Global optimization for power dispatch problems based on theory of moments

Non-convex of an optimal power dispatch problem makes it difficult to guarantee the global optimum. This paper presents a convex relaxation approach, called the Moment Semidefinite Programming (MSDP) method, to facilitate the search for deterministic global optimal solutions. The method employs a sequence of moments, which can linearize polynomial functions and construct positive semidefinite moment matrices, to form an SDP convex relaxation for power dispatch problems. In particular, the rank of the moment matrix is used as a sufficient condition to ensure the global optimality. The same condition can also be leveraged to estimate the number of global optimal solution(s). This method is effectively applied to {0,1}-economic dispatch (ED) problems and optimal power flow (OPF) problems. Simulation results showed that the MSDP method is capable of solving {0,1}-ED problems with integer values directly, and is able to identify if more than one global optimal solutions exist. In additional, the method can obtain rank-1 moment matrices for OPF’s counterexamples of existing SDP method, this ensures the global solution and overcomes the problem that existing SDP method cannot meet the rank-1 condition sometimes.     

Kariya (Hildegardia barteri) seed oil extraction: comparative evaluation of solvents,modeling, and optimization techniques

In this work, the effects of solid/solvent ratio (0.10–0.25?g/ml), extraction time (3–8?h), and solvent type (n-hexane, ethyl acetate, and acetone) together with their shared interactions on Kariya seed oil (KSO) yield were investigated. The oil extraction process was modeled via response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) while the optimization of the three input variables essential to the oil extraction process was carried out by genetic algorithm (GA) and RSM methods. The low mean relative percent deviation (MRPD) of 0.94–4.69% and high coefficient of determination (R²) > 0.98 for the models developed demonstrate that they describe the solvent extraction process with high accuracy in this order: ANFIS, ANN, and RSM. The best operating condition (solid/solvent ratio of 0.1?g/ml, extraction time of 8?h, and acetone as solvent of extraction) that gave the highest KSO yield (32.52?wt.%) was obtained using GA-ANFIS and GA-ANN. Solvent extraction efficiency evaluation showed that ethyl acetate, n-hexane, and acetone gave maximum experimental oil yields of 19.20?±?0.28, 25.11?±?0.01, and 32.33?±?0.04?wt.%, respectively. Properties of the KSO varied based on the type of solvent used. The results of this work showed that KSO could function as raw material in both food and chemical industries.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

Nonlinear response in glass fibre non-crimp fabric reinforced vinylester composites

This paper addresses the nonlinear stress-strain response in glass fibre non-crimp fabric reinforced vinylester composite laminates subjected to in-plane tensile loading. The nonlinearity is shown to be a combination of brittle and plastic failure. It is argued that the shift from plastic to brittle behaviour in the vinylester is caused by the state of stress triaxiality caused by the interaction between fibre and vinylester. A model combining damage and plasticity is calibrated and evaluated using data from extensive experimental testing. The onset of damage is predicted using the Puck failure criterion, and the evolution of damage is calibrated from the observed softening in plies loaded in transverse tension. Shear loading beyond linear elastic response is observed to result in irreversible strains. A yield criterion is implemented for shear deformation. A strain hardening law is fitted to the stress-strain response observed in shear loaded plies. Experimental results from a selection of laminates with different layups are used to verify the numerical models. A complete set of model parameters for predicting elastic behaviour, strength and post failure softening is presented for glass fibre non-crimped fabric reinforced vinylester. The predicted behaviour from using these model parameters are shown to be in good agreement with experimental results.     

Remote Steering of Self‐Propelling Microcircuits by Modulated Electric Field

The principles and design of “active” self‐propelling particles that can convert energy, move directionally on their own, and perform a certain function is an emerging multidisciplinary research field, with high potential for future technologies. A simple and effective technique is presented for on‐demand steering of self‐propelling microdiodes that move electroosmotically on water surface, while supplied with energy by an external alternating (AC) field. It is demonstrated how one can control remotely the direction of diode locomotion by electronically modifying the applied AC signal. The swimming diodes change their direction of motion when a wave asymmetry (equivalent to a DC offset) is introduced into the signal. The data analysis shows that the ability to control and reverse the direction of motion is a result of the electrostatic torque between the asymmetrically polarized diodes and the ionic charges redistributed in the vessel. This novel principle of electrical signal‐coded steering of active functional devices, such as diodes and microcircuits, can find applications in motile sensors, MEMs, and microrobotics.     

基于多项式变换的参数估计方法

本文给出一种采用DPT估计SNCK信号时宽—带宽积的方法,并通过仿真该估计方法的性能与其它估计方法进行比较.首先给出SNCK信号参数估计的一般过程.为了便于计算和理论推导,根据估计出的中心频率将接收到的SNCK信号搬移到零频,从而进一步估计其它参数,如采用DPT估计SNCK信号时宽带宽积.本文将重点研究采用DPT算法估计SNCK信号值的方法.     

Computational studies on the radiative and nonradiative processes of luminescent N-heteroleptic platinum(II) complexes

Three N-heteroleptic Pt(II) complexes, [Pt(C^C)(O^O)] [O^O = acetylacetonate, C^C = 1-phenyl-1,2,4-triazol-5-ylidene (1), C^C = 4-phenyl-1,2,4-triazol-5-ylidene (2), C^C = 2-phenylpyrazine (3)] have been investigated with density functional theory (DFT) and time-dependent density functional theory (TDDFT). The radiative decay rate constants of complexes 1–3 have been discussed with the oscillator strength (f_n), the strength of spin–orbit coupling (SOC) interaction between the lowest energy triplet excited state (T₁) and singlet excited states (S_n), and the energy gaps between E(T₁) and E(S_n). To illustrate the nonradiative decay processes, the transition states between triplet metal-centered (³MC) and T₁ states have been optimized and were verified with the calculations of vibrational frequencies and intrinsic reaction coordinate (IRC). In addition, the minimum energy crossing points (MECPs) between ³MC and ground states (S₀) were optimized. At last, the potential energy curves relevant to the nonradiative decay pathways are simulated. The results show that complex 3 has the biggest photoluminescence quantum yield because the complex 3 has the biggest radiative decay rate constant and the smallest nonradiative decay rate constant in complexes 1–3.     

新型低GWP高温热泵工质HFO-1234ze(Z)的研究进展

高温热泵可以有效回收工业余热，达到节能减排和保护环境的目的。目前，有关高温热泵技术的研究热点在于寻找一种全球变暖潜能值(GWP)低、使用性能良好的工质，以替代现有CFC-114、HFC-245fa工质。对新型环境友好型工质HFO-1234ze(Z)进行了综述，其GWP＜1，临界温度高于423 K，是一种潜在的高温热泵替代工质。总结了近年来国内外学者对HFO-1234ze(Z)的合成技术、热力学性质、输运性质、传热性能等方面的研究，并分析了HFO-1234ze(Z)在高温热泵系统中应用的可行性，认为HFO-1234ze(Z)在高温热泵中具有较好的工作性能和发展前景。     

Compensation of voltage disturbances using PEMFC supported Dynamic Voltage Restorer

The continuity of supply and quality of power are the two main significant aspects of today’s power delivery system. The Dynamic Voltage Restorer (DVR) is a series connected custom power device which improves the quality of power delivered to the consumers. This paper deals with the effectual exploitation of DVR for interconnecting the proton exchange membrane fuel cell (PEMFC) stack to the grid based on optimized proportional integral (PI) and fuzzy logic (FL) Controller. The real coded Genetic algorithm (GA) is used to optimize the PI controller parameters. The PEMFC operated boost converter is used to boost up the fuel cell output voltage to balance the DC side necessities of the voltage source converter (VSC). The proposed DVR provides balanced and unbalanced voltage sag/swell compensation, harmonic reduction as well as an active power injection to the grid. The designed method also protects the sensitive loads from source side power quality disturbances including short term interruption. In addition, the harmonic compensation performance of the proposed work is validated by comparing with the results of the H^∞ controller based DVR under medium level voltage condition. The simulation results from MATLAB/SIMULINK are discussed to prove the effectiveness of the planned method.     

A review study on titanium niobium oxide-based composite anodes for Li-ion batteries: Synthesis,structure, and performance

The growing demands for Li-ion batteries (LIBs) in the electrification revolution, require the development of advanced electrode materials. Recently, intercalating titanium niobium oxide (TNO) anode materials with the general formula of TiNb_xO_2+2.5x have received lots of attention as an alternative to graphite and Li₄Ti₅O₁₂ commercial anodes. The desirability of this family of compounds stems from their high theoretical capacities (377–402 mAh/g), high safety, high working voltage, excellent cycling stability, and significant pseudocapacitive behavior. However, the rate performance of TNO-based anodes is poor owing to their low electronic and ionic conductivities. TNO-based composites generally are prepared with two aims of enhancing the conductivity of TNO and achieving a synergic effect between the TNO and the other component of the composite. Compositing with carbon matrices, such as graphene and carbon nanotubes (CNTs) are the most studied strategy for improving the conductivity of TNO and optimizing its high-rate performance. Also, for obtaining anode materials with high capacity and high long-term stability, the composites of TNO with transition metal dichalcogenides (TMDs) materials were proposed in previous literature. In this work, a comprehensive review of the TNO-based composites as the anodes for LIBs is presented which summarizes in detail the main recent literature from their synthesis procedure, optimum synthesis parameters, and the obtained morphology/structure to their electrochemical performance as the LIBs anode. Finally, the research gaps and the future perspective are proposed.