific regions with urban agglomerations, which have distinct energy challenges [3,4]. Two regions with such energy challenges are the metropolitan region of Beijing-Tianjin-Hebei (BTH) in the north and Yangtze River Delta (YRD) in the south, which together, accounted for 20% of national population, 30% of Gross

Domestic Product (GDP), and 24% of energy consumption in 2015 [5]. These regions suffer from severe air pollution and energy shortages [6]. However, their current energy systems policies are rather short-term, with 5-year planning horizons, and lack sectoral or regional integration, which is necessary to address these energy challenges [7]. This case study is, therefore, intended to fill this gap, adding a long-term and cross-sectoral perspective to the overall picture of energy systems development for the BTH and YRD regions in China, where the chal­ lenges are becoming most acute. We provide long-term energy system scenarios to aid in the development of integrated energy system tran­ sition policies, which will support the decarbonization of the energy sector. To account for the imbalanced distribution of economic growth, urbanization, and available renewable resources in China, we provide a region-based long-term integrated energy system model with sector coupling of power, heat, transport, and fuels. With this model, we explore different energy transition pathways for the BTH and YRD re­ gions up to 2050. The scenario analysis is aimed to deal with regionspecific challenges of efficiency improvement, coal reduction [8], transport decarbonization, and multi-sector electrification. The main research questions are: How would a low-carbon energy supply system

* Corresponding author. E-mail addresses: [email protected] (M. Xiao), [email protected] (S. Simon), [email protected] (T. Pregger). https://doi.org/10.1016/j.esr.2019.100423 Received 21 December 2018; Received in revised form 5 September 2019; Accepted 17 October 2019 Available online 12 November 2019 2211-467X/© 2019 The Authors. Published by Elsevier Ltd. This is an open (http://creativecommons.org/licenses/by-nc-nd/4.0/).

access

article

under

the

CC

BY-NC-ND

license

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

look in each region? How much of the locally available renewable re­ sources can be integrated into the energy system? We also determine the amount of renewable energy, mainly in form of electricity that must be imported from western or surrounding renewable energy abundant re­ gions to guarantee a resilient energy supply and contribute to CO2 emissions reduction in eastern China. We apply a normative scenario approach, backcasting from the target year of 2050. This long-term perspective could help policymakers to compare different options in terms of total system costs and environmental benefits to avoid ‘lock-in effects’, especially in energy-related infrastructure investments, which typically have a long pay back times.

consumption are taken from the high intervention scenario in 2050 in the Shanghai Low Carbon Development Roadmap Report [14]. The provided conversion factors from the China Energy Statistical Yearbook were used for the calculation of universal energy units (PJ) from original individual physical quantities [15]. Regional Gross Domestic Product (GDP) and population are two main drivers for energy demand in end-use sectors. Therefore, energy intensities by GDP or population were used to calculate the final energy demand for power, heat and fuels by sectors. We used population and GDP in terms of Purchasing Power Parity (PPP) from national forecasts [16,17] for the projection of regional development, maintaining the same national shares as in 2015 (Table 1).

2. Methods and scenarios

2.2. Current situation and policies in the study regions

2.1. Energy systems simulation model

Each of the BTH and YRD regions consists of three provinces or municipalities. Fig. 2 shows an overview of geographical and adminis­ trative information of both study regions. The population densities are much higher than the national average and these regions together ac­ count for 27% of the national energy demand in 2015. Since the regions are located in different temperature zones, the YRD region has a much higher electricity demand for cooling, while the BTH region has much higher heat demand for the building sector, especially during winter. For our long term scenarios, we first analysed the current status of the regional energy system, as well as the current or newly implemented policies that influence the short-term development of the energy system. In the BTH and YDR regions, the current energy systems are still largely coal and oil-based (especially the transport sector). Since 1993, China has been a net importer of crude oil and is increasingly dependent on imports. The share of imported crude oil has increased from 53% of total consumption in 2009 to 68% in 2017, turning China into the largest crude oil importer in the world [18,19]. In 2015, most of the munici­ palities in the study regions still have a coal dominated heat and power supply system, with less than 12% of heat and power obtained from natural gas. Beijing is an exception, with 82% and 54% of power and heat supplied by natural gas, respectively. In three provinces (Hebei, Jiangsu, and Zhejiang) coal supply over 97% of the heat demand. In the Hebei, Jiangsu and Zhejiang Provinces coal provides 97%, 91% (6% for natural gas), and 89% (6% for natural gas) of the power demand, respectively. Since 2016, natural gas has been promoted as a “clean fuel” and a more flexible option for power and heat supply, which can reduce air pollution from industry and buildings especially in northern China where district heating systems and coal boilers are widely used in the winter [20]. During the 13th Five-year period (2016–2020), China plans to expand its natural gas and Liquefied Natural Gas (LNG) import infra­ structure to replace coal [21]. The “Coal to Gas” program promoted in northern China covers almost 15 provinces as a pollution reduction corridor to the Beijing-Tianjin-Hebei region with “2 þ 26” key cities

We developed normative scenarios targeting a sustainable energy supply and reduced CO2 emissions within an energy system modelling framework. The energy system models were implemented in the Mesap/ PlaNet platform [9,10]. The model represents a time frame until 2050, divided into five-year intervals (Fig. 1). It starts with energy demand development, driven by GDP and the population. With a broad repre­ sentation of different technologies in the industry, residential, transport, services, and other sectors, the model assesses the required energy supply, as well as capacities for electricity and heat supply, CO2 emis­ sions, and costs of heat and power production. A detailed description of the basic layout of the model can be found in Ref. [11]. We have adapted the original model structure by separating the residential and service sectors, to better capture the effects of urbanization. The technologies for the supply of power, heat, and fuels are repre­ sented by efficiency ratios between flows (e.g. defined for combined heat and power (CHP) plants, transport modes, hybrid vehicles both for passenger & light-duty vehicles (LDV) and heavy-duty vehicles (HDV)), costs, and emission factors. The basic input data for the modelling was obtained through a comprehensive assessment of regional energy statistics. The energy balance tables for each province or respective municipality from the China Energy Statistical Yearbook 2016 were used for the construction of energy systems up to the base year (2015). Additionally, since renewable energies for heat, power, and transport are not included or specified by source in the regional energy balance table, the China Renewable Energy Data Booklet [12] was used for additional informa­ tion regarding the utilization of renewable energies resources for power and heat supply. For the transport sector, the regional energy balance table does not specify energy consumption by mode of transport. Therefore, the traffic volume both for passengers and goods from China Transportation Yearbook [13] was used for energy consumption calcu­ lations for each mode of transport: aviation, rail, road, and pipelines. The adopted parameters for the conversion of traffic volume to energy

Fig. 1. Applied regional energy system simulation model based on Mesap/PlaNet. 2

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

Table 1 Assumption of population and economic growth in the two study regions. Population (Millions) BTH YRD

GDP per capita ($2015PPP/capita)

2015

2020

2030

2040

2050

2015

2020

2030

2040

2050

111 159

112 168

120 176

126 182

133 189

18,109 25,334

25,560 34,080

39,535 53,768

51,650 71,516

65,124 91,657

Fig. 2. Geographical and administrative information of the two study regions (statistical data of 2015 [28]).

aiming to erase small coal-fired boilers [20,22]. Under the Coal to Gas program, the share of natural gas is predicted to increase from 6% in 2015 to 10%, and 15% of national primary energy by 2020 and 2030, respectively. However, this strategy faces challenges at peak demand. In 2017, China’s underground natural gas storage capacity could only cover 5% of its consumption compared with a coverage ratio of 17% in the United States and 27% in Europe [23]. Additionally, bottlenecks from transmission infrastructure lead to higher curtailment ratios especially along the eastern coastal region [23]. This is especially challenging for small cities and towns, where higher prices occur during the process of gradual price liberalization of natural gas (implemented for non-residential customers since 2015 but still remains semi-regulated [20,23]). Furthermore, it is not clear if a long-term transition to natural gas is economically feasible, nor sufficient to guarantee a decarbonized and secure energy supply system. The BTH region relies heavily on pipeline gas from Central Asia [23]; with limited conventional natural gas resources, domestic production is challenging and requires exploitation and utilization of unconventional shale gas. Demand in the BTH region, therefore, still far outpaces domestic supply in any plausible scenario [23]. Therefore, as pointed in 13th Five-year Plans for Power Development and regional specific power develop­ ment plans, nuclear energy is also considered as a key option to reduce coal consumption [24,25]. A renewable energy dominated system is a widely discussed strategy both worldwide and specifically for China [26–28]. However, the

renewable energy resources in eastern coastal China are limited, since much of the recently installed renewable energy capacities are located in western and northern China with relatively abundant wind and solar resources (see Section 2.4.2). Therefore the share of imported electricity (ideally also from renewable energies to be in line with national decarbonization targets) needs to increase, as suggested in the 13th Five-year Plans for Renewable Energy Development towards 2020 [29]. In 2016, non-hydro renewable resources accounted for less than 2% of electricity generation in the two study regions (with the exception of the Hebei Province) with targets set to increase the share to 5% in Shanghai, 7% for the provinces of Zhejiang and Jiangsu, and 10% for BTH region by 2020 (according to Renewable Portfolio Standard Policy released on 29.02.2016 by National Energy Administration) [30]. However, these short-term targets are still too low to meet long-term regional climate targets. The decarbonization of the heat and transport sectors is also heavily reliant on electrification based on renewable energies. Twelve new transmission lines were completed by the end of 2017, under the 2013 Action Plan on Prevention and Control of Air Pollution and the “Elec­ tricity from West and North to East” program, to support the coal reduction plan in eastern coastal China. By 2020, the electricity trans­ mission capacity across provinces and regions will reach 270 GW, of which the development of 130 GW is planned between 2016 and 2020 [24]. With the penetration of variable renewable energy (VRE) into regional power systems, balancing supply and demand is crucial to the 3

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

security of the supply of electricity to metropolitan regions. For the 13th Five-year period, demonstration projects started to balance the fluctu­ ating power generation from hydropower, wind and PV in and around regions. In addition, distributed energy systems with PV and wind, and storage such as batteries, electric vehicles, power to heat, and power to fuel will also promote the penetration of VRE into energy supply systems both in urban and rural areas. After the rapid growth of large-scale onshore wind and PV capacities in northern and western China during the 13th Five-year period, eastern China has also set targets for the installation of distributed onshore wind and PV power plants [31]: The Hebei Province set a target for an increase in on-grid distributed onshore wind capacity of 4.3 GW from 2018 to 2020 [32]; high load centres like Shanghai are to develop smart grids to integrate wind, PV, and storage systems on a distributional scale [33]; the Jiangsu Province is to pro­ mote distributed onshore wind in low wind speed areas [34]; and the Beijing area is to accelerate the installation of onshore wind with sys­ tematic balancing of PV [35]. The fast development of distributed PV began in 2014. For the 13th Five-year period, the 110 GW target for solar power plants by 2020 was achieved, which includes 60 GW of distributed PV [31]. In the 13th Five-year Plan for Renewable Energy Development in the BTH region [25], the Hebei Province plans to improve its ability to control and export its electricity surplus from wind and PV power plants to around 10% of its total power supply; both Tianjin and Beijing have a target to enhance import capacity from the surrounding renewable energy abundant provinces by 6 TWh and 10 TWh, respectively. For the 13th Five-year period, Jiangsu Province has set a priority to develop 10 GW of on-grid offshore wind develop­ ment by 2020 [34] to access these abundant resources (details on the resource assessment in Section 2.4.2). Restructuring the industry sector in eastern China from a heavy in­ dustry based economy towards a service and innovation based economy is seen as another option to limit energy demand. Hebei Province is the largest steel production base in China [36] and in the Jiangsu Province industry accounts for 80% of the energy demand, which is higher than the national average of 66% [15]. Energy demand is also expected to increase with continued urbanization in the region. At the same time, a scenario study suggests that residential and commercial buildings have the potential to reduce their energy demand by up to 74% by 2050 [37]. For example, energy efficiency of heating supply systems could be improved through the use of green building labelling standards for new residential and commercial buildings, or a retrofitting program with smart metering and thermal insulation materials could be applied to existing buildings [38]. In 2015, passenger cars and Light Duty Vehicles (LDV) accounted for 66% and 58% of energy consumption in the transport sector in the BTH and YRD regions and accounted for 67% and 58% of total CO2 emissions in the transport sector, respectively [13,15]. According to the 13th Five-year Plan for Modern Integrated Transport Systems Development (2016–2020) [39], by 2020, high-speed railway services will cover 113 big cities (including megacities), civil aviation will cover 260 cities and another 36 highways will be completed. The electrification rate of the railway is expected to increase from 61% in 2015 to 70% by 2020, doubling the transport service over this time. The metropolitan regions, especially, strive to limit commuting time under 2 h. By June 2018, 27 provinces and municipalities in China had targets for electric vehicles used in private and public transport, supporting the expansion of charging infrastructures highlighted in the 13th Five-year period [40]. By 2020, built charging infrastructures need to support 5 million electric vehicles a. However, future uncertainties exist in terms of the compe­ tition among different modes of transport which may affect the distri­ bution of energy consumption. The future low-carbon fuel supply could involve the successful deployment of Compressed Natural Gas and bio­ fuels; advanced vehicle concepts in the LDV market include battery electric, plug-in hybrid, and fuel cell vehicles [41] supported by fast charging or battery-exchange infrastructures and refuelling stations.

However, a regional plan with multiple provinces and core cities, such as metropolitan regions, with sectoral coupling of the power, heat, fuels, and transport sectors is not yet available. 2.3. Normative scenario approach To conduct the normative scenario approach, we set the desired future target for 2050, namely the transformation of regional energy systems towards lower CO2 emissions. From this starting point, we applied a backcasting process to explore the transition pathways using different decarbonizing strategies and efficiency potentials. Various studies have used this approach to incorporate structural changes beyond current trends and assess the decarbonization of the energy sector [42,43]. Here, the CO2 emissions reduction targets could be achieved through efficiency improvement, implementation of low car­ bon technologies, expansion of the import capacity, transport mode shifts, and behavioural changes. To develop a reference case for the future trajectory of the energy system, we conducted a thorough analysis of recent Chinese energy scenarios and current and emerging energy policies on a regional level. Firstly, the current-available national energy scenario studies that target an energy system transition to meet various climate targets were reviewed to identify regional transitional targets and tasks. Seven sce­ narios from three studies were reviewed to compare the main policies and strategies related to energy system transition pathways in China (Table 2). � The China Renewable Energy Outlook (CREO) examined energy system transition pathways under current domestic policies and the below 2 � C target according to the Paris Agreement. The CREO re­ flects the latest coal reduction policies in China and has the lowest share of energy consumption in the industry sector based on current economic structure adjustment policies in China [16]. � Three scenarios from the International Energy Agency (IEA) are considered, including transition pathways without new policy tar­ gets in the current policy scenario (CPS), NDCs for the Paris Agree­ ment in new policy scenarios, and energy related goals linked to the UN Sustainable Development Goals in the sustainable development scenario [17]. � Two scenarios from the Energy [R]evolution study are included, with high shares of renewable energy, nuclear energy phasing out, and maximum exploitation of efficiency measures. These are the Energy [R]evolution Scenario (E[R]) and the 100% renewable energy sys­ tem in the advanced scenario [27]. The Five-year Plans until 2020 and their trends until 2050 for each province or municipal city are the basis for our reference, the Current Policy Scenario (CPS). To reach the regional CO2 reduction targets we compare the CPS with two alternative options, a Natural Gas & Nuclear Scenario (NGNS) and Renewable & Import Scenario (RIS), which were constructed to assess energy system transition pathways in the two study regions (Table 3). The three scenarios vary not only with regard to lowcarbon heat and power generation options and technologies but also in assumed efficiency improvement potentials. The scenarios differ with regard to: � Energy saving, especially in the industry sector, due to adjustments in the economic structure from a heavy industry based economy towards a service and innovation based economy (from guidelines in the 13th Five-year Plans for Economic and Social Development [44]); � Basic supply strategy: the RIS is assumed to further strengthen the efficiency improvement potentials with deep electrification, compared with the NGNS in both study regions;

4

Energy Strategy Reviews 26 (2019) 100423

M. Xiao et al.

Table 2 Review of national energy scenario studies. Study

Institute

Scenario

China Renewable Energy Outlook Time horizon Main policy and strategy World Energy Outlook

Energy Research Institute 2050

Stated Policy Scenario

Below 2 � C Scenario

Based on current domestic policies Current Policy Scenario

Below 2 � C targets New Policy Scenario

Exclude new policy targets Energy Revolution Scenario

NDCs for Paris Agreements Advanced Scenario

High share of renewable energy with nuclear phasing out and maximum exploited efficiency measures

100% renewable energy system

Time horizon Main policy and strategy Energy [R]evolution Time horizon Main policy and strategy

International Energy Agency 2040 Greenpeace 2050

Table 3 Main strategies for scenario construction in the two study regions. Scenario

Current Policy Scenario

Natural Gas & Nuclear Scenario

Renewable & Import Scenario

Abbreviation

CPS

NGNS

RIS

Same intensity changing rate as China WEO current policy scenario study, indicating no additional new policy effects on energy consumption, extending the trend to 2050

Same intensity changing rate as China WEO sustainable development scenario study, indicating moderate electrification rate effects on energy consumption, extending the trend to 2050 Use of natural gas and nuclear as alternatives to replace coal and oil for locally generation, moderate expansion of renewable energy power generation and import capacity

Same intensity changing rate as national CREO below 2 � C scenario study, indicating the largest effect of electrification rate on energy consumption

Assumptions Efficiency

Power supply

Current situation, driven by shortterm policies

Heat supply

Current situation, driven by shortterm policies

Transport sector

Current situation, driven by shortterm policies

CO2 emissions/ capita by 2050

Based on China WEO current policy scenario study

Use of natural gas as alternative to replace coal, moderate expansion of renewable energy heating supply and electricity for heat Moderate electrification rate

Based on China WEO sustainable development scenario study

Sustainable Development Scenario Interlinked energy related goals to UN SDGs

� Measures in energy conservation in the building sectors (addressed in the 13th Five-year Plans for Energy Saving in Buildings and Green Buildings [45]); � The shift in the mode of transport from road and aviation to rail (highlighted in the 13th Five-year Plans for Integrated Trans­ portation Development [39]); � CO2 emissions per capita: the reduction targets are set according to different national scenario studies with proportional differences be­ tween regional and national averages in 2015 (2.4 times in the BTH region and 2.7 times in the YRD region) [16,17,27]. Based on the strategy developed for the two scenarios, options to transform the fossil fuel dominated energy system in the study regions are also presented in the following. Table 3 gives a detailed insight into the assumptions for each of the scenarios. The NGNS is characterized by the utilization of natural gas and nu­ clear, together with a moderate electrification rate in end-use sectors, to replace coal and oil products for heating, cooling, and mobility. In the NGNS, natural gas and nuclear power plants are further developed as a strategy to reduce reliance on coal power plants, with moderate exploitation of available renewable energies for power generation and a moderate share of imported electricity compared with the RIS. There is a risk that over-investing in gas infrastructure and nuclear expansion may delay a transition to other lower carbon technologies, mainly in forms of renewable energy [46]. Therefore the RIS promotes high shares of renewable energy early on and a high electrification rate in both the heat and transport sectors to achieve regional climate targets higher than the national average [47]. The RIS also phases out nuclear in the YRD re­ gion, does not promote nuclear power plants in the BTH region and limits the expansion of natural gas power and heat plants. Additional power demand from electric heating and electrification of the transport sector is taken into consideration. According to the 13th Five-year Plan for Power Development, by 2020 the electricity used to replace fuels will reach 450 TWh [24]. Power import will be available from other renewable energy abundant provinces such as Inner Mongolia and Sichuan Province. Hydrogen produced from electricity generated with renewable technology is introduced as an option for chemical storage and can be utilized for the production of heat and electricity or recon­ version into electricity for short periods [43]. Compared to the NGNS with a moderate electrification rate in the transport sector, the RIS will further deepen the electrification rate and utilize hydrogen generated from renewable energy sources and synthetic fuels to replace fossil fuels [48,49]. For the heating sector, the district heating system is further developed in the northern region to improve system efficiency compared with the CPS [50]. The effects of these main assumptions will be further discussed in Section 2.4.

Deep electrification and decarbonization of regional energy systems among various sectors, phasing out nuclear and fully utilizing regional renewable energy potentials for power generation, and high share of power import from renewable energy abundant regions Further expansion of renewable energy heating supply, district heating and cooling systems and electricity for heating Modes of transport shift from road to rail both in terms of passengers and goods, high electrification rates, utilization of renewable energy hydrogen and synthetic fuels in transport sector Based on China CREO below 2 � C scenario

5

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

2.4. Main assumptions

2.4.3. Costs and efficiency of fuels and technologies Values for the specific investment costs and fixed operation and maintenance costs for power and CHP plants were taken from a previous study using the China 1.5 � C scenario in 2015 [57]. Regional historic Full Load Hours (FLH) for each technology [58] were used to develop future assumptions based on national scenario studies [27]. CO2 costs from 2020 onwards for CHP units used in the industry, residential and service sectors, public CHP and power plants, as well as prices for fossil fuels, were taken from the national 1.5 � C scenario study [57] with consideration of the expected impact of national carbon markets [59]. Due to the lack of comprehensive investment data for the heat sector, we only accounted for new installations of renewable technologies. In­ vestment costs for biomass, solar heat, geothermal, and heat pumps were based on a previous study [27]. Emission factors for gas transport, refineries, and coal transformation were calibrated from the Multi-resolution Emission Inventory for China v1.0 Database [60]. Technology and fuels transformation efficiency was assumed to increase from the CPS to the NGNS and RIS. For example, efficiency improvement for electrolysis improves by 4% in the RIS compared with the CPS in 2050. The discount rate was set to 6% and the detailed cost and effi­ ciency assumptions under each scenario are available in supplementary materials.

2.4.1. Energy efficiency It was assumed that the RIS had a lower energy intensity compared to the NGNS. The final energy demand of each sector was calculated from the national scenario studies reviewed in Table 3 in terms of energy intensity. Table 4 shows the potential percentage reduction in final energy demand by sector in 2050. The higher reduction rate in the BTH region residential sector compared to the YRD region is due to the currently low efficiency of heating systems in northern China. The higher reduction rate of the BTH region industry sector compared to the YRD region is because of the reduction of capacity, especially for steel production, in the Hebei Province. 2.4.2. Renewable energy potential and import The EnDAT tool was used to perform a land-use assessment to identify areas suitable for wind and solar power generation [51]. The Global Land Cover Database [52] with a spatial resolution of 300 m with 23 land cover types was used to identify these areas with one of three land cover types considered suitable for wind a solar power generation, these were: closed to open (>15%) shrubland, closed to open (>15%) herbaceous vegetation, sparse (<15%) vegetation and bare areas [51]. The suitable areas were then identified as settlements, sand dunes, glaciers, saltpans, protected areas, water-covered areas, or areas with a slope steeper than 2.1� [51]. Land was considered suitable if it had >1 km from a settlement. Both onshore and offshore wind turbines with minimum and maximum generations of 4 m/s and 6 m/s were included. Power generation potentials for solar energy include Concentrating Solar Power (CSP) plants (with an assessment threshold for the annual direct normal irradiance sum of 1600 kWh/m2/y) and Photovoltaic (PV) cells. Biomass as a renewable fuel is a limited resource that has many competing uses such as for electricity and heat generation or as trans­ portation fuels which are all influenced by market-oriented policies [41]. We, therefore, assumed that there would be a very restricted implementation of biomass and biofuels across all sectors. The annual biomass power generation and technical exploitable hydropower gen­ eration potentials by province or municipality are taken from Refs. [53, 54], respectively. Evidence of only a medium to low geothermal po­ tential of 6.1 TWh could be found for the BTH region [55], however, this region has significant potential for the use of geothermal energy for individual and district heating for buildings [56]. The ranges of the regional renewable energy potential for power generation and demand in each scenario are compared in Fig. 3. The minimum and maximum electricity demands are derived from the three scenarios (For a detailed analysis refers to Chapter 3). After 2020, the regional power generation from renewable energy sources cannot meet the growing regional power demand, even at the minimum level. Thus, electricity from other regions, ideally from renewable sources, is required especially when further electrification of the heat and transport sectors increases the power demand towards 2050. Solar (mostly PV) and onshore wind are the most dominant renewable resources for power generation in the BTH region. The YRD region has a higher share of offshore wind and a lower share of solar (all PV) compared to the BTH region. The regional potential of renewable energy for power generation in the two study regions will be fully exploited in the RIS (For a detailed analysis see Section 3.2.1).

3. Results and discussion The simulation results of the transition pathways of the BTH and YRD regions are shown and discussed in the following sub-sections. 3.1. Energy demand The resulting final fuel and electricity energy demands of each enduse sector in each of the two study regions is shown in Fig. 4 and Fig. 5. The improvement of efficiency has a greater effect in the BTH region due to the decarbonization of heat and transport sectors. The share of energy consumed by industry could be reduced in the BTH region from 62% in 2015 to 42% and 37% in the NGNS and RIS, respectively. While in the YRD region, the share of energy consumed by industry would be reduced from 70% in 2015 to 55% and 49% in the NGNS and RIS, respectively. The application of energy-saving standards in the building sector contributed to efficiency improvements in the residential and service sectors. By 2050, the energy demand per capita of the residential sector in the BTH region could decrease by 6 GJ/cap under the NGNS compared to the CPS with a further 2 GJ/cap reduction possible under the RIS. In southern regions like YRD, energy demand per capita is much lower due to a lower heat demand in the winter season. Still, energy efficiency gains can be realized through more efficient cooling systems and other electric appliances. Thus, the energy demand per capita of the residential sector in the YRD region could also decline from the CPS to the NGNS and RIS. There are similar trends in service sectors of the two study regions as well. However, even with the implementation of effi­ ciency measures, energy consumption in both residential and service sectors of the BTH region and the residential sector in the YRD region will increase in the future due to continued urbanization. Moreover, urban areas generally have a higher energy consumption per urban resident compared with rural areas due to improved living standards [61–63]. Energy consumption per capita in the service sector of the YRD region is assumed to be a little lower by 2050 under the NGNS and RIS

Table 4 Assumption of final energy demand reduction potential in the NGNS and RIS compared with the CPS of each study region in 2050. NGNS BTH YRD

RIS

Industry

Residential

Transport

Services

Industry

Residential

Transport

Services

49% 28%

22% 4%

22% 20%

24% 26%

64% 34%

30% 8%

35% 37%

35% 27%

6

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

Fig. 3. Regional renewable energy potentials for power generation compared with power demand from the three scenarios (see Chapter 3) in the two study regions.

Fig. 4. Final fuel and electricity energy demand of each sector under each scenario in the BTH region.

compared with the 2015 level due to improved district heating and cooling systems [50], which transfers industry waste heat to commercial buildings (e.g. policy to prioritize industrial CHP plants for economic development zones in southern Jiangsu Province [34]). In both regions, efficiency measures are essential to curb the massive increase in energy consumption by 2030. Efficiency measures are important if CO2 emis­ sions are to be limited in the short to mid-term. During urbanization, the integrated building designs with smart systems, passive houses and more efficient appliances contributed to increased energy-savings over time. The changes in regional economic structure from a heavy industry-based to a service-based economy also contributed largely to the reduction in

the heat demand of the industry sector, especially in the Hebei, Jiangsu, and Zhejiang Provinces. Efficiency could also be gained from the use of waste heat from the industry sector to heat buildings through well connected district heat networks [50]. In the BTH region, the simulation results show that efficiency measures helped to reduce heat demand by 50% and 72% under the NGNS and RIS in 2050, respectively. Similar reductions could be achieved in the YRD region. Otherwise, heating demand could increase by 11% between 2015 and 2050 under the CPS. The primary mode of transport shifting from private cars to public transportation helps to control energy demand in the transport sector and the electrification of rail and road transport helps to reduce fuel 7

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

Fig. 5. Final fuel and electricity energy demand of each sector under each scenario in the YRD region.

Fig. 6 shows that by 2050, the share of local renewable energy for power generation could increase to 47% and 75% under the NGNS and RIS compared with only 17% under the CPS in the BTH region; under the RIS the share of local fluctuating renewable energy power generation could even reach 67%. Additional storage and other flexibility options such as Demand Side Management (DSM), power to heat, hydrogen, and other fuels are needed to reduce curtailment of VRE power generation, and to improve load balancing and security of the electricity supply [64, 65]. Under the RIS 90% of the CSP plant potential in the Hebei Province could be used as load balancing, with its thermal storage system, similar to the 15 MW demonstration project currently in operation in the Hebei Province. If nuclear power plants are promoted in the BTH region, in the same way as other eastern coastal provinces, installed capacity could reach 9 GW under the NGNS by 2050. To reduce natural gas and nuclear, and with further electrification of heat and transport sectors under the RIS, larger shares of electricity need to be imported from renewable energy abundant regions. This is still the case when available renewable energy resources are fully exploited in the BTH and YRD regions (see section 2.4.2). In the RIS the total installed capacity of wind and solar was 50% larger than in the NGNS and 5.7 times larger than in the CPS in the BTH region by 2050. In the BTH region, solar (mostly PV) could become the main source of domestic electricity, with 85% stemming from PV resources in the RIS, PV could support 44% of regional self-produced electricity. The share of imported electricity (ideally also from renewable sources to avoid “carbon leakage” from consumption centres to supply regions) in the BTH region increased from 30% in 2015 to reach 76% in the RIS compared with 56% in the NGNS and 40% in the CPS. Regional coordination and integration within metropolitan regions and renewable energy abundant regions is crucial to reach overall climate targets. From an energy policy context, it is important to over­ come potential administrative barriers to formulate consolidated tar­ gets, as described in section 2.2. To support the expansion of renewable energies for power genera­ tion, conventional power plants need to operate with reduced FLH. For natural gas power plants this means a reduction to 900 h in the RIS. This means a more significant change in the mode of operation in the BTH region, where plants currently operate at 4830 h compared to the YRD region, where they operate for 2340 h. In contrast, FLH for wind and

consumption. The results also show that power can replace fuels in the heat and transport sectors, especially coal in the heat sector and gasoline in the transport sector. By 2050, the share of power for heat supply could increase from 22% in 2015 to 47% and 68% under the NGNS and RIS compared with 24% under the CPS. The YRD region has a higher pro­ portion of heat from electricity, as no widespread district heating sys­ tems are available. The share of power required to supply heat would be 48% under the CPS to 70% and 82% under the NGNS and RIS, an in­ crease from 35% in 2015. For the transport sector, power consumption in the BTH region could increase from 5% in 2015 to 11%, 41% and 54% under the CPS, NGNS, and RIS, respectively. Starting from only 2% in 2015, transport in the YRD region is slightly lagging behind that of the BTH region, with potential increases in power consumption of 30% and 47% under the NGNS and RIS by 2050. However, electrification of heat and transport leads to “new” power demand sectors, which add to the consumption of “conventional” electric applications, which leads to an overall increase in power demand under the NGNS and RIS, compared to current power demands and those under the CPS. By 2050, the pro­ portion of the total electrical power demand used for heat and transport could increase from 19% under the CPS to 32% and 27% under the NGNS and RIS. In the YRD region, the share of the total electrical power demand for heat and transport appears to be stable in all scenarios due to a lower heat demand compared to the BTH region. Nevertheless, power could become the main heat source in the RIS in the YRD region. 3.2. Energy supply The development of energy supply in the power, heat, and transport sectors and total primary energy supply in the various scenarios are shown and discussed in the following sub-sections. 3.2.1. Power sector The scenarios showed a fundamental change in the structure of the power sector, due to the challenges of coal reduction and a massive increase in consumption due to the electrification of the heat and transport sectors. The integration of renewable sources required new infrastructures, to allow for an integration of VRE both in the NGNS and RIS scenarios. 8

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

Fig. 6. Power generation structure under each scenario in the BTH region.

solar energy could significantly increase by 2050 if such support is ensured (e.g. an increase from 1655 h to 2449 h for onshore wind electricity generation in the BTH region). Fig. 7 shows that in the YRD region, by 2050, renewable energy generation could increase from 41 TWh in 2015 to 897 and 1486 TWh under the NGNS and RIS (more than 80% is VRE), respectively, compared with only 211 TWh under the CPS. If nuclear power plants are further developed in the YRD region, the installed capacity could reach 27 GW under the NGNS by 2050 compared with 12 GW under CPS. In the RIS, only the original 3 GW of nuclear capacity remained. Electricity imports to both regions could come from renewable energy abundant regions, such as Sichuan Province with hydro resources, Inner Mongolia or western provinces with wind and solar energies; although this must be supported by planned and expanded cross-regional High Voltage Direct Current (HVDC) and High Voltage Alternating Current (HVAC) transmission lines [24]. Under the RIS the total installed capacity of wind and solar by 2050 could increase by 55% compared with the NGNS and increase 7 times compared with the CPS, by exploiting 95% of onshore and offshore wind potential. The nationwide installed offshore

wind capacity currently lags behind the set target of 5 GW by 2015 [66]. However, future cost reductions [67,68], development of the domestic offshore wind industry, and eliminating administrative barriers for ocean management and utilization, further installations [69,70] would encourage development of offshore wind, shorter transmission distance with competitive system costs, and less landscape impact compared with onshore wind [71]. This is especially important in the dense urban areas of eastern coastal China. By 2050, offshore wind could supply 47% of the power generation in the YRD region under the RIS but only 25% and 6% under the NGNS and CPS. In contrast to the BTH region, wind would be the primary source of power production in the YRD region. With a higher share of offshore wind in its power system, hydrogen could be produced during peak hours as a storage option. A demonstration project has already been discussed in the 13th Five-year Plan for Wind Power Development (e.g. in Jiangsu Province) [24]. Unlike the large wind bases developed in northern China with high wind speed, onshore wind resources in the YRD region are of low to medium speed. However, exploiting its own available onshore wind resources for power genera­ tion has the advantage of being close to load centres thus reducing

Fig. 7. Power generation structure under scenarios in the YRD region. 9

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

used for heat production during the winter season when heat demand is higher and during peak generation periods. This also helps to both ac­ count for the reduced solar output due to lower levels of solar radiation and balance the VRE through heat storage. This balancing has already been suggested as a valuable option to improve system performance through sector coupling [72]. Compared to the YRD region, the BTH region has the potential to use geothermal energy for individual and district heating supplies in buildings [55,56].

transmission costs. Under RIS the share of imported electricity could be significantly higher: 57% in the YRD region by 2050 compared with 43% under NGNS and 40% under CPS. The share of imported electricity is lower in YRD region compared with BTH region as YRD covers just one megacity but two provinces with larger hinterlands and coastal areas with a significantly higher wind offshore potential. 3 GW and 9 GW of offshore wind energy under NGNS and RIS respectively are expected to provide electricity generation by 2050 with consideration of assumed cost reduction and regional resource potentials.

3.2.3. Transport sector The energy supply for transport changes significantly in the NGNS and RIS as a result of two major strategies: a shift in the mode of transport and an electrification of cars. The RIS led to a higher efficiency in the transport sector compared with the NGNS by further shifting transport from road and aviation to rail (including urban transit and medium to long-distance regional transport). The shift to electric mobility led to additional efficiency gains. By 2050, electricity could be the major fuel for transport in both the NGNS and RIS in the two regions. The use of synthetic fuels could help to replace gasoline for mobility in the RIS, especially for heavy-duty transport, ships, and planes (Fig. 10 and Fig. 11). By 2050, the proportion of oil consumed by the transport sector could drop from 80% under the CPS to 34% under NGNS but only 6% under the RIS in the BTH region. In the YRD region, by 2050, the proportion of oil consumed by the transport sector could decrease from 83% under the CPS to 46% under the NGNS but only 7% under RIS. Such a transformation could largely reduce urban air pollutions from road transport. The energy consumption of the transport sector in metropolitan re­ gions of a developing country such as China cannot be separately dis­ cussed without considering urbanization. Sustainable and integrated urban and regional planning help to increase efficiency and reduce en­ ergy consumption. Moving freight transport from trucks to rail and water modes of transport are considered efficiency measures, as rail and water modes are more energy efficient on a per-ton-km basis [41]. Moving passenger transport from aviation and cars to rail in the RIS both for urban mobility and long-distance travel leads to significant re­ ductions in fuel demand. However, such mode switching needs to be supported by the development of infrastructure, in line with the wide­ spread adoption of alternative fuel vehicles and customer behavioural changes [41]. These strategies led to a much slower increase in energy demand in the road transport sector in the NGNS and RIS and the latter could even stabilize energy demand towards 2050. Electric vehicles help to reduce road pollution from gasoline and diesel cars and can act as storage so electricity from wind and PV can be used during peak generation periods. This helps to integrate VRE into the power system in a cost-effective way. This is especially important

3.2.2. Heat sector Under the precondition of massive efficiency improvements, both the NGNS and RIS scenarios manage to phase out oil, and most of the coal, in the heat sectors in both regions (see Figs. 8 and 9). The CPS retains coal as the main heat source using “clean coal” technology as the base heat supply, as stated in the current policy; whereas the alternative scenarios implement a strong diversification of heat applications instead. The NGNS follows and enhances the short-term policy of promoting natural gas for heating to replace coal boilers and coal-fired CHP plants, and supplements this with other sources such as geothermal, heat pumps, and electricity. The RIS scenario, with larger efficiency gains, could further reduce fossil fuels of gas and coal, leading to a heat supply sys­ tem supplied predominantly by renewable energies. Modern use of biomass and waste for heating and CHP plants, with existing and plan­ ned district heating systems, could contribute to the elimination of lowefficiency, highly-polluting coal-fired boilers and CHP plants, especially in urban areas. Moreover, the development of biomass and waste for heating and CHP plants includes a the use of low temperature sources for space heating and hot water, such as solar thermal collectors and ambient heat via heat pumps. In the BTH region, the share of renewables for heat supply could reach 12%, 45% and 69% under the CPS, NGNS, and RIS, respectively, by 2050, up from only 6% in 2015. Solar heat and biomass could complement each other specifically in district heating systems and the regional potentials of geothermal for heating [55,56] have been exploited in the RIS. In the YRD region, renewables could supply 44% under the NGNS and 65% under the RIS by 2050. Here, electric heating, direct or via heat pumps, supports space heating and hot water; however, the total power demand for heating is even lower than in the CPS in 2050. For both regions, this requires strong efforts and coordinated planning in the refurbishment and construction of buildings. District heating and use of natural gas, electricity, solar, and geothermal energy for heating in small towns and rural areas need to be further promoted to achieve the replacement of traditional coal stoves and biomass with low efficiencies [20]. Fluctuating wind power could be

Fig. 8. Heat supply by fuel under each scenario in the BTH region. 10

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

Fig. 9. Heat supply by fuel under each scenario in the YRD region.

Fig. 10. Final energy demand by fuel for the transport sector under each scenario in the BTH region.

Fig. 11. Final energy demand by fuel for the transport sector under each scenario in the YRD region.

11

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

Fig. 12. Primary energy supply from each renewable source in the BTH region under each scenario.

where renewables have largely penetrated the power system such as in the RIS [73]. While battery-electric vehicles dominate renewable vehi­ cles in the Chinese market at the moment and refuelling stations in China only exist in 7 main cities, after 2030, hydrogen and other syn­ thetic fuels produced from renewable energy electricity could supply fuels for road transport as well, where electric drive systems are at their limit (e.g. in heavy-duty vehicles). 3.2.4. Primary energy As a result of the shifts in final energy demand, we see a major transformation of the primary energy supply in the NGNS and RIS. In both regions, this transformation leads to a significant reduction of coal and oil products, which takes place more rapidly in the BTH region, mainly due to the more comprehensive electrification of the heat and transport sectors. However, primary energy supply is also supplemented by power imports from other regions, which are also presented in Figs. 12 and 13. In both the BTH and YRD regions, power imports in­ crease in line with the proportion of renewables in the system. To further replace natural gas and nuclear power, 58% and 54% of power needs to be imported in the RIS in the BTH and YRD regions, respectively. This is

Fig. 14. Cumulative CO2 budgets from 2015 to 2030 and 2015–2050 in the two study regions.

Fig. 13. Primary energy supply from each renewable source in the YRD region under each scenario. 12

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

much higher than in the other scenarios, resulting in increased primary energy exports from other regions such as Inner Mongolia and Sichuan Province. Nevertheless, compared with the CPS, primary energy demand and renewable electricity imports could be reduced in both regions in the RIS and NGNS scenarios. In the RIS, the remaining primary energy is mainly based on renewables. In the BTH region the reduction in total primary energy could be 43% and 61% under the NGNS and RIS, respectively. Without additional measures under the CPS, coal consumption could peak in 2035, crude oil and natural gas could continue to grow until 2050 to 7000 PJ and 4100 PJ, respectively. Effective measures for fuel alternatives and the improvement of efficiency in the transport sector could largely reduce the demand for crude oil products thus reducing national energy import dependency (Fig. 12). In YRD region, the potential for reductions in primary energy de­ mand is slightly less than in the BTH region; the primary energy demand reduced by 34% and 59% under the NGNS and RIS, respectively, compared to the CPS. But coal consumption in the YRD peaks in 2020 at 15,000 PJ, much earlier than in the BTH region under the CPS (Fig. 13).

curb overall GHG emissions but it must start immediately. However, the transition process requires continuous investment into renewable energies for power and heat supply under the NGNS and RIS. For the power sector the required investments could be large, both in terms of installed capacity and grid and storage infrastructures [74]. On the other hand, these studies also calculate the energy transition pay-off through reduced fuel costs and cost reduction for installations such as PV and wind in the long-term. Our study shows that the total investment costs for power and CHP plants are CPS < NGNS < RIS, mainly due to additional power demand from the heat and transport sectors (Fig. 15). However this will be compensated for through a reduction in fuel costs for power and CHP. Compared with the CPS, the fuel costs under the NGNS and RIS would be largely reduced. Compared with the CPS, the fuel costs would be only 67% and 43% under the NGNS and RIS, respectively, in the BTH region. For the YRD region, this reduction is slightly lower, reaching 78% of the CPS fuel costs under the NGNS and 51% under the RIS. However, to reach regional climate targets, addi­ tional costs are incurred when importing electricity. From our potential analysis, we calculated a mean imported electricity price of 0.06 €/kWh, which is 0.02 €/kWh lower than the costs of locally generated electricity in average. The accelerated electrification in the alternative scenarios could also curb investment costs in the heat sector. However, without compre­ hensive investment accounting of the heat sector as for the power sector, we calculated only cumulative investment costs for the renewable heat applications in each scenario to give an indication of additional heat cost. For the BTH region, investment requirements in renewable heat ranged between $500–600 billion under the NGNS and RIS. These are much higher than the YRD region, where retrofitting of district heating systems in urban areas is not needed. In the YRD region, which is dominated by individual heating devices, the additional investment costs for heat supply range between $200–300 billion under the NGNS and RIS. In both regions, these investments are small compared to in­ vestment and fuel costs in the power and CHP sectors.

3.3. Effects on CO2 emissions and costs With renewable energies replacing fossil fuels and improving elec­ trification rates in the heating and transport sectors, the regional CO2 emissions could significantly reduce under the NGNS and RIS compared with the CPS. In the BTH region, the regional CO2 emissions per capita could be reduced from 15.5 t/cap in 2015 to 4.4 and 1.1 t/cap under the NGNS and RIS, respectively, compared with 15.2 t/cap under the CPS. Due to wide-spread electrification in both regions, the remaining CO2 emissions are predominantly from gas in the power sector under the NGNS and RIS. In the YRD region, the regional CO2 emissions per capita could be reduced even further from 17.6 t/cap in 2015 to 3.5 and 0.6 t/ cap under the NGNS and RIS, respectively, by 2050 compared with 12.5 t/cap under the CPS. This leads to higher overall emission re­ ductions in the YRD region than in the BTH region. However, compared with national below 2 � C climate targets, the regional NGNS could not match the national average target of 2.15 t/cap by 2050. The RIS could help regions achieve higher climate targets than the national average, such as below 1.5 � C. Energy reductions in large demand centres could also contribute to energy system transitions in supply regions with a high proportion of renewable energies in the power sector. The cumu­ lative CO2 budget could be cut by half between 2015 and 2050 under the RIS (Fig. 14), with a higher potential for reduction in the BTH region. Fig. 14 also shows that the reduction will take a long time to come into effect. Therefore the transition towards a low carbon future can help to

4. Conclusion and discussion Our scenario analysis shows two possible transition paths for the decarbonization of the energy systems in two regions. The transition paths highly depend on efficiency measures, policies for nuclear, natural gas, and coal development, and regional exploitation of renewable re­ sources (especially solar and wind) with the implicit assumption of substantial storage and electricity import capacity expansion. This study extends national NDCs from 2030 to possible regional targets by 2050 with a regionally integrated multi-sectoral analysis. The results show

Fig. 15. Selected cumulative costs during the transition period (2015–2050) for each scenario in the two study regions. 13

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

that ambitious policies to manage the penetration of renewable energy and natural gas as substitutes for coal and oil are needed to achieve the targets, both in the supply and consumption sectors and not only at national but also at regional level. However, a recent analysis of current policy [7] has indicated, that such measures are not yet in place. Such firm commitments beyond 2030 help to create investment security and build confidence among the relevant actors for long-term business op­ portunities. This is particularly important for technologies still in the early stages of deployment, such as CSP, offshore wind, and ocean en­ ergy [71]. With additional policies triggering the transformation and necessary sectoral and regional integration, the regional CO2 emissions could be largely reduced to address national climate targets. This holds true especially for the RIS through the penetration of renewable energies into various sectors, shifts in transport mode, the development of district heating and cooling systems, electrification in heat and transport sec­ tors, and the production and use of synthetic fuels. Improvements in energy efficiency are paramount to decarbonization strategies, which is why the NGNS and RIS use different potentials. Our study also shows that a policy should also focus on industrial restructuring, in particular, to reduce overcapacity in heavy industry and district heating in the BTH region which would reduce coal consumption. In the YRD region, the exploitation of offshore wind, improving the efficiency of cooling systems and the utilization of industrial waste heat are the most important targets. The decarbonization of the transport sector, not only in both regions but also worldwide, largely depends on electrification, with biofuels, hydrogen, and synthetic fuels as important complementary options to direct electricity use. The decarbonization of the transport sector would result in large environmental benefits, especially in urban areas. The high electricity demand and the high electrification rate in all sectors of the RIS implicitly require the devel­ opment of suitable electricity market mechanisms, improved system flexibility, and appropriate supply security measures. Imports of both electricity and natural gas are particularly important for China’s eastern coastal metropolitan regions on their way to achieving their CO2 emis­ sions reduction targets. This study discusses key premises and strategies for regional energy systems using the example of two possible decarbonization paths. A further sensitivity analysis of key assumptions is needed to discuss the robustness and uncertainty of the scenarios constructed here. Large uncertainty arises from the future economic structure of China, and in particular the development of the tertiary sector. The extent to which electrification in the heat and transport sectors can be achieved, and the measures that can be taken to achieve it, also require further examina­ tion. Uncertainties also stem from the competitiveness of various low carbon technologies and the expansion of transmission capacity and storage. The Carbon capture and storage technology for fossil fuel power and heating plants as a mitigation option is not taken into consideration due to possible limitations in storage capacity and costs uncertainties. Additionally, global natural gas markets with import pipelines and ca­ pacities to export to China, and the future development of natural gas prices are further uncertainties, especially for the NGNS. Sustainable urban and rural development strongly influences energy efficiency, for example, through the use of solid urban waste for heat generation and integrated transport and land use planning to support the energy system transition in metropolitan regions. Regional development plans must therefore also consider interdependencies with energy policies of other regions, which currently is not yet the case. More research is required to identify how to support and develop a market based flexible system for the supply and consumption of both power and heat. Appropriate con­ cepts need to combine utility-scale and decentralized renewable sources and local capacities with energy exchange across provincial and regional borders. Our scenarios are a first step to identify the key challenges, not only from a national but a regional perspective, highlighting the importance of regional integration especially for the power system. Electricity generation from VRE sources is highly weather dependent, thus more information is necessary to guarantee supply security in

extreme weather conditions. Challenges of system integration rise with the expansion of renewable energies for both regionally generated and imported electricity. A higher temporal resolution is needed to analyse storage needs, particularly for short-term electricity storage such as batteries, and to use excess electricity for the heating and transport sectors. Nevertheless, our study provides insights into cross-sectoral challenges arising from long-term targets, which require additional focus during the development of regional policies in the medium-term. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi. org/10.1016/j.esr.2019.100423. References [1] IPCC, Climate Change 2014: Synthesis Report - Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC, 2014. [2] S. Wei, Enhanced Actions on Climate Change: China’s Intended Nationally Determined Contributions, Department of Climate Change, National Development and Reform Commission of China, 2015. [3] IEA, World Energy Outlook 2018, International Energy Agency, 2018. [4] China Renewable Energy Outlook, China Research Institute of Academy of Macroeconomic Research/NDRC, China National Renewable Energy Center, 2018, 2018. [5] China Statistical Year Book, National Bureau of Statistics of China, 2016. [6] A. Li, M. Hu, M. Wang, Y. Cao, Energy consumption and CO2 emissions in Eastern and Central China: a temporal and a cross-regional decomposition analysis, Technol. Forecast. Soc. Chang. 103 (2016) 284–297, https://doi.org/10.1016/j. techfore.2015.09.009. [7] M. Xiao, S. Simon, T. Pregger, Energy system transitions in the eastern coastal metropolitan regions of China—the role of regional policy plans, Energies 12 (2019), https://doi.org/10.3390/en12030389. [8] X. Ou, Z. Yuan, T. Peng, Z. Sun, S. Zhou, The low-carbon transition toward sustainability of regional coal-dominated energy consumption structure: a case of Hebei province in China, Sustainability 9 (2017), https://doi.org/10.3390/ su9071184. [9] C. Schlenzig, PlaNet: ein entscheidungsunterstützendes System für die Energie- und Umweltplanung, Universit€ at Stuttgart, 1998. [10] Seven2one. Mesap documentation, Available online: http://www.seven2one.de/en /technology/mesap.html, 2015. (Accessed 7 September 2015). [11] S. Simon, N. Tobias, H.C. Gils, Transformation towards a renewable energy system in Brazil and Mexico - technological and structural options for Latin America, Energies 11 (4) (2018). [12] China Renewable Energy Data Booklet, 2017. [13] China Transportation Yearbook, China Transportation Publication, 2016. [14] WWF, Shanghai Low Carbon Development Roadmap Report, WWF Shanghai Low Carbon Development Roadmap Research Team, 2011, 2050. [15] China Energy Statistics, China Statistics Press, 2016. [16] China Renewable Energy Outlook, China Research Institute of Academy of Macroeconomic Research/NDRC, China National Renewable Energy Center, 2017, 2017. [17] IEA, World Energy Outlook 2017, International Energy Agency, 2017. [18] China oil consumption (1965-2017), Available online: https://www.ceicdata.co m/en/indicator/china/oil-consumption. (Accessed 21 March 2018). [19] EIA, China Surpassed the United States as the World’s Largest Crude Oil Importer in 2017, 2018. Available online: https://www.eia.gov/todayinenergy/detail.php? id¼34812. (Accessed 12 April 2018). [20] Clean Heating Plan for Northern China (2017-2021), National Development and Reform Commission, 2017. [21] NDRC, 13th Five-Year Plan for Natural Gas Development (2016-2020) (天然气发展 “十三五”规划), 2017. [22] GOSC, Action Plan on Prevention and Control of Air Pollution (大气污染防治行动计划 ), General Office of the State Council, 2013. [23] D. Sandalow, A. Losz, S. Yan, A Natural Gas Giant Awakens: China’s Quest for Blue Skies Shapes Global Markets, 2018. [24] NDRC, 13th National Five-Year Plan for Power Development (电力发展“十三五”规划 (2016-2020 年)), National Development and Reform Commission, National Energy Board, 2016. [25] 13th Five-Year Plan for Beijing-Tianjin-Hebei Region Renewable Energy Development, National Development and Reform Commission (NDRC), 2016. [26] China 2050 High Renewable Energy Penetration Scenario and Roadmap Study, Energy Research Institute of National Development and Reform Commission, 2015.

14

M. Xiao et al.

Energy Strategy Reviews 26 (2019) 100423

[27] S. Teske, S. Sawyer, O. Sch€ afer, T. Pregger, S. Simon, T. Naegler, et al., Energy [R] evolution - A Sustainable World Energy Outlook, Greenpeace International, Global Wind Energy Council, SolarPowerEurope, Deutsches Zentrum für Luft- und Raumfahrt (DLR), 2015. [28] M.Z. Jacobson, M.A. Delucchi, Z.A.F. Bauer, S.C. Goodman, W.E. Chapman, M. A. Cameron, et al., 100% clean and renewable wind, water, and sunlight all-sector energy roadmaps for 139 countries in the world, Joule 1 (2017) 108–121, https:// doi.org/10.1016/j.joule.2017.07.005. [29] NDRC, 13th National Five-Year Plan for Renewable Energy Development (可再生能源发展“十三五”规划), National Development and Reform Commission, 2016. [30] NEA, Renewable Portfolio Standard Policy (RPS) (可再生能源配额政策), National Energy Administration, 2016. [31] NDRC, 13th National Five-Five Plan for Energy Development (能源发展“十三五”规划), National Development and Reform Commission, National Energy Board, 2017. [32] 13th Five-Year Plan for Energy Development in Hebei Province, Government of Hebei Province, 2017. [33] 13th Five-Year Plan for Energy Development of Shanghai, Shanghai Government, 2017. [34] 13th Five-Year Plan for Power Development in Jiangsu Province, Jiangsu Province Development and Reform Commission, 2016. [35] 13th Five-Year Plan for Energy Development in Beijing, Beijing Development and Reform Commission, 2017. [36] L. Sun, B. Pan, A. Gu, H. Lu, W. Wang, Energy–water nexus analysis in the Beijing–Tianjin–Hebei region: case of electricity sector, Renew. Sustain. Energy Rev. 93 (2018) 27–34, https://doi.org/10.1016/j.rser.2018.04.111. [37] Y. Dai, P. Lynn, C. Jon, et al., Reinventing Fire: China - A Roadmap for China’s Revolution in Energy Consumption and Production to 2050, Executive Summary, Energy Research Institute, Lawrence Berkeley National Laboratory and Rocky Mountain Institute, 2016. [38] Research Report for Energy Consumption in Buildings of China, 2016, 2016. [39] 13th Five-Year Plan for Modern Integrated Transport System Development (20162020), General Office of the State Council, 2017. [40] Policy Report for Electric Vehicles Charging Infrastructure Market during 13th Five-Year Plan Period, 2017, 2017. [41] L. Vimmerstedt, et al., High Penetration of Renewable Energy in the Transportation Sector: Scenarios, Barriers, and Enablers, National Renewable Energy Laboratory and Argonne National Laboratory, 2012. [42] IPCC, Exploratory and Normative Scenarios, 2014. [43] T. Pregger, J. Nitsch, T. Naegler, Long-term scenarios and strategies for the deployment of renewable energies in Germany, Energy Policy 59 (2013) 350–360, https://doi.org/10.1016/j.enpol.2013.03.049. [44] NDRC, 13th Five-Year Plan for Economic and Social Development (中华人民共和国国民经济和社会发展第十三个五年规划纲要), National Congress, 2016. [45] 13th Five-Year Plan on Building Energy Saving and Green Buildings, Ministry of Housing and Urban-Rural Development, 2017. [46] B. Solano-Rodríguez, A. Pizarro-Alonso, K. Vaillancourt, C. Martin-del-Campo, Mexico’s transition to a net-zero emissions energy system: near term implications of long term stringent climate targets, in: G. Giannakidis, K. Karlsson, M. Labriet, � Gallach� B.O. oir (Eds.), Limiting Global Warming to Well below 2 textdegreeC: Energy System Modelling and Policy Development, Springer International Publishing, Cham, 2018, pp. 315–331, https://doi.org/10.1007/978-3-319-744247_19. [47] R. Kannan, H. Turton, Long term climate change mitigation goals under the nuclear phase out policy: the Swiss energy system transition, Energy Econ. 55 (2016) 211–222, https://doi.org/10.1016/j.eneco.2016.02.003. [48] E. Shafiei, B. Davidsdottir, J. Leaver, H. Stefansson, E.I. Asgeirsson, Comparative analysis of hydrogen, biofuels and electricity transitional pathways to sustainable transport in a renewable-based energy system, Energy 83 (2015) 614–627, https:// doi.org/10.1016/j.energy.2015.02.071. [49] E. Shafiei, B. Davidsdottir, J. Leaver, H. Stefansson, E.I. Asgeirsson, Energy, economic, and mitigation cost implications of transition toward a carbon-neutral

[50] [51] [52] [53] [54] [55] [56] [57]

[58] [59] [60] [61] [62]

[63] [64] [65] [66] [67] [68] [69] [70] [71] [72] [73] [74]

15

transport sector: a simulation-based comparison between hydrogen and electricity, J. Clean. Prod. 141 (2017) 237–247, https://doi.org/10.1016/j. jclepro.2016.09.064. OECD/IEA, District Energy Systems in China: Options for Optimisation and Diversification, IEA and Tsinghua University, 2017. D. Stetter, Enhancement of the REMix Energy System Model: Global Renewable Energy Potentials, Optimized Power Plant Siting and Scenario Validation, Universit€ at Stuttgart, 2014. E. Bartholom� e, A.S. Belward, GLC 2000: a new approach to global land cover mapping from earth observation data, Int. J. Remote Sens. 26 (2005) 1959–1977, https://doi.org/10.1080/01431160412331291297. K. Song, J. Zhou, P. Zhang, S. Kan, Assessment of biomass power potential on provincial scale and analysis on plan target quota, Forum Sci. Technol. China 0 (2016) 124–129. Y. Hu, H. Cheng, Displacement efficiency of alternative energy and trans-provincial imported electricity in China, Nat. Commun. 8 (2017) 14590. CREIA, The Current Status of 2017 and Future Development of Geothermal Power Generation in China, 2016. NDRC, 13th National Five-Year Plan for Geothermal Development (地热能开发利用“十三五”规划), National Development and Reform Commission, National Energy Administration, National Ministry of Land and Resources, 2017. S. Teske, D. Giurco, T. Morris, K. Nagrath, F. Mey, C. Briggs, et al., Achieving the Paris Climate Agreement Goals: Global and Regional 100% Renewable Energy Scenarios to Achieve the Paris Agreement Goals with Non-energy GHG Pathways for þ1.5� C and þ2� C, Springer, Cham, 2019. Statistics of Power Industry Development of China, China Electric Power Press, 2016. On going program of carbon trading in 5 municipalities and 2 provinces (碳交易试点七省市进行时), Available online: https://www.china5e.com/su bject/show_750.html. (Accessed 1 November 2018). Multi-resolution Emission Inventory for China v.1.0, MEIC Database, 2016. Q. Wang, Effects of urbanisation on energy consumption in China, Energy Policy 65 (2014) 332–339, https://doi.org/10.1016/j.enpol.2013.10.005. Z. Wang, Z. Zhao, B. Lin, Y. Zhu, Q. Ouyang, Residential heating energy consumption modeling through a bottom-up approach for China’s Hot SummerCold Winter climatic region, Energy Build. 109 (2015) 65–74, https://doi.org/ 10.1016/j.enbuild.2015.09.057. G. Jin, Z.K. Nina, Z. Xinye (Eds.), Electricity Demand in Chinese Households: Findings from China Residential Energy Consumption Survey, 2016. H.C. Gils, Balancing of Intermittent Renewable Power Generation by Demand Response and Thermal Energy Storage, Universit€ at Stuttgart, 2015. P.D. Lund, J. Lindgren, J. Mikkola, J. Salpakari, Review of energy system flexibility measures to enable high levels of variable renewable electricity, Renew. Sustain. Energy Rev. 45 (2015) 785–807, https://doi.org/10.1016/j.rser.2015.01.057. 13th National Five-Five Plan for Wind Energy Development (2016-2020), National Energy Board, 2016. IRENA, Renewable Energy Auctions: Analysing 2016, 2017. IRENA, Renewable Power Generation Costs in 2017, 2018. L. Hong, B. M€ oller, Offshore wind energy potential in China: under technical, spatial and economic constraints, Energy 36 (2011) 4482–4491, https://doi.org/ 10.1016/j.energy.2011.03.071. X. Zhao, L. Ren, Focus on the development of offshore wind power in China: has the golden period come? Renew. Energy 81 (2015) 644–657, https://doi.org/ 10.1016/j.renene.2015.03.077. Pathways to Deep Decarbonization: 2014 Report, 2014. W. Xiong, Y. Wang, B.V. Mathiesen, H. Lund, X. Zhang, Heat roadmap China: new heat strategy to reduce energy consumption towards 2030, Energy 81 (2015) 274–285, https://doi.org/10.1016/j.energy.2014.12.039. D Luca de Tena, Large Scale Renewable Power Integration with Electric Vehicles, Universit€ at Stuttgart, 2014. S. Pfenninger, J. Keirstead, Renewables, nuclear, or fossil fuels? Scenarios for Great Britain’s power system considering costs, emissions and energy security, Appl. Energy 152 (2015) 83–93, https://doi.org/10.1016/j.apenergy.2015.04.102.