Influence of Cathode Modification by Chitosan and Fe^(3+)on the Electrochemical Performance of Marine Sediment Microbial Fuel Cell

The electrochemical performances of cathode play a key role in the marine sediment microbial fuel cells(MSMFCs)as a long lasting power source to drive instruments,especially when the dissolved oxygen concentration is very low in seawater.A CTS-Fe^(3+)modified cathode is prepared here by grafting chitosan(CTS)on a carbon fiber surface and then chelating Fe^(3+)through the coordination process.The electrochemical performance in seawater and the output power of the assembled MSMFCs are both studied.The results show that the exchange current densities of CTS and the CTS-Fe^(3+)group are 5.5 and 6.2 times higher than that of the blank group,respectively.The potential of the CTS-Fe^(3+)modified cathode increases by 138 mV.The output power of the fuel cell(613.0 mW m^(-2))assembled with CTS-Fe^(3+)is 54 times larger than that of the blank group(11.4 mW m^(-2))and the current output corresponding with the maximum power output also increases by 56 times.Due to the valence conversion between Fe^(3+)and Fe^(2+)on the modified cathode,the kinetic activity of the dissolved oxygen reduction is accelerated and the depolarization capability of the cathode is enhanced,resulting higher cell power.On the basis of this study,the new cathode materials will be encouraged to design with the complex of iron ion in natural seawater as the catalysis for oxygen reduction to improve the cell power in deep sea.

A Novel Modified Alpha Power Transformed Weibull Distribution and Its Engineering Applications

This paper suggests a new modified version of the traditional Weibull distribution by adding a new shape parameter utilising the modified alpha power transformed technique.We refer to the new model as modified alpha power transformed Weibull distribution.The attractiveness and significance of the new distribution lie in its power to model monotone and non-monotone failure rate functions,which are quite familiar in environmental investigations.Its hazard rate function can be decreasing,increasing,bathtub and upside-down then bathtub shaped.Diverse structural properties of the proposed model are acquired including quantile function,moments,entropies,order statistics,residual life and reversed failure rate function.The parameters of the distribution were estimated using the maximum likelihood function.The maximum likelihood method is employed to estimate the model parameters and the approximate confidence intervals are also computed.Via a simulation study,the performance of the point and interval estimates are compared using different criteria.Employing real lifetime data sets,we verify that the offered model furnishes a better fit than some other lifetime models including Weibull,gamma and alpha powerWeibull models.

Forecasting Model of Photovoltaic Power Based on KPCA-MCS-DCNN

Accurate photovoltaic(PV)power prediction can effectively help the power sector to make rational energy planning and dispatching decisions,promote PV consumption,make full use of renewable energy and alleviate energy problems.To address this research objective,this paper proposes a prediction model based on kernel principal component analysis(KPCA),modified cuckoo search algorithm(MCS)and deep convolutional neural networks(DCNN).Firstly,KPCA is utilized to reduce the dimension of the feature,which aims to reduce the redundant input vectors.Then using MCS to optimize the parameters of DCNN.Finally,the photovoltaic power forecasting method of KPCA-MCS-DCNN is established.In order to verify the prediction performance of the proposed model,this paper selects a photovoltaic power station in China for example analysis.The results show that the new hybrid KPCA-MCS-DCNN model has higher prediction accuracy and better robustness.

Wind power time series simulation model based on typical daily output processes and Markov algorithm

The simulation of wind power time series is a key process in renewable power allocation planning,operation mode calculation,and safety assessment.Traditional single-point modeling methods discretely generate wind power at each moment;however,they ignore the daily output characteristics and are unable to consider both modeling accuracy and efficiency.To resolve this problem,a wind power time series simulation model based on typical daily output processes and Markov algorithm is proposed.First,a typical daily output process classification method based on time series similarity and modified K-means clustering algorithm is presented.Second,considering the typical daily output processes as status variables,a wind power time series simulation model based on Markov algorithm is constructed.Finally,a case is analyzed based on the measured data of a wind farm in China.The proposed model is then compared with traditional methods to verify its effectiveness and applicability.The comparison results indicate that the statistical characteristics,probability distributions,and autocorrelation characteristics of the wind power time series generated by the proposed model are better than those of the traditional methods.Moreover,modeling efficiency considerably improves.

Solving Optimal Power Flow Using Modified Bacterial Foraging Algorithm Considering FACTS Devices

In this paper, a new Modified Bacterial Foraging Algorithm (MBFA) method is developed to incorporate FACTS devices in optimal power flow (OPF) problem. This method can provide an enhanced economic solution with the use of controllable FACTS devices. Two types of FACTS devices, thyristor controlled series compensators (TCSC) and Static VAR Compensator (SVC) are considered in this method. The basic bacterial foraging algorithm (BFA) is an evolutionary optimization technique inspired by the foraging behavior of the E. coli bacteria. The strategy of the OPF problem is decomposed in two sub-problems, the first sub-problem related to active power planning to minimize the fuel cost function, and the second sub-problem designed to make corrections to the voltage deviation and reactive power violation based in an efficient reactive power planning of multi Static VAR Compensator (SVC). The specified power flow control constraints due to the use of FACTS devices are included in the OPF problem. The proposed method decomposes the solution of such modified OPF problem into two sub problems’ iteration. The first sub problem is a power flow control problem and the second sub problem is a modified Bacterial foraging algorithm (MBFA) OPF problem. The two sub problems are solved iteratively until convergence. Case studies are presented to show the effectiveness of the proposed method.

Error Detection and Pattern Prediction Through Phase II Process Monitoring

The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution.It is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality improvement.The current study introduces control charts that help the manufacturing concerns to keep the production process in control.It presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their performance.The percentiles estimator and the modified maximum likelihood estimator are used to constructing the control charts.The findings suggest that an extended exponentially weighted moving average control chart based on the percentiles estimator performs better than exponentially weightedmoving average control charts based on the percentiles estimator and modified maximum likelihood estimator.Further,these results will help the firms in the early detection of errors that enhance the process reliability of the telecommunications and financing industry.

Non-Newtonian Power-Law Fluid Flow and Heat Transfer over a Non-Linearly Stretching Surface

The problem of magneto-hydrodynamic flow and heat transfer of an electrically conducting non-Newtonian power-law fluid past a non-linearly stretching surface in the presence of a transverse magnetic field is considered. The stretching velocity, the temperature and the transverse magnetic field are assumed to vary in a power-law with the distance from the origin. The flow is induced due to an infinite elastic sheet which is stretched in its own plane. The governing equations are reduced to non-linear ordinary differential equations by means of similarity transformations. These equations are then solved numerically by an implicit finite-difference scheme known as Keller-Box method. The numerical solution is found to be dependent on several governing parameters, including the magnetic field parameter, power-law index, velocity exponent parameter, temperature exponent parameter, Modified Prandtl number and heat source/sink parameter. A systematic study is carried out to illustrate the effects of these parameters on the fluid velocity and the temperature distribution in the boundary layer. The results for the local skin-friction coefficient and the local Nusselt number are tabulated and discussed. The results obtained reveal many interesting behaviors that warrant further study on the equations related to non-Newtonian fluid phenomena.

空气标准等温加热修正Brayton循环:(1)功率效率特性分析

在已有文献建立的闭式等温加热修正定常流式Brayton循环模型基础上,提出了一种新的五分支Brayton循环,即空气标准等温加热修正Brayton循环,并运用有限时间热力学理论建立了内可逆空气标准等温加热修正Brayton循环模型,导出了其功率效率表达式,分析了最大温比和预胀比对功率与效率、功率与压缩比和效率与压缩比特性关系的影响,以及传热损失对功率与效率特性关系的影响,并将修正后的Brayton循环性能与传统的Brayton循环性能进行了对比。结果表明:循环功率与效率的关系曲线呈扭叶形,而功率与压缩比和效率与压缩比的关系曲线均呈类抛物线形;随着预胀比和循环温比的增加,循环性能明显提升;与传统的Brayton循环相比,修正后的循环性能更优。

Taylor幂法则模型的改进单纯形法最优拟合

Ｔａｙｌｏｒ幂法则模型是研究种群空间格局的重要工具之一。其拟合方法通常采用对数线性化最小二乘法求得参数ａ、ｂ值。这种方法不是最优的，本文提出用改进单纯形法最优拟合Ｔａｙｌｏｒ幂法则，并比较了多种方法的拟合结果，证明改进单纯形法简单、精确，优于其他拟合方法。

一种改进的Newton算法在电力系统潮流计算中的研究与应用

为了提高电力系统潮流计算的计算速度,适应不断发展的电力系统规模和多区域电网的互联运行,文章在分Newton-Raphson潮流算法存在的缺点的基础上,对离散Newton法和修正Newton法进行了比较,提出了一种基于二者的改进算法并将其用于电力系统潮流计算。该算法无需计算Jacobi矩阵,迭代次数更少,比Newton法具有更高的效率。利用IEEE57及IEEE300母线标准试验系统验证,结果表明在相同的收敛精度下,该算法具有更高的收敛速度,是一种可供实际运用的方法。

碳中和背景下我国多晶硅产业现状及发展趋势

在碳中和、碳达峰的重大时代背景下,加速能源结构转型、改变当前能源结构已成共识。本文简述了目前多晶硅主要的生产工艺流程,从多方面对比了各工艺的优缺点,详述了改良西门子法与硅烷流化床法工艺的发展趋势,指出硅烷流化床法仍有巨大改进空间,有望给我国多晶硅行业带来崭新局面。多晶硅产业逐渐向我国转移,我国市场占有率不断提升,推动双碳目标的实现也更加离不开多晶硅产业的发展。

变温热源等温加热修正不可逆回热Brayton循环功率优化

根据有限时间热力学理论,在给定各换热器总热导率的情况下,对变温热源条件下等温加热过程修正的不可逆回热式Brayton循环的功率特性进行了优化。研究表明,该情况下全局性的优化结果并不存在。在给定CCC(收敛型燃烧室)和回热器热导率分配的情况下,通过数值计算,得到了最佳的透平出口温度及RCC(常规燃烧室)和低温侧换热器的热导率分配,讨论了循环参数对最佳热导率分配的影响。另外,本文还对文献[7]中的错误进行了修正,并分析了循环工质与热源的热容率匹配问题。

回热式等温加热修正Brayton循环的功率与效率特性!

根据有限时间热力学理论,分析了变温热源条件下不可逆回热式等温加热修正Brayton循环的功率、效率的全局特性和最优特性。研究发现,计入外部传热不可逆性后,分别存在最佳的循环压比使得循环无因次输出功率和效率取得最大值,而且,一般来说,前一最佳压比更大;回热对循环的输出功率影响极小,对循环效率的提高也只在较低压比时起作用;为提高循环的输出功率和效率,常规燃烧室(RCC)有效度、RCC中热源的入口温度和热容率应取较小的值,而收敛型燃烧室(CCC)有效度、CCC中热源的入口温度和热容率应取较大的值。详细讨论了循环热力参数对最大无因次输出功率及其对应的最佳压比和效率、最大效率及其对应的最佳压比和无因次输出功率的影响,指出了已有文献的错误。研究结果对燃气轮机装置的评估和最优设计具有一定的指导意义。

基于TOPSwitch-Ⅱ的小功率通用开关电源的快速设计

介绍了开关电源的基本原理,以及Topswitch-Ⅱ型开关芯片的结构,探讨了基于该芯片小功率通用开关电源的设计过程中开关管的选型,主要元件参数的计算等问题。最后通过仿真试验,对电源的设计过程进行了认证。

基于改进深度学习的光伏电站发电量精准估计

为实现对电站发电量的精准估计与测算,引入改进深度学习算法,以某光伏发电站为例,进行发电量精准估计方法的设计研究。计算光伏电站太阳辐照量,收集光伏电站功率、电流、电压等发电数据以及太阳辐射强度、温度、湿度等相关气象数据,并对收集到的光伏电站发电信息进行预处理;为排除光伏组件损失对发电量估算的影响,先进行光伏组件损失分析,再以此为依据对光伏电站发电量进行估计。实例应用结果表明该设计方法在应用中可以有效控制光伏电站发电量估计误差,提高发电量估计值的准确性与可靠性。

A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG

In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more reliably and economically. In this regard, this paper proposes a novel solution methodology based on bat algorithm to solve the op- timal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), Photovoltaics (PV), Micro Turbine (MT) as well as storage devices to meet the energy mismatch. The problem is formulated as a nonlinear constraint optimization problem to minimize the total cost of the grid and RESs, simultaneously. In addition, the problem considers the interactive effects of MG and utility in a 24 hour time interval which would in- crease the complexity of the problem from the optimization point of view more severely. The proposed optimization technique is consisted of a self adaptive modification method compromised of two modification methods based on bat algorithm to explore the total search space globally. The superiority of the proposed method over the other well-known algorithms is demonstrated through a typical renewable MG as the test system.

Pyrolyzed Iron Phthalocyanine-Modified Multi-Walled Carbon Nanotubes as Composite Anode in Marine Sediment Microbial Fuel Cells and Its Electrochemical Performance

Improving the performance of anode is a crucial step for increasing output power of marine sediment microbial fuel cells(MSMFCs)to drive marine monitor to work for a long term on the ocean floor.A pyrolyzed iron phthalocyanine modified multi-walled carbon nanotubes composite(FePc/MWCNTs)has been utilized as a novel nodified anode in the MSMFC.Its structure of the composite modified anode and electrochemical performance have been investigated respectively in the paper.There is a substantial improvement in electron-transfer efficiency from the bacteria biofilm to the modified anode via the pyrolyzed FePc/MWCNTs composite based on their cyclic voltammetry(CV)and Tafel curves.The electron transfer kinetic activity of the FePc/MWCNTs-modified anode is 1.86 times higher than of the unmodified anode.The maximum power density of the modified MSMFC was 572.3±14 m W m^-2,which is 2.6 times larger than the unmodified one(218.3±11 m W m^-2).The anodic structure and cell scale would be greatly minimized to obtain the same output power by the modified MSMFC,so that it will make the MSMFC to be easily deployed on the remote ocean floor.Therefore,it would have a great significance for us to design a novel and renewable long term power source.Finally,a novel molecular synergetic mechanism is proposed to elucidate its excellent electrochemical performance.

Thermo-electronic solar power conversion with a parabolic concentrator

We consider the energy dynamics of the power generation from the sun when the solar energy is con- centrated on to the emitter ofa thermo-electronic converter with the help of a parabolic mirror. We use the modified Richardson-Dushman equation. The emitter cross section is assumed to be exactly equal to the focused area at a height h from the base of the mirror to prevent loss of efficiency. We report the variation of output power with solar insolation, height h, reflectivity of the mirror, and anode temperature, initially assuming that there is no space charge effect. Our methodology allows us to predict the temperature at which the anode must be cooled in order to prevent loss of efficiency of power conversion. Novel ways of tackling the space charge problem have been discussed. The space charge effect is modeled through the introduction of a parameter f （0 〈 f 〈 1） in the thermos-electron emission equation. We find that the efficiency of the power conversion depends on solar insolation, height h, apart from radii R of the concentrator aperture and emitter, and the collector material properties. We have also considered solar thermos electronic power conversion by using single atom-layer graphene as an emitter.

Generalized Kumaraswamy Generalized Power Gompertz Distribution: Statistical Properties, Application, and Validation Using a Modified Chi-Squared Goodness of Fit Test

A new six-parameter continuous distribution called the Generalized Kumaraswamy Generalized Power Gompertz (GKGPG) distribution is proposed in this study, a graphical illustration of the probability density function and cumulative distribution function is presented. The statistical features of the Generalized Kumaraswamy Generalized Power Gompertz distribution are systematically derived and adequately studied. The estimation of the model parameters in the absence of censoring and under-right censoring is performed using the method of maximum likelihood. The test statistic for right-censored data, criteria test for GKGPG distribution, estimated matrix Ŵ, Ĉ, and Ĝ, criteria test Y2n, alongside the quadratic form of the test statistic is derived. Mean simulated values of maximum likelihood estimates and their corresponding square mean errors are presented and confirmed to agree closely with the true parameter values. Simulated levels of significance for Y2n (γ) test for the GKGPG model against their theoretical values were recorded. We conclude that the null hypothesis for which simulated samples are fitted by GKGPG distribution is widely validated for the different levels of significance considered. From the summary of the results of the strength of a specific type of braided cord dataset on the GKGPG model, it is observed that the proposed GKGPG model fits the data set for a significance level ε = 0.05.