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Abstract Limiting the increase of global temperature requires electrification of the railway transport, which is relatively a distinct mode of transport in terms of economy, business and socialization of a country. However, battery complemented railway transport systems such as fuel cell hybrid railway propulsion systems are constrained by the high cost of the battery, and suboptimal performance of the fuel cell under varying loads. Optimized selection of battery can reduce its costs associated with sizing, life and utilization. Similarly, managing the load distribution between the battery and fuel cell can reduce the load variations concern for fuel cell. In this study, model-based selective characterization of the battery and fuel cell is done to identify the optimal features and constraints. Following characterization, the load allocation to battery and fuel cell is determined with the targets of collaborative utilization of optimal features and mitigation of constraints. Subsequently, considering this load allocation and results of characterization, conditions are proposed for reliable sizing and optimized selection of battery. The significance of the proposed conditions in reliable sizing is explored. Based on these conditions, certain commercially developed batteries are evaluated for optimized selection of battery. The results signify this study as a foundation for research on the reliable sizing and optimized selection of battery in fuel cell hybrid railway propulsion systems.

Plastic film mulching (FM) became a general practice to enhance crop productivity and its net primary production (NPP), but it can increase greenhouse gas (GHG) emissions. The proper addition of organic amendments might effectively decrease the impact of FM on global warming. To evaluate the feasibility of biomass addition on decreasing this negative influence, cover crop biomass as a green manure was incorporated with different recycling levels (0-100% of aboveground biomass) under FM and no-mulching. The net global warming potential (GWP) which integrated with soil C stock change and GHG (N2O and CH4) fluxes with CO2-equivalent was evaluated during maize cultivation. Under the same biomass incorporation, FM significantly enhanced the grain productivity and NPP of maize by 22-61 and 18-58% over no-mulching, respectively. In contrast, FM also highly increased the respired C loss, which was 11-95% higher than NPP increase, over no-mulching. Irrespective with biomass recycling ratio and mulching system, negative NECB which indicates the decrease of soil C stock was observed, mainly due to big harvest removal. FM decreased more soil C stock by 57-158% over no-mulching, but its C stock was clearly increased with increasing biomass addition. FM significantly increased total N2O and CH4 fluxes by 4-61 and 140-600% over no-mulching, respectively. Soil C stock changes mainly decided net GWP scale, but N2O and CH4 fluxes negligibly influenced. As a result, FM highly increased net GWP over no-mulching, while this net GWP was clearly decreased with increasing biomass application. However, cover cropping, and its biomass recycling was not enough to compensate the negative impact of FM on global warming. Therefore, more biomass incorporation might be essential to compensate this negative effect of FM.

The current status and challenges associated with the production and utilization of cellulosic ethanol in Korea are reviewed in this paper. Cellulosic ethanol has emerged as a promising option for mitigating Korea's CO(2) emissions and enhancing its energy security. Korea's limited biomass resources is the most critical barrier to achieving its implementation targets for cellulosic ethanol. Efforts to identify new suitable biomass resources for cellulosic ethanol production are ongoing and intensive. Aquatic biomasses including macroalgae and plantation wastes collected in the Southeast Asia region have been found to have great potential as feedstocks for the production of cellulosic ethanol. R&D explorations into the development of technologies that can convert biomass materials to ethanol more efficiently also are underway. It is expected that cellulosic ethanol will be in supply from 2020 and that, by 2030, its use will have effectively reduced Korea's total gasoline consumption by 10%.

Among various bioreactors examined in anaerobic digestion and dark fermentation, UASB bioreactor has shown to be a promising alternative. However, mass transfer resistance and biomass washout have been the issues that reported as draw backs of the granular system in the literature. Another problem associated with such a system is its long start-up period as a result of biomass washout and long microbial granulation stage. In this paper, the results obtained from an UASFF bioreactor in methane (AD process) and hydrogen (DF process) production from POME, are presented to assess mass transfer of substrate into the granules and also study the role of internal packing used in the middle part of reactor in the process stability. The value of effectiveness factor, η, for AD and DF processes were calculated to be 0.96 and 0.94, respectively, indicating that there was no mass transfer resistance due to internal and/or external factors. The results showed that the packing material could retain biomass in the reactor and had outstanding contribution in the granulation enhancement. Its role as a supplementing treatment stage was more significant at low HRTs and up-flow velocities.

Abstract We report all-polymer solar cells with new electron-accepting (n-type) polymer nanoparticles, poly(2,7-bis(4-hexylthiophen-2-yl)-9H-fluoren-9-one-co-benzothiadiazole) (BHTF-co-BT), which were in-situ generated during polymerization reaction. The size of the BHTF-co-BT nanoparticles was ca. 5–15 nm with a particular single X-ray diffraction peak (d-spacing=1.3 nm), indicative of a highly ordered crystalline state, while their glass transition temperature was ~140 °C. Their band gap energy and ionization potential were 1.8 eV and 5.7 eV, respectively. The possibility of the BHTF-co-BT nanoparticles as an electron acceptor for both normal-type and inverted-type all-polymer (polymer:polymer) solar cells was examined by employing poly(3-hexylthiophene) (P3HT) as an electron donor. The normal-type P3HT:BHTF-co-BT solar cells exhibited promising open circuit voltage ( V oc =0.67–0.73 V) and fill factor (FF=51.3%), while a three-fold improved short circuit current density and higher V oc (0.77 V) were achieved for their inverted-type solar cells.

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

Conventionally assessing of turbine performance was done by conducting model experiments which at times become costly and time consuming for several design alternatives in design optimization. Recently, computational fluid dynamics (CFD) has become a more cost effective tool for predicting detailed flow information in turbine space to enable the selection of the best design. With the growth of computational mechanics, the virtual hydraulic machines are becoming more and more realistic to get minor details of the flow, which are not possible in model testing. The inverse design technique and fully 3-dimensional flow simulations were performed early to manufacture the newly developed runner. It allows a quick and efficient improvement and optimization of turbine components. The system has been applied to the optimization of a Francis turbine runner for a turbine replacement project. In present work, 3D turbulent real flow analyses in hydraulic Francis turbine have been carried out at four guide vane opening at constant rotational speed using Ansys CFX computational fluid dynamics (CFD) software. The newly developed runner from reverse engineering and CFD results show an enhanced performance. The average values of flow parameters like velocities and flow angles at the inlet and outlet of runner, guide vane and stay vane of turbine are computed to derive flow characteristics. The aim was to analyze the flow behavior and pressure distribution to further fine-tune the whole numerical experiment to achieve the level of accuracy necessary for the concept design of a revitalized turbine. The obtained results are in good agreement with the in site experiments, especially for the characteristic curve.

Abstract In many visions and roadmaps, there is a broad agreement that fuel cells – both for stationary and mobile applications – are the key technology to allow the development of a hydrogen infrastructure. Furthermore, this development is generally thought to be based on a gradual, decentralised evolution. Nevertheless, in this paper it is argued that, taking into account the entire hydrogen chain (production, transport, storage, distribution and end-use), this decentralised fuel-cell based philosophy shows some serious flaws. Therefore, a new hydrogen-transition approach was pushed forward: mixing in of hydrogen into the natural-gas bulk. Using Flanders – the Northern part of Belgium – as a case study, the development of a transitory hydrogen infrastructure has been studied, taking into account the entire hydrogen chain and its dynamics, from production to end use. In a next step, this transition is being quantified. An optimisation model has been developed using Matlab and the commercial solvers GAMS and CPLEX. Following a mixed-integer linear-programming approach, this model is able to determine the economically optimal hydrogen-production mix and operational behaviour of each hydrogen-production plant separately. The model then allows gaining valuable insights in the importance of storage and the influence of fuel prices and carbon taxes with regard to the development of an early hydrogen economy.