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Cu2CdSn(S,Se)(4) is an important candidate material for thin film solar cell absorber layers. In this work, low-cost Cu2CdSnS4 nanocrytal thin film with a stannite structure has been successfully fabricated by a butyldithiocarbamate-based ethanol solution approach. The selenized Cu2CdSn(S,Se)(4) thin film shows large densely packed grains and has a suitable band gap value of 1.01 eV. The Cu2CdSn(S,Se)(4) thin film solar cell with a proof-of-concept power conversion efficiency of 3.1% was fabricated. (C) 2014 Elsevier B.V. All rights reserved.

Robust mitigation options will play significant role in achieving the target of limiting global change to below 1.5 °C above pre-industrial levels by 2100. To support cooperation for mitigation development, we establish a real options-based model to evaluate the rational decisions of exercising the abandon option for carbon capture and storage-enhanced oil recovery (CCS-EOR) projects under oil market and geological uncertainties. Three possible cooperative mechanisms (fixed carbon dioxide (CO2) price, oil-indexed CO2 price, and joint venture contracts) among CO2-EOR stakeholders are evaluated. The results show that the conflicts in profit maximization targets for different stakeholders in cooperative mitigation are to a great extent unable to be avoided. A joint venture business model is preferred in cooperative mitigation as it can effectively weaken such conflicts. And it is more reasonable to provide incentives to the downstream of the CO2-EOR chain than compensating the adoption cost of carbon capture technologies in the upstream. From a global perspective, the inefficient cooperation can be a main barrier that hinders the development of deep-cutting options. Global mitigation strategies should not only focus on promoting technology progress but also the design of innovative business models to balance the benefits among stakeholders. A joint venture business model is recommended in both the developed and developing countries for seizing the early mitigation opportunities.

Abstract In this paper, a finned heat pipe assisted passive heat sink based on a newly emerging high performance phase change material (PCM), the low melting point metal (LMPM), was developed for thermal buffering of high power electronics which works intermittently with heat generation rate up to 1000 W (10 W/cm2). Firstly, thermal performances of the PCM heat sink under different thermal shocks (from 200 W to 1000 W) were experimentally evaluated, in comparison with that of an organic PCM which has similar melting point. It was found that, the former one can prolong the working duration 1.4–2.4 times that of the latter one. Then, the performance of the heat sink was improved through reducing the contact thermal resistance and by increasing the fin number. Furtherly, an air cooling radiator was configured to accelerate the solidification process of the PCM module, which makes it capable of maintaining its highest temperature below 85 °C under 1000 W periodic thermal shock (10 min on and 15 min off). Moreover, energy dispersive spectrometer (EDS) analysis was conducted to verify the compatibility of the LMPM PCM and the structural materials. Finally, a simplified numerical model was developed and validated for the currently constructed finned heat pipe assisted LMPM PCM heat sink, which can be much helpful for future practical thermal design and optimization of this kind of thermal buffering module.

Abstract The mesophase pitch derived graphite foams with low bulk density (L-GF) and high bulk density (H-GF) were spontaneously infiltrated by erythritol to prepare graphite foam/erythritol (GF/erythritol) phase change materials (PCMs) with ultrahigh thermal conductivity for medium temperature thermal energy storage applications. Results of thermophysical properties indicated that thermal diffusivity of the GF/erythritol PCMs can be enhanced by 66 and 117 times as compared with that of pristine erythritol in solid (0.36 mm2/s). This enhancement resulting from three-dimensional ordered network of graphite foam can significantly reduce the charging and discharging time of the PCM storage system. Although H-GF as a matrix can obtain a higher thermal conductivity (68.71 W/(m·K)) than L-GF (40.52 W/(m·K)), the smaller porosity cannot allow more erythritol to be absorbed, and its melting enthalpy (178.4 J/g) is lower than L-GF (266.6 J/g). In addition, the enhancement of thermal conductivity and the increase of interfacial surface area caused by graphite foam structure strongly suppresses the supercooling of erythritol, which can be reduced from 86.0 °C to 53.2 °C. The obtained results demonstrated that the GF/erythritol PCM as a stable PCM is a promising material for medium temperature thermal energy storage applications.

Abstract Algae have been considered as a promising biodiesel feedstock. One of the major factors affecting large-scale algae technology application is poor wintering cultivation performance. In this study, an integrated approach is investigated combining freshwater microalgae Chlorella zofingiensis wintering cultivation in pilot-scale photobioreactors with artificial wastewater treatment. Mixotrophic culture with the addition of acetic acid (pH-regulation group) and autotrophic culture (control group) were designed, and the characteristics of algal growth, lipid and biodiesel production, and nitrogen and phosphate removal were examined. The results showed that, by using acetic acid three times per day to regulate pH at between 6.8 and 7.2, the total nitrogen (TN) and total phosphate (TP) removal could be increased from 45.2% to 73.5% and from 92.2% to 100%, respectively. Higher biomass productivity of 66.94 mg L−1 day−1 with specific growth rate of 0.260 day−1 was achieved in the pH-regulation group. The lipid content was much higher when using acetic acid to regulate pH, and the relative lipid productivity reached 37.48 mg L−1 day−1. The biodiesel yield in the pH-regulated group was 19.44% of dry weight, with 16–18 carbons as the most abundant composition for fatty acid methyl esters. The findings of the study prove that pH adjustment using acetic acid is efficient in cultivating C. zofingiensis in wastewater in winter for biodiesel production and nutrient reduction.

Abstract Based on the design concept of a fourth-generation smart pipe network system, this paper innovatively proposes a new TOTS (Two-supply/One-return, triple pipe structure) arrangement method for district heating systems. Moreover, to accurately predict the heat loss due to the pipeline operation of the multi-pipe system, based on the multipole calculation method, a new heat loss theoretical analytical model for the TOTS was created; additionally, a corresponding three-dimensional numerical simulation model was established, which was analyzed and numerically solved. The results showed that in comparison with thermal loss data measured by Danfoss et al., the above analytical and numerical models have a high accuracy, and the deviation is within 2%. Additionally, through calculations, it was found that the distance between the heating pipes is an important factor that affects the total heat loss from the new multi-control heating system and the actual heat exchange between pipes.

Abstract In order to maximize the operation profit while maintaining the service quality, an effective energy management scheme is highly needed for the Photovoltaic-assisted Charging Station (PVCS). Considering the uncertainty of Electric Vehicle (EV) charging demand and PV power output, it will be challenging to determine the charging power for EVs to make informed real-time decisions. In this study, an online energy management method leveraging both offline optimization and online learning is proposed. In order to maximize the self-consumption of Photovoltaic (PV) energy and decide the power supplied from the power grid with Time-of-Use (TOU) pricing, here online learning is coupled with the rule-based decision-making to obtain a real-time online algorithm. The knowledge base for online learning is derived and updated from the results of offline optimization after every operation day. The PVCS located at workplace parking lots is used as an example to test the proposed method. The simulation results show that the method can be implemented without the information on future PV power and charging demand. The obtained results are close to the optimal results from offline optimization.

Abstract Nowadays, lithium-ion battery (LIB) technology provides one of the most important approaches for large-scale electricity storage. In this work, an electrical-thermal-fluidic coupled model is proposed for practical LIB-based energy storage systems (ESSs). The coupled model is established based on the equivalent circuit model (ECM) which describes electrical behavior of LIBs, the airflow turbulent model, and the “single domain of multiple sub-regions” thermal model. Currents and voltages of LIB cells, airflow velocity field and pressure field, and temperature distribution in the whole ESS, can be simulated by the developed full-scale model. Simulation results of a practical commercial LIB ESS (1 MW/2 MWh) in typical frequency regulation operation, including electrical-thermal characteristics represented by currents and heat generation rates of LIBs in the ESS, flow characteristics represented by airflow field and mass flow rate distribution, ambient temperature sensitivity analysis represented by temperature distributions of the ESS initially under 27℃ and 38℃ ambient respectively, are displayed and discussed, exhibiting the capability of the proposed model. The proposed model has been validated by comparing the simulated results with the actual measured data; the reasonably good agreement demonstrates the effectiveness of the proposed model. Therefore, the established model has the potential to provide a feasible and powerful approach or tool to perform multi-physics simulations of practical large-scale LIB ESSs for different functions, including but not limited to detailed temperature evaluations, cooling structure optimization, materials selection, and thermal-safety status evaluating and monitoring.

For power generation management and power system dispatching, it is of big significance to predict the consumption of electric energy accurately. For the sake of improving the prediction accuracy of power consumption, taking the complex features of time series data into consideration, a novel neural network sandwich structure with an improved attention mechanism is inserted into the double-layer bidirectional long short-term memory network shortened as A-DBLSTM is put forward in this article. In A-DBLSTM, compared with traditional attention mechanism, the presented attention mechanism focuses on different features in each time unit and the A-DBLLSTM network extracts time information in sequence. The parameter optimization of A-DBLSTM is based on the method of particle swarm optimization (PSO). For confirming the effectiveness and feasibility of A-DBLSTM, case studies using two datasets of the hourly temperature values and power loads between 2012 and 2014 and the electric energy consumption are carried out. The experimental results indicate that the presented A-DBLSTM with the novel sandwich network structure achieves superior performance in the aspects of the mean square error, root mean square, the average absolute error and the mean absolute percentage error to other advanced methods. What is more, the factors that have the greatest impact on the prediction performance can be found through analyzing the heatmap of the attention layer.