Impact of industrial virtual power plant on renewable energy integration

An industrial park is one of the typical energy consumption schemes in power systems owing to the heavy industrial loads and their abilities to respond to electricity price changes. Therefore, energy integration in the industrial sector is significant. Accordingly, the concept of industrial virtual power plant (IVPP) has been proposed to deal with such problems. This study demonstrates an IVPP model to manage resources in an eco-industrial park, including energy storage systems, demand response (DR) resources, and distributed energies. In addition, fuzzy theory is used to change the deterministic system constraints to fuzzy parameters, considering the uncertainty of renewable energy, and fuzzy chance constraints are then set based on the credibility theory. By maximizing the daily benefits of the IVPP owners in day-ahead markets, DR and energy storage systems can be scheduled economically. Therefore, the energy between the grid and IVPP can flow in both directions: the surplus renewable electricity of IVPP can be sold in the market; when the electricity generated inside IVPP is not enough for its use, IVPP can also purchase power through the market. Case studies based on three wind-level scenarios demonstrate the efficient synergies between IVPP resources. The validation results indicate that IVPP can optimize the supply and demand resources in industrial parks, thereby decarbonizing the power systems.     

Technologies for Single-Cell Isolation

The handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods. This review provides an overview of technologies that are currently used or in development to isolate single cells for subsequent single-cell analysis. Data from a dedicated online market survey conducted to identify the most relevant technologies, presented here for the first time, shows that FACS (fluorescence activated cell sorting) respectively Flow cytometry (33% usage), laser microdissection (17%), manual cell picking (17%), random seeding/dilution (15%), and microfluidics/lab-on-a-chip devices (12%) are currently the most frequently used technologies. These most prominent technologies are described in detail and key performance factors are discussed. The survey data indicates a further increasing interest in single-cell isolation tools for the coming years. Additionally, a worldwide patent search was performed to screen for emerging technologies that might become relevant in the future. In total 179 patents were found, out of which 25 were evaluated by screening the title and abstract to be relevant to the field.     

Ant colony approaches for multiobjective structural optimization problems with a cardinality constraint

Two Ant Colony Optimization algorithms are proposed to tackle multiobjective structural optimization problems with an additional constraint. A cardinality constraint is introduced in order to limit the number of distinct values of the design variables appearing in any candidate solution. Such constraint is directly enforced when an ant builds a candidate solution, while the other mechanical constraints are handled by means of an adaptive penalty method (APM). The test-problems are composed by structural optimization problems with discrete design variables, and the objectives are to minimize both the structure’s weight and its maximum nodal displacement. The Pareto sets generated in the computational experiments are evaluated by means of performance metrics, and the obtained designs are also compared with solutions available from single-objective studies in the literature.     

On optimizing system energy of voltage–frequency island based 3-D multi-core SoCs under thermal constraints

Three dimensional (3-D) multi-core SoC has been recognized as a promising solution for implementing complex applications with lower system energy. Recently, voltage–frequency island (VFI)-based design paradigm was widely adopted for energy optimization. However, the existing work commonly targeted 2-D platform, which cannot handle the exacerbated thermal issues and the increased solution space from 3-D integration. In this paper, we propose an optimization framework targeting VFI-based 3-D multi-core SoCs to minimize system energy meanwhile still meeting task deadline and thermal constraints. Our framework conducts at an earlier design phase in which designers have the freedom to determine the core stacks and map them into the hardware platform. Besides energy-aware task scheduling, we also conduct core stacking and task adjusting to balance the powers across the chip for thermal optimization. Moreover, by treating each core stack as a unity, the complicated problem of core mapping and VFI partitioning in 3-D platform can be simplified as a 2-D one. Experimental results demonstrate that on average our framework can achieve an energy reduction of 15.8% over the prior thermal balancing algorithm [17] (X. Zhou, J. Yang, Y. Xu, et al. Thermal-aware task scheduling for 3D multicore processors, IEEE Trans. Parallel Distrib. Syst. (TPDS), 21(1) (2010), 60–71.). Moreover, on average a reduction of 4.8 °C in peak temperature is achieved by our framework, compared with the state-of-the-art energy optimization scheme [8] (U.Y. Ogras, R. Marculescu, P. Choudhary, et al. Voltage–frequency island partitioning for GALS-based networks-on-chip, in: ACM/IEEE Design Automation Conference (DAC), 2007, pp. 110–115.).     

Simulation-based baggage handling system merge analysis

This paper details the investigation into the design and control of merging bottlenecks of conveyor-based baggage handling systems, encompassing the merging control algorithm and the impact of the merge’s physical layout. A methodology for the analysis of simulation model results is presented. Results show that the layout of the merge influences bag throughput and when the physical configuration is in a preferred position, input variance has no effect on bag throughput performance. These results have potential application to other material handling systems, such as those used in manufacturing and warehousing.     

转角型幕墙铝板风荷载作用下内力和变形的数值模拟

阐述了转角型铝板和加劲肋构成的铝板幕墙的内力及变形计算，采用ANSYS软件，对板块由转角型铝板与5条加劲肋组成的复合结构的内力和变形进行计算，研究了加劲肋与铝板转角处由于局部铆钉松脱由刚结点变成铰接点后，其计算模型发生改变的应力及位移计算，最后介绍实际应用。     

A simulation-based optimization approach for a semiconductor photobay with automated material handling system

This study addressed the issue of automated material handling systems (AMHS) in the photolithography zone of a 300 mm (12-in.) wafer fab facility. The lithography process accounts for 40–50% of the time required to produce wafers. Therefore, managing the AMHS in the photolithography zone is a challenging task. This paper examines the dispatching rule and the number of vehicles in variable wafer input cases. With a stochastic and complex manufacturing process, a photobay simulation may lead to excessive iterations and wasted computation time. The most frequently used approach for process management in the literature is performance analysis with a model that simulates each alternative for N times. However, this approach becomes time consuming as the number of variables and iterations increases. To address this issue, we use Optimal Computing Budget Allocation (OCBA) and extend OCBA by adding particle swarm optimization (PSO). With this combined approached, the number of iterations of each alternative is determined by OCBA, and the optimal solution in the domain of feasible solutions is identified through PSO. This research provides a useful reference to optimally allocate lithographical resources and the number of iterations with random parameters for both scholars and practitioners. Results demonstrate the superiority of PSO_OCBA in terms of searching quality and robustness.     

Asymmetric relay autotuning – Practical features for industrial use

The relay autotuner provides a simple way of finding PID controller parameters. Even though relay autotuning is much investigated in the literature, the practical aspects are not that well-documented. In this paper an asymmetric relay autotuner with features such as a startup procedure and adaptive relay amplitudes is proposed. Parameter choices and handling of noise, disturbances, start in non-steady state and other possible error sources are discussed. The autotuner is implemented and tested on an industrial air handling unit to show its use in practice. The experiments show good results, and prove that the proposed simple autotuner is well-suited for industrial use. But the experiments also enlighten possible error sources and remaining problems.     

Design and analysis of multi-source multi-area deregulated power system for automatic generation control using quasi-oppositional harmony search algorithm

The present article focuses on the study of automatic generation control (AGC) of a realistic power system having a distinct combination of multi-area multi-source generating units in each control area under deregulated framework. An attempt is made in this paper to integrate reheat thermal, hydro and gas generating unit in a single control area and, then, extended this combination to five control areas. In this work, six reheat thermal, six hydro and three gas generating units are taken into account for the modeling of five-area power system. Some important physical constraints like time delay, governor dead band and generation rate constraint are imposed in the power system dynamics to get an accurate perception of the deregulated AGC subject. The highlighting features of the present work are to model, simulate, optimize and co-relate their inter-related dynamic performances for the purpose of AGC study. For such a complex AGC model, the vital role of the proposed quasi-oppositional harmony search (QOHS) algorithm, as an optimizing tool, is signified while solving the AGC problem in deregulated regime. The simplicity of the structure and acceptability of the responses of the well-known proportional–integral–derivative controller, inherently, enforces to employ in this work. The three classes of extensive deregulated cases (in the presence of load following and physical constraints) are demonstrated by examining the closed loop performance of the studied model. The simulation results show that the designed power system model may be a feasible one and the proposed QOHS algorithm may be a promising optimization technique under these circumstances.     

Lift-and-project MVEE based convex hull for robust SCED with wind power integration using historical data-driven modeling approach

This paper presents an adjustable robust security constrained economic dispatch (SCED) model with wind power uncertainties. First, the scenario based adjustable robust SCED model is presented. It considers multiple scenarios from historical data as well as the spatial correlation among wind farms. Then, the proposed SCED model becomes an optimization problem with a large amount of constraints which is skillfully solved using a lift-and-project minimum volume enclosing ellipsoid (MVEE) based convex hull. Furthermore, the proposed model is transformed into a second order cone programming (SOCP) model by the use of participation factors to generate adjustable generation outputs and thus guarantee the energy balance. In order to further reduce the computational complexity, the inactive constraints reduction strategy is proposed to quickly eliminate inactive SOC security constraints before solving the model. Numerical results of IEEE 14-bus and 118-bus test systems as well as the practical Polish power systems with several wind farms show that the proposed model can achieve better economies. Moreover, more than 82% of security constraints are identified as inactive in various cases of the simulation, and the proposed inactive constraints reduction strategy is promising for improving the computational performance.