Experimental Study on Hybrid Organic Phase Change Materials Used for Solar Energy Storage

The solar energy utilization in built environment has been limited due to its low heat flux, uneven distribution in time and space and temporal difference in day and night. The phase change materials have been used to collect the fluctuant solar energy to form a stable energy source for the terminal equipment of the buildings. In this study, the hybrid organic phase change materials was prepared for the capillary radiant heating system which formed a cascade utilization of solar energy. Firstly, lauric acid and stearic acid were selected as the basic organic phase change materials and the binary equilibrium phase diagram was completed based on the method of step cooling curve according to the experimental tests data. The results showed that the phase transition temperature of the mixed acid at the lowest eutectic point was 31.2℃ and the latent heat value was 264.3 kJ/kg when the mass mixing ratio was 70% for lauric acid and 30% for stearic acid. Secondly, the expanded graphite was used as an additive to enwrap the mixed acid and enhance the heat conductivity. The experimental results showed that when the mass proportion of expanded graphite in the mixed acid was 10%, the mixed acid could be completely enclosed by expanded graphite and the stability of melting and solidification was optimal. Additionally, the phase transition temperature of the hybrid phase change material was 31.5℃ and the latent heat value was 217.4 kJ/kg. The novel hybrid phase change material has a lower eutectic point and a higher latent heat of phase change, so it has a large application space and is quite suitable for the cascade utilization of solar energy with capillary network heating system.     

Multi-objective optimal allocation strategy for the energy internet in Huangpu District,Guangzhou, China

To improve the overall efficiency of the energy system, the basic structure for the energy internet of coordination and optimization of “generation-grid-load-storage” of Huangpu District, Guangzhou, China is designed, while the arrangement for the output of centralized and distributed energy module and energy storage are proposed. Taking economic benefit maximization, environmental benefit maximization and energy efficiency maximization as sub-objectives, the mathematical model of multi-objective optimal allocation and operation strategy of the energy internet is established considering supply-demand balance constraints, equipment characteristic constraints, operation mode constraints, and energy conditions constraints. The calculation results show that without considering the outsourced electricity, the balanced strategy, the economic development strategy, the environmental protection strategy, and the energy efficiency strategy are obtained by calculation, which are all superior to the traditional energy supply strategy. Moreover, considering the outsourced electricity, the proportion of outsourced electricity to total electricity is 19.8%, which is the system optimization of the energy internet under certain power demand. Compared with other strategies without outsourced electricity, the outsourced electricity strategy can have a certain emission reduction effect, but at the same time reduce the economic benefit. Furthermore, the huge difference in demand for thermal and cooling load between industrial and commercial areas results in the installed capacity of gas distributed energy stations in industrial areas being nearly twice as large as that in commercial areas. The distributed photovoltaic power generation is allocated according to the proportion of the installed roof areas of photovoltaic power generation system in residential, industrial, and commercial areas.     

A values–beliefs–attitude model of local food consumption: An empirical study in China and Denmark

Consumers’ and policy makers’ interest in local foods is growing. Accordingly, researchers are also increasingly paying attention to the consumption of local foods. Studies have identified preference for local foods as an emergent consumer ideology called “locavorism”, but they have not yet addressed its antecedents or put it into a theoretical context. In addition, extant research provides several insights into local food buying behaviour in developed economies (e.g., USA, UK, Germany, or Italy); however, studies simultaneously conducted in developed and emerging economies are lacking. To address these research gaps, this study develops a conceptual framework with proposed relationships among values, beliefs (locavorism and fresh start mindset), and attitudes towards and intentions to purchase local foods in China and Denmark. We conducted an online survey in China and Denmark that evaluated our constructs with pre-developed multiple-item measures. Using structural equation modelling to test the integrated model, we find that values and long-term orientation are antecedents of consumer beliefs but the influences of values on consumer beliefs differ between collectivistic-dominated China and individualistic-dominated Denmark. Specifically, collectivistic values are significantly and positively related to locavorism in both countries, while individualistic values are strongly linked to locavorism only in Denmark; collectivistic values have no effects on fresh start mindset for the two samples, but individualistic values are significantly and positively related to a fresh start mindset in Denmark. In addition, consumer beliefs are significantly and positively associated with attitudes towards and intentions to buy local foods. Local food marketers can use our findings to target their communications more effectively.     

柠檬酸铋合成新工艺研究

针对现有柠檬酸铋制备工艺合成时间长、能耗高、产品纯度不高等不足,介绍了一种常温下制备柠檬酸铋的新工艺。新工艺制备时间短,制备的柠檬酸铋产品质量好,合成过程产生的废水可循环利用,废气经碱液循环吸收可生产硝酸钠副产品。     

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources (RESs) are considered to be reliable and green electric power generation sources. Photovoltaics (PVs) and wind turbines (WTs) are used to provide electricity in remote areas. Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment. The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution. This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization (TLBO) named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost (TAC). The reliability of the system is considered by a maximum allowable loss of power supply probability (LPSP_max) concept. The results obtained from the JLBO algorithm are compared with the original Jaya, TLBO, and genetic algorithms. The JLBO results show superior performance in terms of TAC, and the PV–WT–battery hybrid system is found to be the most economical scenario. This system provides a cost-effective solution for all proposed LPSP_max values as compared with PV–battery and WT–battery systems.     

Modeling and design of 3-D MPPT for ultra low power RF energy harvesters

Radio-Frequency (RF) energy harvesting must cope with the limited availability and high variability of the energy source. In this paper, the modeling of an RF harvester for ultra low power environments is presented. A mathematical model based on theoretical analysis is developed. The model demonstrates that the maximum transferred power point is located in a three-dimensional space defined by the input capacitance, the output voltage, and the load resistance of the rectifier circuit. Moreover, the mathematical model returns results in substantial agreement with the SPICE simulation results, while guaranteeing a remarkable reduction of the required computation time. Furthermore, the paper reports the implementation of a mixed signal system for the 3-D MPPT, to be embedded in an RF harvester, in a 65 nm CMOS technology. The circuit exhibits a simulated power consumption lower than 100 nW, making this solution suitable for ultra low power harvesting.     

异质性环境规制对绿色全要素生产率的影响机制——基于能源消费结构的调节作用

为探讨能源消费结构调节下异质性环境规制对绿色全要素生产率的影响机制，论文利用SBM方向距离函数测得全国各省市“经济-资源-环境-社会”四位一体的绿色全要素生产率，并将环境规制工具分为命令控制型、经济激励型、治理投入型和公众参与型4类，构建了空间杜宾模型以及门槛效应模型，进而得出在能源消费结构调节下，异质性环境规制对绿色全要素生产率的直接作用、间接作用以及空间溢出效应。研究结果表明：1）经济激励型和公众参与型环境规制通过调节能源消费结构对当地和邻地的绿色全要素生产率产生影响；2）在门槛检验方面，能源消费结构对命令控制型、经济激励型和公众参与型环境规制影响绿色全要素生产率存在门槛效应，同时在能源消费结构调节下，命令控制型和经济激励型环境规制对其本身对绿色全要素生产率的间接作用存在门槛效应。建议政府在制定环境规制时要考虑到其与能源消费结构的交互作用，并且在不同能源消费水平地区采用适宜的规制方法和强度，以更好地发挥环境规制作用。     

铅锌多金属矿分段浓缩选别技术的研究与应用

通过多碎细磨、原矿分级溢流优先浓缩脱水,进行了高浓度选铅银、选锌,锌尾矿再浓缩脱水选硫、选锰,同时匹配合理的选矿药剂,原矿浓缩水回用于磨矿分级和选铅,锌尾浓缩水回用于选锌,尾矿浓缩水回用于选硫、选锰,剩余各种废水经适度处理回用于选铅和磨矿分级等,使一段磨矿细度-74μm从70%提高到80%,铅、锌、硫入选初始浓度分别提高到50%、40%、50%,选矿废水全部分质回用。铅锌硫银回收率分别提高了1.5、2.83、13.57、1.01个百分点,硫精矿主品位从38.9%提高到46.5%,设备减少40%、能耗降低25%,节约了选矿药剂消耗和废水处理费用,实现了铅锌多金属矿产资源的高效回收和节能环保。     

Catalytic oxidative desulfurization of gasoline using phosphotungstic acid supported on MWW zeolite

Catalysts for the desulfurization of gasoline samples were synthesized via the immobilization of well-dispersed phosphotungstic acid (HPW) on Mobil composition of matter-twenty-two (MWW) zeolite. Characterization results indicated that these catalysts possess a mesoporous structure with the retention of the Keggin structure of immobilized HPW. Relevant reaction parameters influencing sulfur removal were systematically investigated, including HPW loading, catalyst dosage, temperature, initial S-concentration, molar ratio of oxidant to sulfide (O/S), volume ratio of MeCN to model oil (Ext./oil), and sulfide species. The 40 wt-% HPW/MWW catalyst exhibited the highest catalytic activity with 99.6% dibenzothiophene sulfur removal from prepared samples. The 40 wt-% HPW/MWW catalyst was recycled four times and could be easily regenerated. Finally, as an exploratory study, straight-run-gasoline and fluid catalytic cracking gasoline were employed to accurately evaluate the desulfurization performance of 40 wt-% HPW/MWW. Our research provides new insights into the development and application of catalysts for desulfurization of gasoline.     

A small-scale silica gel-water adsorption system for domestic air conditioning and water heating by the recovery of solar energy

A small-scale silica gel-water adsorption system with modular adsorber, which utilizes solar energy to achieve the cogeneration of domestic air conditioning and water heating effect, is proposed and investigated in this paper. A heat recovery process between two adsorbers and a mass recovery process between two evaporators are adopted to improve the overall cooling and heating performance. First, the adsorption system is tested under different modes (different mass recovery, heat recovery, and cogeneration time) to determine the optimal operating conditions. Then, the cogeneration performance of domestic cooling and water heating effect is studied at different heat transfer fluid temperatures. The results show that the optimal time for cogeneration, mass recovery, and heat recovery are 600 s, 40 s, and 40 s, respectively. When the inlet temperature of hot water is around 85°C, the largest cooling power and heating power are 8.25 kW and 21.94 kW, respectively. Under the condition of cooling water temperature of 35°C, the obtained maximum COP_c, COP_h, and SCP of the system are 0.59, 1.39, and 184.5 W/kg, respectively.