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As a relatively mature technology, biomass molded fuel (BMF) is widely used in distributed and centralized heating in China and has received considerable government attention. Although many BFM incentive policies have been developed, decreased domestic traditional fuel prices in China have caused BMF to lose its economic viability and new policy recommendations are needed to stimulate this industry. The present study built a regionalized net present value (NPV) model based on real production process simulation to test the impacts of each policy factor. The calculations showed that BMF production costs vary remarkably between regions, with the cost of agricultural briquette fuel (ABF) ranging from 86 US dollar per metric ton (USD/t) to 110 (USD/t), while that of woody pellet fuel (WPF) varies from 122 USD/t to 154 USD/t. The largest part of BMF’s cost composition is feedstock, which accounts for up 50%–60% of the total; accordingly a feedstock subsidy is the most effective policy factor, but in consideration of policy implementation, it would be better to use a production subsidy. For ABF, the optimal product subsidy varies from 26 USD/t to 57 USD/t among different regions of China, while for WPF, the range is 36 USD/t to 75 USD/t. Based on the data, a regional BMF development strategy is also proposed in this study.

Abstract How to increase clean energy utilization is a key issue in household energy consumption analysis aimed at alleviating air pollution and improving the health of residents. Clean energy substitution is a complex decision process between related stakeholders, and is affected by a combination of factors such as geographical location and household income. To evaluate the potential of clean energy promotion to contribute to better policy decisions and measures, an agent-based household energy consumption model is established to capture the group habits of different stakeholders and the impact mechanism of critical influential factors. Multi-layered structures including various types of households and energy consumption devices are modeled. The experimental results of several scenario analyses show that increased income, improved technology and subsidies from local governments can influence clean energy substitution in the household in various ways. These findings provide a better understanding of the energy cleaning process and decision-making support for governments.

Abstract Identifying the appropriate amount of subsidy is crucial to spur the development of low carbon electricity technologies such as wind power that are currently not competitive with conventional coal-fired power on the basis of levelized cost. Though essential for formulating subsidy policy, most of the existing planning tools have not been tailored for policymakers, especially at the sub-national level. In this paper, we introduce an integrated renewable power planning (IRPP) model that is both practical and flexible. This model integrates resource databases, equipment databases and levelized cost calculation module to generate supply curves for wind and solar and evaluate potential subsidy to achieve a certain installation target. A case study focused on wind power planning in Fujian Province is performed. Under the wind power feed-in-tariff of 0.61 yuan/kWh, the generation can reach about 3.7 TWh, and total subsidy will be about 260 million yuan (including subsidies already paid to existing projects). Sensitivity analysis shows that this number will significantly increase if capital cost of wind is reduced or external cost of coal-fired power is internalized.

China has built the world’s largest power transmission infrastructure by consuming massive volumes of greenhouse gas- (GHG-) intensive products such as steel. A quantitative analysis of the carbon implications of expanding the transmission infrastructure would shed light on the trade-offs among three connected dimensions of sustainable development, namely, climate change mitigation, energy access and infrastructure development. By collecting a high-resolution inventory, we developed an assessment framework of, and analysed, the GHG emissions caused by China’s power transmission infrastructure construction during 1990–2017. We show that cumulative embodied GHG emissions have dramatically increased by more than 7.3 times those in 1990, reaching 0.89 GtCO2-equivalent in 2017. Over the same period, the gaps between the well-developed eastern and less-developed western regions in China have gradually narrowed. Voltage class, transmission-line length and terrain were important factors that influenced embodied GHG emissions. We discuss measures for the mitigation of GHG emissions from power transmission development that can inform global low-carbon infrastructure transitions. Expanding energy infrastructure has been vital to China’s development plans, but has had negative consequences. This study finds that in 2017 the level of embodied greenhouse gas emissions from the expansion of China’s power transmission infrastructure increased by more than 7.3 times that in 1990.

Abstract Cities are the major contributors to energy consumption and CO2 emissions, as well as being leading innovators and implementers of policy measures in climate change mitigation. Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is an agglomeration of cities put forward by China to strengthen international cooperation among “Belt and Road” countries and promote low-carbon, inclusive, coordinated and sustainable development. Few studies have discussed the emission characteristics of GBA cities. This study, for the first time, compiles emission inventories of 11 GBA cities and their surroundings based on IPCC territorial emission accounting approach, which are consistent and comparable with the national and provincial inventories. Results show that (a) total emissions increased from 426 Mt in 2000 to 610 Mt in 2016, while emissions of GBA cities increased rapidly by 6.9% over 2000–2011 and peaked in 2014 (334 Mt); (b) raw coal and diesel oil are the top two emitters by energy type, while energy production sector and tertiary industry are the top two largest sectors; (c) GBA cities take the lead in low-carbon development, emitted 4% of total national emissions and contributed 13% of national GDP with less than a third of national emission intensities and less than three-quarters of national per capita emissions; (d) Macao, Shenzhen and Hong Kong have the top three lowest emission intensity in the country; (e) most of GBA cities are experiencing the shift from an industrial economy to a service economy, while Hong Kong, Shenzhen, Foshan and Huizhou reached their peak emissions and Guangzhou, Dongguan and Jiangmen remained decreasing emission tendencies; (g) for those coal-dominate or energy-production cities (i.e. Zhuhai, Zhongshan, Zhaoqing, Maoming, Yangjiang, Shanwei, Shaoguan and Zhanjiang) in mid-term industrialization, total emissions experienced soaring increases. The emission inventories provide robust, self-consistent, transparent and comparable data support for identifying spatial–temporal emission characteristics, developing low-carbon policies, monitoring mitigation progress in GBA cities as well as further emissions-related studies at a city-level. The low-carbon roadmaps designed for GBA cities and their surroundings also provide a benchmark for other developing countries/cities to adapting changing climate and achieve sustainable development.

A stochastic method to compute the operation of active distribution networks (DNs) under different configurations with renewable distributed generators (DGs) and energy storage (ES) systems is proposed. Based on this method, evaluations of the effect on minimizing the total hourly operation cost under the integration of all or a part of wind, solar DGs and ESs is completed. The uncertainties of load demand, wind speed and solar irradiance, as well as the carbon emission cost are also considered. The simulation results show the large potential of carbon emission trading in improving the penetration rate of renewable energy (especially for wind energy without large-scale deployments of ESs in active DNs), and the advantages of hybrid renewable DGs compared to wind, solar DGs solely.

Abstract To meet the needs of fuel security and combat the growing concerns of CO2 emissions, the automotive industry is seeking solutions through biofuels. Traditionally, when supplying biofuel blends to the combustion chamber, the blend is mixed externally prior to its injection in one location. This location occurs either before the cylinder (port-fuel injection, PFI), or directly into the cylinder (direct-injection, DI). However, the use of dual-injection allows the in-cylinder blending of two fuels at any blend ratio, when combining the two locations (PFI and DI). This injection strategy offers increased flexibility as the blend ratio can be changed instantaneously according to engine speed and load demand and fuel availability. Previous work by the authors has reported the improved combustion performance of dual-injection with 25% blends (in gasoline) of a new biofuel candidate: 2,5-dimethylfuran (DMF). This current investigation extends the analysis to include the gaseous emissions of various DMF blends (25%, 50% and 75%) from 3.5 bar to 8.5 bar IMEP and the particulate matter (PM) emissions of similar fraction ethanol blends at a selected condition of 5.5 bar IMEP. Compared to DI, dual-injection offers reduced CO and CO2 emissions and comparable HC emissions. The mean PM diameter is decreased and the accumulation mode particles are negligible compared to DI. However, the implication of the higher combustion pressures is an increase in NOx due to reduced charge-cooling.

The energy balancing problem is the main challenge for the effective application of micro combined heat and power (m-CHP) in a residential context. Due to its high energy density and relative robustness, the lead-acid battery is widely used for power demand management to compensate the mismatch between the m-CHP electrical output and domestic demand. However, batteries are not suited to respond effectively to high frequency power fluctuations, but when coupled to the m-CHP, they experience frequent short-term charge/discharge cycles and abrupt power changes, which significantly decreases their lifetime. This paper addresses this problem by hybridising the lead-acid battery storage with superconducting magnetic energy storage (SMES) to form a hybrid energy storage system (HESS) that is coordinated by a novel sizing based droop control method. The control method for the first time considers both the capacity sizing of the HESS technologies and the droop control method of the battery and the SMES. A hardware in the loop test circuit is developed coupling with the real time digital simulator (RTDS) to verify the performance of the HESS with the new control algorithm. The experimental results show that control method is able to exploit the different characteristics of the SMES and the battery to meet the mismatch of m-CHP power generation and domestic demand. In addition, the lifetime analysis is implemented in this paper to quantify the battery lifetime extension in the HESS, which further proves the validity of the proposed control strategy.