Modeling,design, and optimization of a cost‐effective and reliable hybrid renewable energy system integrated with desalination using the division algorithm

People in the Middle East are facing the problem of freshwater shortages. This problem is more intense for a remote region, which has no access to the power grid. The use of seawater desalination technology integrated with the generated energy unit by renewable energy sources could help overcome this problem. In this study, we refer a seawater reverse osmosis desalination (SWROD) plant with a capacity of 1.5 m³/h used on Larak Island, Iran. Moreover, for producing fresh water and meet the load demand of the SWROD plant, three different stand‐alone hybrid renewable energy systems (SAHRES), namely wind turbine (WT)/photovoltaic (PV)/battery bank storage (BBS), PV/BBS, and WT/BBS are modeled and investigated. The optimization problem was coded in MATLAB software. Furthermore, the optimized results were obtained by the division algorithm (DA). The DA has been developed to solve the sizing problem of three SAHRES configurations by considering the object function's constraints. These results show that this improved algorithm has been simpler, more precise, faster, and more flexible than a genetic algorithm (GA) in solving problems. Moreover, the minimum total life cycle cost (TLCC = 243 763$), with minimum loss of power supply probability (LPSP = 0%) and maximum reliability, was related to the WT/PV/BBS configuration. WT/PV/BBS is also the best configuration to use less battery as a backup unit (69 units). The batteries in this configuration have a longer life cycle (maximum average of annual battery charge level) than two other configurations (93.86%). Moreover, the optimized results have shown that utilizing the configuration of WT/PV/BBS could lead to attaining a cost‐effective and green (without environmental pollution) SAHRES, with high reliability for remote areas, with appropriate potential of wind and solar irradiance.     

Hydrogen production costs of a polymer electrolyte membrane electrolysis powered by a renewable hybrid system

In this work, a novel approach related to the production of hydrogen using a polymer electrolyte membrane electrolysis powered by a renewable hybrid system is proposed. The investigation is carried out by establishing energy balances in the different components constituting the combined renewable system. A mathematical model to predict the production of electricity and hydrogen is proposed. The discrepancies between the numerical results and those from the literature review do not exceed 7%. The results show that the overall efficiency and the capacity factor of the combined renewable system without thermal storage are 20 and 34%, respectively. The levelized cost of hydrogen also is 6.86 US$/kg. The effect of certain physical parameters such as optical efficiency, water electrolysis temperature, unit electrolysis capital cost and solar multiple on the performance of the combined system is investigated. The results show that the performance of hydrogen production is optimal when the solar installation is three times oversized. The results also show that the levelized cost of hydrogen for the optimal sized is 4.07 US$/kg. Finally, the proposed combined system can produce low cost hydrogen and compete with hybrid sulfur thermochemical cycles, conventional photovoltaic installations, concentrated photovoltaic thermal systems and wind farms developed in all regions of the world.     

汽车锁零部件碱性锌镍合金电镀工艺

介绍了汽车锁零部件碱性挂镀锌镍合金电镀生产线的开发过程,包括前期市场调研、中期小槽试验、后期成本核算、电镀工艺流程确定、废水处理工艺制定以及阳极膜应用可行性分析。     

Probabilistic tree-based representation for solving minimum cost integer flow problems with nonlinear non-convex cost functions

The minimum cost flow problem (MCFP) is the most generic variation of the network flow problem which aims to transfer a commodity throughout the network to satisfy demands. The problem size (in terms of the number of nodes and arcs) and the shape of the cost function are the most critical factors when considering MCFPs. Existing mathematical programming techniques often assume the cost functions to be linear or convex. Unfortunately, the linearity and convexity assumptions are too restrictive for modelling many real-world scenarios. In addition, many real-world MCFPs are large-scale, with networks having a large number of nodes and arcs. In this paper, we propose a probabilistic tree-based genetic algorithm (PTbGA) for solving large-scale minimum cost integer flow problems with nonlinear non-convex cost functions. We first compare this probabilistic tree-based representation scheme with the priority-based representation scheme, which is the most commonly-used representation for solving MCFPs. We then compare the performance of PTbGA with that of the priority-based genetic algorithm (PrGA), and two state-of-the-art mathematical solvers on a set of MCFP instances. Our experimental results demonstrate the superiority and efficiency of PTbGA in dealing with large-sized MCFPs, as compared to the PrGA method and the mathematical solvers.     

Distributed ledger technology in supply chains: a transaction cost perspective

With the emergence of distributed ledger technology (DLT), numerous practitioners and researchers have proclaimed its beneficial impact on supply chain transactions in the future. However, the vast majority of DLT initiatives are discontinued after a short period. With the full potential of DLT laying far down the road, especially managers in supply chain management (SCM) seek for short-term cost-saving effects of DLT in order to achieve long-term benefits of DLT in the future. However, the extant research has bypassed grounding long-term as well as short-term effects of DLT on supply chain transaction with empirical data. We address this shortcoming, following an abductive research approach and combining empirical data from a multiple case study design with the corresponding literature. Our study reveals that the effects of DLT on supply chain transactions are two-sided. We found six effects of DLT solutions that have a cost-reducing or cost avoidance impact on supply chain transactions. In addition, we found two effects that change the power distribution between buyers and suppliers in transactions and a single effect that reduces the dependency of supply chain transactions on third parties. While cost-reducing and avoidance as well as dependency-reducing effects are positive effects, the change in power distribution might come with disadvantages. With these findings, the paper provides the first empirical evidence of the impact of DLT on supply chain transactions, which will enable managers to improve their assessment of DLT usage in supply chains.     

Multi-hazard loss analysis of tall buildings under wind and seismic loads

This paper presents a framework for life-cycle loss estimation for non-structural damage in tall buildings under wind and seismic loads. Life-cycle cost analysis is a useful design tool for decision- makers, aimed at predicting monetary losses over the lifetime of a structure, accounting for uncertainties involved in the problem definition. For tall buildings, sensitive to dynamic excitations like earthquake and wind, it can be particularly suitable to base design decisions not only on initial cost and performance but also on future repair expenses. The proposed approach harmonises the procedures for intervention costs evaluation of structures subjected to multiple-hazards, taking into account the peculiar differences of wind and earthquake, in terms of load characterisation, type and evolution of damage. Relative effect of the two hazards on damage to drift- and acceleration-sensitive non-structural elements are examined. The influence of uncertainty in structural damping is also taken into account. It is shown that, although it is commonly believed that the design of a given structure is usually dominated by either winds or earthquakes, when LCC-based design is performed, both winds and earthquakes may be important.     

数据信息化时代下的工程造价管理

在经济不断迅猛发展的形势下,新时代的经济形式催生出一些多元化企业和职业,信息技术的不断发展使数据信息成为最具价值的财富。在信息传播极其迅速的今天,工程造价在数据信息时代下的管理模式也不断更新变化,以适应多元化的工程项目形式。因此信息数据的大量搜集和相关研究受到了各大科研机构和各类企业的高度关注。     

Quantitative assessments of performance and robustness of maintenance policies for stochastically deteriorating production systems

Over the last few decades, many efforts have been invested in improving the economic performances of maintenance policies for stochastically deteriorating production systems. However, with the development of complex production systems, maintenance managers are interested not only in cost saving, but also in how to trustworthily plan and allocate the required maintenance budget. In this context, the robustness of maintenance policies which is related to the maintenance cost variability from a renewal cycle to another plays a pivotal role. This research deals with a quantitative approach to jointly assess the economic performance and robustness of some representatives of two most well-known classes of maintenance policies: time-based and condition-based maintenance. To this end, we first propose a new cost criterion which combines the long-run expected cost rate and standard deviation of maintenance cost per renewal cycle. Then, we develop and compare the associated mathematical cost models of the considered maintenance policies on the basis of the Gamma degradation process and the theory of stochastic renewal processes. The comparison results under different situations of maintenance costs and system characteristics show that the optimal configuration of maintenance policies gives the best compromise between the performance and robustness, and is mostly affected by the system downtime. Under this aspect, the condition-based maintenance remains more profitable than the time-based maintenance. Still, maintenance managers could implement condition-based maintenance policies that efficiently control the downtime to maximise the maintenance effectiveness of production systems from both performance and robustness viewpoints.     

Impact of Lake Michigan water level rise on complex bidirectional flow in the Chicago Area Waterway System (CAWS)

In the past decade, continuously rising water levels in Lake Michigan have been threatening lakefront areas, especially in metropolitan regions like the Greater Chicago area. This provides the motivation to analyze the impact that high lake levels have on the Chicago Area Waterway System (CAWS). As the only primary free connection between the CAWS and Lake Michigan, the Calumet Area waterway subsystem plays a key and unique role. In this work, a numerical model covering the Calumet subsystem and having Lake Michigan as a boundary condition, is set up, calibrated, and validated using limited field observations. It is found that the Calumet subsystem has become bidirectional, where both discharge and flow directions are controlled by lake levels. When lake levels are below −0.15 m (-0.5 ft, Chicago City Datum, CCD), the discharge in the Grand Calumet River is around zero, with water flowing along its east branch towards Indiana. When lake levels are above +0.46 m (+1.5 ft, CCD), the flow reverses direction and drains west into Illinois. In 2020, the mean lake-level was at +1.07 m (+3.5 ft, CCD), and the base discharge in the Grand Calumet River was approximately 8.5 m³/s (300 ft³/s). The higher Lake Michigan’s level is, the larger the discharge would be into Illinois. Potential impact of this extra discharge on Lake Michigan Diversion Accounting (LMDA) of the State of Illinois and flood management in the Chicago Sanitary and Ship Canal (CSSC), is analyzed; while the nature of the bidirectional flows is characterized with the intent of shedding light on this complex phenomenon.     

Policy reforms and productivity change in the judiciary system: a cost function approach applied to time series of the Dutch judiciary system between 1980 and 2016

The judiciary is constantly undergoing change in order to respond to a wide range of social developments that have brought the sector under increasing pressure. In order to deal with the constant call for enhancing budgets, different policy measures have been taken to downsize the appeal to the judiciary and to improve productivity. One of the central questions hereby is whether these measures have actually contributed to a more productive sector. This paper focuses on the development of productivity in the judiciary and how policy measures have affected productivity. In this empirical analysis, we apply a cost function model to time series data of the Dutch judiciary between 1980 and 2016. The results show a dramatic decline of productivity over the entire period (?50%), in spite of various policy measures. The year 2001 can be regarded as a turning point, as since then productivity has remained more or less stable. It seems that this is largely due to the establishment of the Council for the Judiciary and the associated increase in (financial and operational) autonomy for the judiciary. Another striking result is that technical change is biased toward using more personnel through time.