Particle swarm optimization applied to integrated demand response resources scheduling

The concept of demand response has a growing importance in the context of the future power systems. Demand response can be seen as a resource like distributed generation, storage, electric vehicles, etc. All these resources require the existence of an infrastructure able to give players the means to operate and use them in an efficient way. This infrastructure implements in practice the smart grid concept, and should accommodate a large number of diverse types of players in the context of a competitive business environment. In this paper, demand response is optimally scheduled jointly with other resources such as distributed generation units and the energy provided by the electricity market, minimizing the operation costs from the point of view of a virtual power player, who manages these resources and supplies the aggregated consumers. The optimal schedule is obtained using two approaches based on particle swarm optimization (with and without mutation) which are compared with a deterministic approach that is used as a reference methodology. A case study with two scenarios implemented in DemSi, a demand Response simulator developed by the authors, evidences the advantages of the use of the proposed particle swarm approaches.

Computing the phase diagram of binary mixtures: A patchy particle case study

We investigate the phase behaviour of 2D mixtures of bi-functional and three-functional patchy particles and 3D mixtures of bi-functional and tetra-functional patchy particles by means of Monte Carlo simulations and Wertheim theory. We start by computing the critical points of the pure systems and then we investigate how the critical parameters change upon lowering the temperature. We extend the successive umbrella sampling method to mixtures to make it possible to extract information about the phase behaviour of the system at a fixed temperature for the whole range of densities and compositions of interest. (C) 2013 AIP Publishing LLC.

Biaxial Nematic Order in the Hard-boomerang Fluid

We consider a fluid of hard boomerangs, each composed of two hard spherocylinders joined at their ends at an angle Psi. The resulting particle is nonconvex and biaxial. The occurence of nematic order in such a system has been investigated using Straley's theory, which is a simplificaton of Onsager's second-virial treatment of long hard rods, and by bifurcation analysis. The excluded volume of two hard boomerangs has been approximated by the sum of excluded volumes of pairs of constituent spherocylinders, and the angle-dependent second-virial coefficient has been replaced by a low-order interpolating function. At the so-called Landau point, Psi(Landau)approximate to 107.4 degrees, the fluid undergoes a continuous transition from the isotropic to a biaxial nematic (B) phase. For Psi not equal Psi(Landau) ordering is via a first-order transition into a rod-like uniaxial nematic phase (N(+)) if Psi > Psi(Landau), or a plate-like uniaxial nematic (N(-)) phase if Psi < Psi(Landau). The B phase is separated from the N(+) and N(-) phases by two lines of continuous transitions meeting at the Landau point. This topology of the phase diagram is in agreement with previous studies of spheroplatelets and biaxial ellipsoids. We have checked the accuracy of our theory by performing numerical calculations of the angle-dependent second virial coefficient, which yields Psi(Landau)approximate to 110 degrees for very long rods, and Psi(Landau)approximate to 90 degrees for short rods. In the latter case, the I-N transitions occur at unphysically high packing fractions, reflecting the inappropriateness of the second-virial approximation in this limit.

Particle agglomeration study in rf silane plasmas: In situ study by polarization-sensitive laser light scattering

To determine self-consistently the time evolution of particle size and their number density in situ multi-angle polarization-sensitive laser light scattering was used. Cross-polarization intensities (incident and scattered light intensities with opposite polarization) measured at 135 degrees and ex situ transmission electronic microscopy analysis demonstrate the existence of nonspherical agglomerates during the early phase of agglomeration. Later in the particle time development both techniques reveal spherical particles again. The presence of strong cross-polarization intensities is accompanied by low-frequency instabilities detected on the scattered light intensities and plasma emission. It is found that the particle radius and particle number density during the agglomeration phase can be well described by the Brownian free molecule coagulation model. Application of this neutral particle coagulation model is justified by calculation of the particle charge whereby it is shown that particles of a few tens of nanometer can be considered as neutral under our experimental conditions. The measured particle dispersion can be well described by a Brownian free molecule coagulation model including a log-normal particle size distribution. (C) 1996 American Institute of Physics.

Environmental impact caused by fungal and particle contamination of Portuguese swine

Social concerns for environmental impact on air, water and soil pollution have grown along with the accelerated growth of pig production. This study intends to characterize air contamination caused by fungi and particles in swine production, and, additionally, to conclude about their eventual environmental impact. Fiftysix air samples of 50 litters were collected through impaction method. Air sampling and particle matter concentration were performed in indoor and also outdoor premises. Simultaneously, temperature and relative humidity were monitored according to the International Standard ISO 7726 – 1998. Aspergillus versicolor presents the highest indoor spore counts (>2000 CFU/m3) and the highest overall prevalence (40.5%), followed by Scopulariopsis brevicaulis (17.0%) and Penicillium sp. (14.1%). All the swine farms showed indoor fungal species different from the ones identified outdoors and the most frequent genera were also different from the ones indoors. The distribution of particle size showed the same tendency in all swine farms (higher concentration values in PM5 and PM10 sizes). Through the ratio between the indoor and outdoor values, it was possible to conclude that CFU/m3 and particles presented an eventual impact in outdoor measurements.

Natural waste materials containing chitin as adsorbents for textile dyestuffs: batch and continuous studies

In this work three natural waste materials containing chitin were used as adsorbents for textile dyestuffs, namely the Anodonta (Anodonta cygnea) shell, the Sepia (Sepia officinalis) and the Squid (Loligo vulgaris) pens. The selected dyestuffs were the Cibacron green T3G-E (CI reactive green 12), and the Solophenyl green BLE 155% (CI direct green 26), both from CIBA, commonly used in cellulosic fibres dyeing, the most used fibres in the textile industry. Batch equilibrium studies showed that the materials’ adsorption capacities increase after a simple and inexpensive chemical treatment, which increases their porosity and chitin relative content. Kinetic studies suggested the existence of a high internal resistance in both systems. Fixed bed column experiments performed showed an improvement in adsorbents’ behaviour after chemical treatment. However, in the column experiments, the biodegradation was the main mechanism of dyestuff removal, allowing the materials’ bioregeneration. The adsorption was strongly reduced by the pore clogging effect of the biomass. The deproteinised Squid pen (grain size 0.500–1.41 mm) is the adsorbent with highest adsorption capacity (0.27 and 0.037 g/g, respectively, for the reactive and direct dyestuffs, at 20ºC), followed by the demineralised Sepia pen and Anodonta shell, behaving like pure chitin in all experiments, but showing inferior performances than the granular activated carbon tested in the column experiments.

Entropy diversity in multi-objective particle swarm optimization

Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly by accessing the final results. In the present paper, a different approach is proposed, by using Shannon entropy to analyzethe MOPSO dynamics along the algorithm execution. The results indicate that Shannon entropy can be used as an indicator of diversity and convergence for MOPSO problems.

On local fractional continuous wavelet transform

We introduce a new wavelet transform within the framework of the local fractional calculus. An illustrative example of local fractional wavelet transform is also presented.

Demand response management in power systems using a particle swarm optimization approach

Competitive electricity markets have arisen as a result of power-sector restructuration and power-system deregulation. The players participating in competitive electricity markets must define strategies and make decisions using all the available information and business opportunities.

Application-specific modified particle swarm optimization for energy resource scheduling considering vehicle-to-grid

This paper presents a modified Particle Swarm Optimization (PSO) methodology to solve the problem of energy resources management with high penetration of distributed generation and Electric Vehicles (EVs) with gridable capability (V2G). The objective of the day-ahead scheduling problem in this work is to minimize operation costs, namely energy costs, regarding he management of these resources in the smart grid context. The modifications applied to the PSO aimed to improve its adequacy to solve the mentioned problem. The proposed Application Specific Modified Particle Swarm Optimization (ASMPSO) includes an intelligent mechanism to adjust velocity limits during the search process, as well as self-parameterization of PSO parameters making it more user-independent. It presents better robustness and convergence characteristics compared with the tested PSO variants as well as better constraint handling. This enables its use for addressing real world large-scale problems in much shorter times than the deterministic methods, providing system operators with adequate decision support and achieving efficient resource scheduling, even when a significant number of alternative scenarios should be considered. The paper includes two realistic case studies with different penetration of gridable vehicles (1000 and 2000). The proposed methodology is about 2600 times faster than Mixed-Integer Non-Linear Programming (MINLP) reference technique, reducing the time required from 25 h to 36 s for the scenario with 2000 vehicles, with about one percent of difference in the objective function cost value.

Complex evolution of a multi-particle system

This paper studies a discrete dynamical system of interacting particles that evolve by interacting among them. The computational model is an abstraction of the natural world, and real systems can range from the huge cosmological scale down to the scale of biological cell, or even molecules. Different conditions for the system evolution are tested. The emerging patterns are analysed by means of fractal dimension and entropy measures. It is observed that the population of particles evolves towards geometrical objects with a fractal nature. Moreover, the time signature of the entropy can be interpreted at the light of complex dynamical systems.

Fractional order modelling of zero length column desorption response for adsorbents with variable particle sizes

This manuscript analyses the data generated by a Zero Length Column (ZLC) diffusion experimental set-up, for 1,3 Di-isopropyl benzene in a 100% alumina matrix with variable particle size. The time evolution of the phenomena resembles those of fractional order systems, namely those with a fast initial transient followed by long and slow tails. The experimental measurements are best fitted with the Harris model revealing a power law behavior.

Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Dynamical behaviour of multi-particle large-scale systems

Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.