Techno-economic assessment of hydrogen refueling station: A case study in Croatia

Hydrogen refueling station (HRS) capacity and location depend on the users, which makes it difficult to select the most favorable option before potential users are actually identified. As in Croatia, at least for now, there are no hydrogen users, this study considers a wide range of HRS capacities and their different configurations. These include hydrogen production and charging station within one existing wind farm in Croatia or both nearby the users, the hydrogen production within the wind farm and the charging station nearby the users, while hydrogen is delivered to the station with a tube trailer, and configuration of hydrogen production within the wind farm with a mobile charging station in case of several users in different locations. Each HRS configuration is evaluated by the obtained levelized cost of hydrogen depending on the capital, and operation and maintenance costs within the HRS techno-economic analysis provided.     

Stochastic polynomial optimization

ABSTRACT

This paper studies stochastic optimization problems with polynomials. We propose an optimization model with sample averages and perturbations. The Lasserre-type Moment-SOS relaxations are used to solve the sample average optimization. Properties of the optimization and its relaxations are studied. Numerical experiments are presented.     

An improved iterative stochastic multi-objective acceptability analysis method for robust alternative selection in new product development

Alternative selection in new product development (NPD) is a multi-criteria decision-making (MCDM) problem. It usually starts with incomplete, imprecise or even partially missing information. Currently, most existing methods in dealing with this problem cannot work well if required information is incomplete or missing. It is acknowledged that stochastic multi-objective acceptability analysis (SMAA) can be applied to address MCDM problem with incomplete preference information and uncertain criteria measurements. In SMAA, alternatives are evaluated based on SMAA measurements (acceptability index, central weight vector and confidence factor). The discriminability of SMAA for the optimum alternative heavily depends on differences of SMAA measurements among different alternatives. Usually, a large number of alternatives and high level of uncertainty are involved in alternative selection in NPD. In this situation, the differences among SMAA measurements are not obvious, and therefore SMAA cannot deal with such problem very well. To this end, this paper proposes an improved SMAA method called Iterative-SMAA (I-SMAA) for alternative selection in NPD. In the I-SMAA, an iterative multi-step decision-making process is suggested to improve differences of SMAA measurements among different alternatives, and thus assist decision makers (DMs) to positively discern from the most preferred alternative. To enhance the decision-making efficiency, sensitive criteria are acquired in each iteration by ranking sensitivity analysis. DMs are guided to provide partial preference information and give more accurate criteria measurements for sensitive criteria rather than all criteria. Eventually, to verify the proposed method, a numerical example of the existing literature is solved with the method, and the results are compared. And then, a practical example of a preparation equipment for coal samples is further employed to verify the practicability of the proposed I-SMAA.     

Stochastic analysis of strongly non-linear elastic impact system with Coulomb friction excited by white noise

The stochastic response of frictionally damped strongly non-linear elastic impact oscillator subjected to white noise excitation and its stochastic bifurcation are considered. By the stochastic averaging method based on generalized harmonic function, one can obtain the stationary probability density function of this system. The effects of system parameters on the responses are investigated and the analytical results were verified by comparing with numerical results from Monte Carlo simulations. Stochastic bifurcations are discussed through a qualitative change of the stationary probability distribution, which indicates that the coefficient of friction, damping constant of the elastic impact force respectively, can be treated as bifurcation parameters.     

论游戏的核心艺术评价标准

数字游戏常被认为是继文学、绘画、音乐等传统艺术之后的“第九艺术”。然而,长期以来,由于游戏的评价标准被商业体系左右,造成了游戏创作在思想层面的偏颇,所以设计师有必要建立一套针对数字游戏的艺术评价标准,以促进游戏的艺术创作和理论研究。从艺术思潮、艺术哲学和设计创新的角度出发,通过美学历史文献查阅、游戏艺术作品案例分析、艺术理论辨析等方法,就游戏的核心艺术因素展开论述。游戏的艺术标准应包括情感表现、艺术反思和创新性三个主要方面。其中,艺术情感是所有艺术的共性和核心;艺术反思是艺术理念的升华和艺术创作的动机;创新性则是艺术更替发展的内在动力。该标准独立于商业体系,将有助于促进和引导数字游戏在艺术层面的发展。     

The role of Persian-language word exercise games in improving spelling of students with dyslexia: Word exercise games in improving spelling

Children with dyslexia have reduced sensitivity to phonological sounds and words, and this deficiency in lexical processing causes many problems for them. Word exercise games based on phonological awareness have emphasized the mistakes of students with dyslexia, attempting to help children avoid these mistakes. This study was conducted to investigate the effect of Persian-language word exercise games on the spelling of students with dyslexia. The design of the present study was quasi-experimental, with a pretest and posttest of an experimental group and a control group. Participants were 30 students with dyslexia from second grade to fifth grade in elementary schools in Bojnord, who completed the spelling test as a pretest and posttest. The experimental group played eleven 40-min sessions of word exercise games. The results showed that the word exercise programme improved the spelling of the children with dyslexia. This suggests that basing training on the phonological mistakes of students with dyslexia and using the word exercise games can improve their spelling.     

Spillover effects of distribution grid tariffs in the internal electricity market: An argument for harmonization?

In many countries, distribution grid tariffs are being reformed to adapt to the new realities of an electricity system with distributed energy resources. In Europe, legislative proposals have been made to harmonize these reforms across country borders. Many stakeholders have argued that distribution tariffs are a local affair, while the European institutions argued that there can be spillovers to other countries, which could justify a more harmonized approach. In this paper, we quantify these spillovers in a simplified numerical example to give insight and an order of magnitude. We look at different scenarios, and find that the spillovers can be both negative and positive. To be able to quantify these effects, we developed a long-run market equilibrium model that captures the wholesale market effects of distribution grid tariffs. The problem is formulated as a non-cooperative game involving consumers, generating companies and distribution system operators in a stylized electricity market.     

Coverage control algorithm for wireless sensor networks based on non-cooperative game

For the redundancy coverage of nodes leads to the phenomenon of low energy efficiency,Non-cooperative game theory was used to solve it.A revenue function was proposed,which considering the coverage of nodes and the residual energy.The lifetime of the node and network path gain were applied to revenue function.The network topology was built by nodes with the appropriate work strategy.Control algorithm coverage in wireless sensor network was proposed based on Non-cooperative game theory.A Nash equilibrium between the coverage rate and the residual energy was proved,and the return function converged to the Pareto optimal.Experiments show that the algorithm can provide reasonable coverage of network nodes and ensure energy efficiency.     

基于博弈分析的流域水资源配置

针对传统规划方法难以体现水资源配置过程中多种复杂因素的问题,基于博弈理论建立宏观调控和市场经济相结合的水资源配置动态博弈模型,求解其子博弈精炼纳什均衡下各博弈参与人的策略,并运用改进量子遗传算法求解该博弈模型。对A河流域水资源配置结果表明,在保证流域公共生态用水2.0×10~8 m~3的基础上,各用水子区自发约束自身的取水量,达到均衡时,社会总收益为11.27亿元,相比自由取水模型,社会总收益增加了0.95亿元,增幅为9.2%。     

Kalman filter based production control of a failure-prone single-machine single-product manufacturing system with imprecise demand and inventory information

An adaptive production control structure for failure-prone manufacturing systems under inventory and demand uncertainty is proposed. It contains estimation and forecasting modules incorporated into a control loop. The customer demand is unknown and its rate is composed of ramp-type, seasonal and random components. Information available to decision maker consists of imprecise inventory records, and the Kalman filter technique is used for estimating the inventory level and demand rate online from noisy inventory measurements. Estimates obtained are shown to converge to the actual values in stochastic sense. They are subsequently used for demand component forecasting, once the estimation errors become sufficiently small. A forecasting algorithm allows estimating ramp-type and seasonal demand components, together with their potential errors. Obtained estimates are incorporated into production control procedures, recently developed for manufacturing systems under variable and uncertain demand. Optimality conditions in the form of Hamilton-Jacobi-Bellman equations are obtained. A constructive numerical method for computing sub-optimal production policies is proposed and validated through numerical simulations.