Replacing traditional fossil energy with renewable biofuel is considered to be an effective way to achieve the emission reduction target. The optimal design and operation of the supply chain is the key step in the large-scale development of biofuel. To fully utilize the extensive oil and gas supply chain infrastructure in China, this paper intends to incorporate liquid biofuel into the existing refined product supply network and explore the benefits of this integrated supply chain. Firstly, a mixed-integer linear programming model for a single-cycle integrated supply chain is developed to obtain the optimal supply scheme, transportation scheme and demand scheme of both liquid biofuel and refined product. The objective is set to minimize the total cost, including depreciated investment cost of bio-refinery, liquid fuel transportation cost, backlog cost on supply side and stock-out cost on demand side. The geographical distribution of biofuel yield, refinery production capacity, oil depot inventory levels and transportation volume requirements are rigorously considered. Finally, the existing refined product supply train in China is taken as a case study and two scenarios (with and without biofuel participation) are carried out for comparison from the perspective of economy and environment. The results demonstrate the economic and environmental benefit of the proposed integrated liquid biofuel-refined product supply chain, which can provide significant guidelines for the decision makers.
Due to speeding up urbanization and increasing living standards of city residents, environmental consequence of both production and consumption activities have raised air pollution issue as one of major concern worldwide. Among varied air pollutants, PM2.5 does only contribute to respiratory diseases, but also causing cardiopulmonary, ischemic disease, etc. It may further cause extremely unequal impact on age or affluence-based population groups, due to its varying spatial concentration. To investigate its exposure to citizens from economical aspect, we firstly extract affluence-based residents in Shanghai city, China, based on the most recent housing price and population data, then analyzed its potential exposure to PM2.5 across the year of 2019. Direction analysis is applied to comparing the varied exposure levels to PM2.5 by affluence-specific population. Results suggest the highest PM2.5 exposure is found in the central wards of Shanghai, which is also featured by average housing price over 40,000 yuan. People living in 60,000 yuan above housing of Shanghai city are exposed to the highest PM2.5 pollution, in winter in particular.
Reduction of fuel consumption and lowering harmful gas emissions are among the most important research topics in marine transportation. The latter particularly refers to the vessels that operate within highly inhabited areas like short-sea vessels. This paper deals with the techno-economic assessment of the implementation of renewable energy sources in the short-sea shipping sector, where Croatian ro-ro passenger fleet is taken as a test case. In this sense, the aim of the paper is to identify preferable power system configuration that reduces ship emissions (CO2, NOX, SOX, particulates) at acceptable costs. Firstly, realistic operating profile of ro-ro passenger ships is analysed and their annual emissions are evaluated by assessing total fuel consumption and multiplying it by relevant emission factors. Secondly, renewable energy potential in the Adriatic Sea and Croatian energy mix are reviewed. Third, the techno-economic analysis of conventional power systems with a diesel engine as a prime mover, and proper alternatives is done. Finally, it is found that electrification of short-sea shipping sector is recognized as a promising option to reduce environmental footprint and operative costs of the ship over its lifetime.
Climate change and depletion of fossil fuel are two of the major global challenges calling for urgent actions. Localised generation of renewable energy such as wind power has been adopted by farms as an effort for decarbonisation. It is important to develop the capability to accurately predict wind power generation featured by intermittence and fluctuation so that optimal renewable development plans can be formulated. In this work, the Autoregressive Distributed Lag modelling approach was employed to study the influences of economic and environmental factors (pressure, wind speed, temperature, and electricity price) on wind power generation on a Scottish farm. The proposed Autoregressive Distributed Lag model well explain the wind power generation with an accuracy of 91.8%. The results showed that when wind speed increases by 1%, the wind power output increases by 0.256% in the long run. We forecasted a total wind generation capacity of 1894.9 MWh from September 2020 to September 2021 based empirical environmental and economic data. In this case, the annual carbon emission of on-farm wind power usage was estimated to be 5.3664 tonnes. The on-farm wind power generation would reduce the electricity-related carbon emission by 278.87 tons over the 13 months.
Proper energy storage system design is important for performance improvements in solar power shared building communities. Existing studies have developed various design methods for sizing the distributed batteries and shared batteries. For sizing the distributed batteries, most of the design methods are based on single building energy mismatch, but they neglect the potentials of energy sharing in reducing battery capacity, thereby easily causing battery oversizing problem. For sizing the shared batteries, the existing design methods are based on a community aggregated energy mismatch, which may avoid battery oversizing but cause another severe problem, i.e., excessive electricity losses in the sharing process caused by the long-distance power transmissions. Therefore, this study proposes a hierarchical design method of distributed batteries in solar power shared building communities, with the purpose of reducing the battery capacity and minimizing the energy loss in the sharing process. Case studies on a building community show that compared with an existing design method, the proposed design can significantly reduce the battery capacity and electricity loss in the sharing process, i.e. 36.6% capacity reduction and 55% electricity loss reduction. The proposed method is helpful to improve the cost-effectiveness and energy efficiency of energy storage systems in solar power shared building communities.
Based on the investigation of a hospital in Beijing, it is found that the clean air conditioning system of the operation department consumes a large amount of energy per unit area, and the energy consumption of the air conditioning unit is relatively high in winter than in summer. The energy consumption simulation software was used to build the model. After verification, the model is used to simulate and analyze different working conditions based on the requirements of Chinese standards. The results show that the energy consumption of the surgical department is relatively high, and the new standard in China can save 16% compared with the current energy consumption of the surgical department. China’s new standard saves 10 percent of energy compared with the old one. This verified energy consumption benchmark model combined with national standards provides ideas for energy consumption quota.
As a major strategic technology for reducing greenhouse gas emissions and ensuring energy security, carbon capture, utilization, and storage (CCUS) is of great significance to large-scale emission reduction. Most previous CCUS studies have focused on technological implementation, application prospect, and economic analysis. From the perspective of knowledge discovery, it is important to explore the study progress based on existing study achievements, evolution characteristics of study topics over time, and stage-specific findings. This will help researchers gain an overall understanding of CCUS studies and serve to develop an academic study community of CCUS, as well as promote the industry-college-research cooperation in respect to CCUS. Based on the Web of Science (WOS) database platform, the present study conducts a literature review of international CCUS studies from 1989 to 2018 using the bibliometric method. Through the software CitNet-Explorer, this study identifies the core study topics in the CCUS field and explores the evolutionary trends and characteristics of the topics, using visual and cluster analysis methods. According to the H-index-based citation network, this study could track six hot modules within the CCUS field. Consequently, the cutting-edge trends of CCUS studies were predicted.
This study proposes a novel ammonia-water power and cooling cogeneration system in which an extraction Rankine cycle is introduced to drive the absorption refrigeration cycle to produce cooling and power simultaneously. The system mathematical model is established and the thermodynamic analysis is carried out to investigate the influence of key thermodynamic design parameters on system performance. Under design conditions, the cooling and power output are calculated to be 78.17 kW and 104.56 kW, and the thermal efficiency and exergy efficiency are equal to 21.81% and 43.69%, respectively. The parameter analysis results show that as boiler temperature rises, the system total output increases significantly, but the exergy efficiency and the thermal efficiency exhibit no significant changes. The results also show that an increase of circulating high pressure will lead to a decrease of system total output, and thus the thermal efficiency and exergy efficiency are decreased.
This study develops hybrid renewable energy systems for applications in zero-energy buildings and their community integrated with stationary battery storage and mobile hydrogen vehicles following different cruise schedules. The educational, office and residential building groups in Hong Kong are selected for zero-energy building case studies based on on-site collected energy consumption data and simulated load data as per local surveys and codes. And a zero-energy community integrating the three building groups is also developed for comparison to evaluate the supply, load cover, storage efficiency, grid integration, system cost and carbon emission indicators. The study results indicate that the renewable energy self-consumption ratio of four zero-energy scenarios varies between 88.10% – 96.01%. The community microgrid performs best in the load cover ratio of 74.96% with shared renewables and storages and achieves positive grid integration performance with a peak-to-average power ratio of 7.65 due to the complementary load characteristics of three building groups. The hydrogen storage efficiency of four zero-energy building scenarios varies between 37.42% – 55.62%. The levelized cost of energy of hybrid systems applied in four zero-energy scenarios varies within 0.48 – 0.63 US$/kWh, and it can be reduced to 0.09 – 0.24 US$/kWh considering the local feed-in tariff. The CO2 emission of the zero-energy community is about 13631.82 tons, higher than the sum of three buildings by 4.32%, as its power exchange with the utility grid is reduced for more renewable energy self-consumption with higher energy losses. The detailed techno-economic-environmental feasibility analysis offers valuable references for relevant stakeholders to develop renewables applications in zero-energy building communities of urban areas.
The growing capacity of gas-fired generating units has intensified the interaction between the electricity and gas systems. Though a more flexible operation can be achieved by integration, it also raises a serious issue on managing contingencies when some of the components in the integrated electricity and gas systems (IEGS) fail during the operation. This paper proposes a contingency management scheme in the IEGS considering the influence of the gas flow dynamics. Firstly, the partial derivative equations which describe the continuity and motion of gas flow are discretized using the finite-difference scheme. A second-order cone reformulation of the discretized equations is then proposed. Moreover, the optimal load shedding problem during the contingency state of the IEGS is formulated and then solved. Finally, 24-bus IEEE Reliability Test System and Belgium natural gas transmission system are used to validate the proposed technique.