Plasma catalysis holds great promise for environmental applications, provided that the process viability can be maximized in terms of energy efficiency and product selectivity. This requires a fundamental understanding of the various processes taking place and especially the mutual interactions between plasma and catalyst. In this review, we therefore first examine the various effects of the plasma on the catalyst and of the catalyst on the plasma that have been described in the literature. Most of these studies are purely experimental. The urgently needed fundamental understanding of the mechanisms underpinning plasma catalysis, however, may also be obtained through modelling and simulation. Therefore, we also provide here an overview of the modelling efforts that have been developed already, on both the atomistic and the macroscale, and we identify the data that can be obtained with these models to illustrate how modelling and simulation may contribute to this field. Last but not least, we also identify future modelling opportunities to obtain a more complete understanding of the various underlying plasma catalytic effects, which is needed to provide a comprehensive picture of plasma catalysis.

Understanding plasma catalysis through modelling and simulation—a review

Plasma N2-fixation : 1900-2014

Microwave measurement refers to the acquisition of parameters of a microwave signal or the identification of properties of an object via microwave-based approaches. Thanks to the broad bandwidth and high speed provided by modern photonics, microwave measurement in the optical domain can provide better performance in terms of bandwidth and speed which may not be achievable using traditional, even state-of-the-art electronics. In this tutorial, techniques for photonics-based broadband and high-speed microwave measurement are discussed with an emphasis on the system architectures for microwave signal parameter measurement and object property identification. Emerging technologies in this area and possible future research directions are also discussed.

Photonics-Based Broadband Microwave Measurement

A full time-dependent kinetic study is presented for the main microscopic collisional and radiative processes underlying the optical flashes associated with an impulsive (τ = 5 µs) discharge in the form of a single sprite streamer passing through an air region of the mesosphere at three different altitudes (63, 68 and 78 km). The kinetic formalism developed includes the coupling of the rate equations of each of the different species considered (electrons, ions, atoms and molecules) with the Boltzmann transport equation so that, in this way, all the kinetics is self-consistent, although, in the present approach, the electrodynamics (no Poisson equation is considered) is not coupled. The chemical model set up for air plasmas includes more than 75 species and almost 500 reactions. In addition, a complete set of reactions (more than 110) has been considered to take into account the possible impact of including H2O (humid chemistry) in the generated air plasmas. This study also considers the vibrational kinetics of N2 and CO2 and explicitly evaluates the optical emissions associated with a number of excited states of N2 ,O 2, O in the visible, CO2 in the infrared (IR) and ultraviolet (UV) emissions of sprite streamers due to the N2 Lyman–Birge–Hopfield (LBH) and the NO-γ band systems. All the calculations are conducted for midnight conditions in mid-latitude regions (+38 ◦ N) and 0 ◦ longitude, using as initial values for the neutral species those provided by the latest version of the Whole Atmosphere Community Climate Model (WACCM). According to our calculations, the impact of 4 ppm of H2O is only slightly visible in O − at 68 and 78 km while it strongly affects the behaviour of the anion CO − at all the altitudes investigated. The local enhancement of NOx predicted by the present model varies with the altitude. At 68 km, the concentrations of NO and NO2 increase by about one order of magnitude while that of NO3 exhibits a remarkable growth of up to almost three orders of magnitude. The variation of the O3 density predicted by the model in the sprite streamer head is negligible in all the altitudes investigated. The analysis of the time dependence of the electron distribution function (EDF) in the sprite plasma during the pulse reveals that the EDF transient is quite fast, reaching its ‘steady’ values during the pulse in less than 100 ns (much shorter than streamer head lifetimes). In addition, the calculated EDF during the pulse and in the afterglow is far from being Maxwellian, especially for energetic electrons (with e> 30 eV). Finally, the evaluation of the mid-latitude nighttime electrical conductivity of air plasmas under the influence of a single sprite event reveals an increase of up to four orders of magnitude (at 68 km) above its measured background level of 10 −11 cm −1 at an altitude of ∼70 km. This sudden increase in the electrical conductivity lasts for 100 ms (at 68 km), being shorter (∼1 ms) and longer (1 s) at 63 km and 78 km, respectively. The total power delivered by the streamer head of a single sprite event has been estimated to be approximately 1677 W (at 78 km), 230 kW (at 68 km) and 78 MW (at 63 km). (Some figures in this article are in colour only in the electronic version)

Air Plasma Kinetics Under the Influence of Sprites

In this paper, we discuss the compression of waveforms obtained from measurements of power system quantities and analyze the reasons why its importance is growing with the advent of smart grid systems. While generation and transmission networks already use a considerable number of automation and measurement devices, a large number of smart monitors and meters are to be deployed in the distribution network to allow broad observability and real-time monitoring. This situation creates new requirements concerning the communication interface, computational intelligence and the ability to process data or signals and also to share information. Therefore, a considerable increase in data exchange and in storage is likely to occur. In this context, one must achieve an efficient use of channel communication bandwidth and a reduced need of storage space for power system data. Here, we review the main compression techniques devised for electric signal waveforms providing an overview of the achievements obtained in the past decades. Additionally, we envision some smart grid scenarios emphasizing open research issues regarding compression of electric signal waveforms. We expect that this paper will contribute to motivate joint research efforts between electrical power system and signal processing communities in the area of signal waveform compression.

The Compression of Electric Signal Waveforms for Smart Grids: State of the Art and Future Trends

The mechanisms by which conductive and dielectric nanoparticles (NPs) trap electrons are explained by the potential well distribution caused by induced or polarized charges on NPs. Thus, the distributions of surface and saturation charges on conductive and dielectric NPs are determined. Given conductive Fe3O4, semiconductive TiO2, and dielectric Al2O3 NPs, insulation performance tests are conducted and ionization models of nanofluids (NFs) based on transformer oil are developed. These models are compared with those of NFs based on pure oil. The NP whose conductivity or permittivity does not match that of the dielectric liquid has a potential well and an increased amount of saturation charges on its interface. This NP influences streamer development strongly and enhances the breakdown of oilbased NF.

Effects of conductivity and permittivity of nanoparticle on transformer oil insulation performance: experiment and theory

In order to assess how severe the contamination level of the surface of power line insulators and to prevent unpredictable contamination flashovers, it is important to seek optimal prediction characteristics. That leads to the increase of the warning time and to the improvement of the reliability of the pre-warning system. Nearly 30 insulator strings at five pollution levels were tested in an artificial fog chamber, where their leakage currents were continuously recorded at the same operation conditions. The three characteristics of the leakage current, namely the mean value, maximum value, and the standard deviation of the root-mean-square (RMS) value of the leakage current, have been extracted. They describe jointly the current contamination levels of an insulator surface. In addition, regression equations between the three characteristics and various contamination levels have been established. The same three characteristics have been selected and used as the inputs of a neural network model together with two more parameters, the relative humidity and operating voltage. Also, the influence of each characteristic on the contamination prediction results has been investigated. The model is appropriate to predict the equivalent salt deposit densities (ESDD) with a difference of less than 0.035 mg/cm2 if the training data and the testing data are selected at the security stage. This research results in the optimal prediction input parameters and sufficient pre-warning time before a contamination flashover.

Contamination Level Prediction of Insulators Based on the Characteristics of Leakage Current

A detailed research on the streamer discharge local mechanism is necessary to enhance and develop the streamer theory. In the present paper, the characteristics of a streamer discharge in air at an atmospheric pressure are investigated using a hydrodynamic model based on plasma chemistry. Aside from continuity equations for electrons and ions, as well as Poisson's equation for the electric field, the model includes the electron mean energy density equation and the neutral particle density continuity equation. The electric field strength and the velocities of streamer propagations obtained from proposed model are in good agreement with experimental and simulation results in literature. The mean electron energy is nearly constant in the streamer channel, except for a peak value at the streamer tip. Although the mole fraction of oxygen is only about 0.2 in air, oxygen ions are the dominant charged particles in the streamer discharge. At the electrode surface, the charged particle densities significantly decrease in the direction of the electrode because of surface reactions.

Study of the characteristics of a streamer discharge in air based on a plasma chemical model

This paper presents a numerical method, combined the finite element method in the spatial domain with the finite difference time domain, to calculate the transient impulse response of grounding systems considering the ionization phenomenon. In this numerical method, space-time variable soil resistivity is used to simulate the soil ionization phenomenon where soil resistivity is controlled according to its relationship with the local instantaneous value of the electric field and no a priori hypothesis on the geometrical shape of the ionized region around the electrodes is necessary. Based on the widely accepted principle of dimensional similarity, this paper makes simulated experimental investigations on the impulse-current dispersal regularity of grounding electrodes with various structures. The proposed numerical scheme is validated by comparing computed results with experimental results and simulation results in literature. Based on the measurement and simulation results, the impulse response regularity of grounding electrodes is discussed and the effect of ionization on human and installations safety is reported.

/pdf/numerical-and-experimental-investigation-of-grounding-5fo0fmztyg.pdf

Numerical and Experimental Investigation of Grounding Electrode Impulse-Current Dispersal Regularity Considering the Transient Ionization Phenomenon

This paper proposes a complete and effective smart over-voltage monitoring and identification system. In recent years, smart grids are of the greatest interest in power system research. One of the main features of smart grid is their self-healing, which can continuously carry out online self-evaluation, discover existing faults, and correct them immediately. The over-voltage smart monitoring-identification-suppression systems play a key role in the construction of self-healing grids. In this paper, eight kinds of common over-voltage are discussed and analyzed. The S-transform algorithm is used to extract features of over-voltage. Aiming at the main features of each kind of over-voltage, six different characteristic quantities are proposed. A well designed fuzzy expert system and a support vector machine are employed as the classifiers to build a two-step identification model. The accuracy of the identification system is verified by field records. Results show that this system is feasible and promising for real applications.

/pdf/a-smart-online-over-voltage-monitoring-and-identification-3spenpkme6.pdf

Qing Yang

Papers

Effects of conductivity and permittivity of nanoparticle on transformer oil insulation performance: experiment and theory

Contamination Level Prediction of Insulators Based on the Characteristics of Leakage Current

Study of the characteristics of a streamer discharge in air based on a plasma chemical model

Numerical and Experimental Investigation of Grounding Electrode Impulse-Current Dispersal Regularity Considering the Transient Ionization Phenomenon

A Smart Online Over-Voltage Monitoring and Identification System