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.     

汽蚀对离心泵性能影响的实验研究

离心泵长时间运转后,会出现危害严重的汽蚀现象,造成泵性能下降,严重时影响泵的效率、寿命,甚至造成离心泵内部部件损坏。文章通过改变进口压力的方法对单泵、双泵并联、双泵串联等工况下汽蚀对离心泵性能影响进行实验研究。结果表明:当进口压力小于输送液体的饱和蒸汽压时,液体开始发生气化并伴随气泡产生,表明泵内发生汽蚀;汽蚀初期离心泵的效率开始下降,但表现不明显;随着汽蚀不断增大至严重汽蚀区时,Q 1~η曲线出现陡坡,效率出现明显下降并伴随嗡响。实验证明采用提高泵的进口压力等措施可适当减小汽蚀对泵性能的不利影响。     

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。     

表面润湿性对梯形除雾器分离性能的影响

为解决实际工业中除雾器在高气速时分离效率明显降低的问题，利用除雾器分离实验装置，以水为实验介质，采用电火花线切割技术在叶片表面构建仿生微结构实现表面疏水化，考察了表面润湿性对除雾器分离效率和压降的影响。结果表明，仿生微结构的疏水功能和减阻效应良好，表面液膜的排液速率明显加快。当气速超过5 m/s时，其液膜厚度相对较薄，可有效抑制液滴的二次夹带，提升分离效率。同时，疏水型梯形除雾器内的流场分布较平缓，流动阻力小，总压降约为带钩型梯形除雾器的一半。因此，疏水型梯形除雾器兼具高效率和低阻力特性，综合分离性能最佳。     

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.     

基于α-FeOOH催化H2O2蒸气的低温烟气脱硝实验

针铁矿是分布广泛、储量丰富的铁氧化物，其主要成分为α-羟基氧化铁（α-FeOOH）。为了探究针铁矿在催化H₂O₂烟气脱硝反应中的性能，本文通过沉淀-水解法制备了α-FeOOH，并在自行搭建的实验台上开展了α-FeOOH催化H₂O₂的低温烟气脱硝实验研究，深入分析了H₂O₂流量、H₂O₂浓度、汽化温度、反应温度和共存气体浓度等工况参数对脱硝性能的影响。采用离子色谱（IC）分析了单独脱硝反应和同时脱硫脱硝反应后的含氧酸成分，结合各项表征分析技术考察了催化剂反应前后的理化特性和稳定性。实验结果显示，随着汽化温度和反应温度的升高，NO的脱除效率先增加后降低；增加H₂O₂浓度对脱硝效率有明显的促进作用。当汽化温度为140℃、反应温度为160℃时，以2.5mL/h注入10mol/L的H₂O₂脱硝效率达到80%。当SO₂浓度为1000μL/L时，脱硝效率提高至86.4%。离子色谱分析结果显示，单独脱硝反应和同时脱硫脱硝反应后含氧酸产物为HNO₃和H₂SO₄。反应前后催化剂的表征结果显示，α-FeOOH在脱硝反应后依然具有良好的稳定性，显示出针铁矿在低温烟气脱硝工艺中的潜在应用前景。     

安家岭储煤场输煤暗道通风除尘技术应用研究

针对输煤暗道的生产工艺现状，提出了采用通风与密闭抽尘净化技术，结合转载落料点密闭干雾降尘等技术措施，实现了输煤暗道内粉尘的的综合治理，通过粉尘浓度在线监测系统进行智能化控制，实现对输煤暗道通风除尘系统的远程连续监测监控，输煤暗道转载点下风侧5 m作业人员通行的位置总粉尘浓度由380.8 mg/m3降至19.8 mg/m3，降尘效率达94.8%，呼吸性粉尘浓度从96.7 mg/m3降至8.4 mg/m3，降尘效率达91.3%，降尘效果较好，有效地解决了输煤暗道及其转载落料点的粉尘污染问题，为输煤暗道内的粉尘防治提供参考依据。     

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.