Abstract

Thermoelectric generator (TEG) and organic Rankine cycle (ORC) are both promising waste heat recovery technologies, which have different advantages and disadvantages in operating temperature, size and efficiency. A combination of TEG and ORC systems forming a TEG-ORC system has the possibility to complement each other achieving a win-win situation. The paper proposes a combined TEG-ORC system applied in passenger cars for both waste heat recovery and engine warm-up. This bifunctional TEG-ORC system has a novel layout utilizing components that already exist in a passenger car to reduce the size of system. To evaluate the performance of TEG-ORC, a semi-empirical model is developed. The fuel saving potential of the vehicular TEG-ORC system along the world light vehicle test procedure (WLTP) is estimated. The results indicate that 0.13% and 3.19 % of fuel saving potential are respectively achieved in the fast engine warm-up and waste heat recovery compared to the baseline vehicle without the TEG-ORC system.

Abstract

Beijing has a complex urban water system with multiple water sources including transfer water from the South-North Water Transfer Project (SNWDP), reclaimed water, surface water, and groundwater, which needs a large number of electricity consumptions. Due to the spatial differences of multiple water sources, especially for the Nine stage pumping station of SNWDP, the spatial distribution of electricity consumption of the urban water system should be considered. This study established a spatial urban water-energy nexus framework for exploring electricity consumption of the urban water system including water collection, water consumption, and wastewater treatment. And then a spatial autocorrelation model is applied to explore the hot-spot areas of water-related electricity consumption. We select the year 2018 as an example to show the spatial characteristics of urban water-energy nexus in Beijing. The results showed that: (1) Electricity consumption of pumping stations of SNWDP in southwestern, northern and northeastern parts accounted for their 96.30%, 96.27% and 74.39% of the water-collection related total energy consumption; (2) High water-related energy consumption mainly gathers in central parts of Beijing with high urban density. And there are several high areas of water-related energy consumptions located in southwestern, northern and northeastern of Beijing where has have been built high-level pumping stations of SNWDP; (3) The hot-spot areas of water-related electricity consumption are distributed in the central parts, and northeastern of Beijing, where should be carefully considered to develop more urban electricity infrastructure to support water-related energy supply.

Abstract

The dynamic nature of manufacturing production environments, along with numerous machines, their unique activity states, and mutual interactions render challenges to energy monitoring at a machine level. To this aim, a machine learning framework is presented, to predict the machine-specific load profiles via energy disaggregation, and these machine-specific load profiles are in turn used to predict the machine’s activity state as well as their respective production capacities. Various supervised machine learning algorithms such as GBDT, XGBoost, LightGBM, LSTM and BLSTM were evaluated on their capacities to predict load profiles and production capacities of four machines investigated in this study. LightGBM and EnBLSTM were identified as the respective best performing algorithms with an average MAE and RMSE of 0.035 and 0.105 for disaggregation studies and 1.64 and 11.41 for production capacity estimation. Four unsupervised machine learning algorithms, namely K-means, minibatch K-means, HMM and GMM were evaluated to cluster the machines activity states from their disaggregated load, where the GMM algorithm had a superior performance with the V score and Fowlkes-Mallows index of 0.85 and 0.98, respectively. The framework and methodology developed in this study are purely data-driven, cross-deployable and serve as promising catalyst to foster smart energy management practices and sustainable productions in the manufacturing industry.

Abstract

Micro grid (MG) is defined as a small-scale power supply network with a group of distributed energy resources and could connect with outer electric power grid, when utilizing MG to satisfy the load demand of user, two important objectives: economic operation cost and environmental pollution emission, should be taken into consideration. In this paper, two operations: Demand Response (DR) and Energy Storage (ES) are introduced into MG system to reduce the operation cost and pollution emission. A multi-objective optimization model of MG operation is built and a hybrid Multi-Objective Particle Swarm Optimization (MOPSO) is presented to minimize operation cost and pollution emission simultaneously. Besides, since the uncertainty of load demand and Renewable Energy Source (RES) power generation, power supply service level of MG is utilized to ensure the power supply balance between MG and user. Moreover, a stochastic sampling method, termed as Monte-Carlo simulation, is combined with MOPSO to ensure the required service level could be satisfied by obtained power supply solution. The simulation results show that introduced DR and ES operation could reduce operation cost and pollution emission of MG efficiently. Moreover, under different uncertainty of RES power generation and load demand, compared with original MG operation without DR and ES, the stability of solutions obtained by proposed DR and ES operation, refers to the both robustness of operation cost and pollution emission, could be improved well. Finally, sensitivity analysis of different DR policies with virous incentive price and user acceptance are analyzed for providing decision support for manager of MG.

Abstract

With the urbanization, the dairy farming system is undergoing industrialization to meet the growing demand for dairy products. Industrial farms have been reported to increase milk production per unit area because of the high breeding density and improve feed use efficiency of dairy cow, which may reduce the environmental impact intensities, such as non-CO2 emission in producing one unit of milk. However, industrialization also increases the energy input due to the use of mechanized equipment and thus increases CO2 emission. Anaerobic digestion of cow manure to produce biogas and using the digestate to produce bioenergy crops are cleaner ways for fossil energy saving. In this study, by combining field survey, model simulation and scenario analysis, we calculated the mitigation potentials of fossil energy consumption and CO2 emission in milk production using bioenergy production technologies in an average-sized industrial dairy farm, compared with milk production without bioenergy production technologies. Then, we estimated the manure excretion and CO2 equivalent emissions released from manure management from China’s dairy farming systems in 2017, and calculated the mitigation potential of CO2 emission if all dairy cow manure were treated by biogas fermentation plus waste nitrogen for bioenergy crops production. The cost-benefit of manure management with bioenergy production technologies was also analyzed to explore the economic potential of the manure management with bioenergy production technologies.

Abstract

Hg0 emission from coal-fired flue gas has become a great public concern due to its hazards for human health and ecosystem. The wet oxidation has received wide attention in the removal of Hg0 because of its low cost and synergy with other processes. A series of oxidants (KMnO4, H2O2, NaClO2, NaClO, K2S2O8 and, K2FeO4) were selected in this study to remove Hg0 from simulated flue gas in a packed tower, and the composite oxidant NaClO/NaClO2 showed a better removal efficiency. Thermodynamic analysis on Hg0 removal with composite oxidants was carried out, and experimental results indicated that the removal efficiency reached 94% at the reaction temperature of 50 °C. The physicochemical characteristics of solid products were studied through SEM (scanning electron microscopy) and XRD (X-ray diffraction), and the amount of mercury was detected by AAS (atomic absorption spectrophotometry). Results showed that 23% of Hg0 was oxidized and transferred into the gypsum in the form of compounds, while 77% was oxidized into Hg2 in the absorption solution. The findings of this research might provide a practical reference for promoting the removal of Hg0 from coal fired flue gas by NaClO/NaClO2 with limestone in industrial application.

Abstract

The development status of the ship’s shore power system and shore power insulation system and the research status of insulation monitoring technology are described. The use of external DC power injection to monitor the insulation performance of the shore power system is studied. In order to quickly find the point of insulation reduction, the problem of selecting the line of multiple power supply branches of the shore power system is studied. In order to further accurately determine the fault point, a comprehensive insulation monitoring and line selection and phase selection scheme for ship shore power systems based on additional injection signals, comparison of branch zero sequence currents, and comparison of branch relative to ground voltage is proposed, which solves the problem of ITN-powered ship shore power System insulation monitoring problem.

Abstract

Although urbanization should be an integrated process of rural-to-urban transformation involving the interactions and mutual influences between population urbanization and land urbanization, its definition in such multi-dimensioned terms is as yet underexplored. This is an important issue for the relationship between urbanization and carbon emissions, as the fuzzy definition of urbanization may have contributed to the neglect of the mechanisms involved, with misleading low-carbon policy implications and misguidance for achieving 2030 carbon emission peak goals. This study is one of the first attempts to disaggregate the urbanization nexus and simultaneously explore the correlation between land urbanization and population urbanization, and carbon emissions across China.
The findings suggest that land urbanization and population urbanization both have an inverted U-shaped correlation with carbon emissions, and a U-shaped relationship with carbon productivity. These results support the environmental Kuznets curve, in that urbanization helps mitigate carbon dioxide emissions in the long run depending on urbanization performance. However, unlike western countries, the triple restrictions of land policy, fiscal and taxation policies, and the household registration system, as well as the disconnection between urbanization and industrial development in China will result in the asynchrony of land urbanization and population urbanization. The results also point to a considerable but differentiated potential for urbanization to reduce GHG emissions through effective urbanization management and policy adjustment, and that low-carbon policies and strategies need to be tailor-made based on regional differentiations.

Abstract

The fuel efficiency are related to the engine temperature. The total fuel consumption of a warmed-up engine is less than that of the cold-start engine for the same driving cycle. Hybrid electric vehicle (HEV) allows the motor to work during the engine warming-up process. Optimizing torque distribution ratio can help reduce engine fuel consumption of the warm-up process. The traditional energy management strategy, which does not consider the engine temperature, is designed for a warmed-up engine. In this paper, an energy management strategy with considering engine warming-up is formulated.

Abstract

Hydrogen fuel cell vehicle (HFCV) are recognized to have the potential to reduce fossil fuel dependence and CO2 emissions. Japanese government has included the promotion of HFCV adoption as a part of national economic development agenda. As Tokyo has an important demonstration role as the capital, its progress in the popularization of HFCV deserves more attention. However, the metropolitan area surrounding Tokyo has differences in population distribution, economic development, facility construction, and cultural needs. In addition, due to the initial stage of HFCV promotion, the distribution of support facilities and situation of subsidy policy varies between districts. Therefore, different factors and barriers influence the willingness of customers to accept HFCVs in Tokyo. Recognizing the differences will benefit the future facility planning and policy formulation of HFCV promotion.
Analytic hierarchy process (AHP) and field surveys are employed in this study to propose a group of factors that may affect customers’ preferences on HFCV, and to prioritize them and identify the critical ones. It indicates that fuel availability, economic costs, vehicle performance, environmental friendliness, policy support and social condition are the most important 6 dimensions in affecting customers’ attitude towards HFCV. The lower-level factors of each dimension also identify the most critical ones through AHP: the fuel availability is mainly determined by the number of hydrogen refueling stations. The economic cost is mainly affected by the affordability of consumers. The vehicle performance is mainly restricted by the distance travelled by the car. Policy support is mainly reflected in the amount of subsidies. Social conditions are determined by the number of 4S shops is determined. This study uses GPS data via mobile phone users to discover individual travel behavior and accurately calculate the distance travelled by car. Other data can be obtained from industrial reports and government planning information. Therefore, the 6 dimensions can be evaluated by the corresponding lower-level factors. Furthermore, the distribution of the 6 dimensions in each district is figured out by Pareto Analysis to reflect the adoption potential.
The results show that the districts with high adoption potential for hydrogen fuel cell vehicles are mainly areas with low public transport dependence, high income levels, and well-planned corresponding facilities, such as Minato-Ku and Koto-Ku. According to the results, some policy implications are proposed from the prospective of improving and demonstrating government leading HFCV facility construction and operation, and costs reductions.