THE OPTIMAL ACTIVITY DISTRIBUTION IN NONISOTHERMAL PELLETS

The nonisothermal effectiveness fcator for reaction with kinetics r=kc^m/(l+Kc)~a can be improved bycatalysts with nonuniform activity distribution.The optimal distribution function in one-dimensional modelwith which the effectiveness factor can be maximized is a δ-function which means that the activity of thecatalyst should be concentrated on a layer with negligible thickness in a precise locationfrom the centerof pellets.The general equations for predicting the value ofand maximum effectiveness factor as a functionof thermodynamic,kinetic and transport parameters are derived and they can be given explicitly in the case ofa=O,m=a or isothermal reaction.An active layer with definite thickness and a deviation from the optimal locationboth decrease thevalue of the effectiveness factor.It has been shown numerically that the effectiveness factor decreases slightlywith an active layer at the inner side of x but seriously at outer side.

Developmental Lead Exposure Alters the Distribution of Protein Kinase C Activity in the Rat Hippocampus

Chronic low-level lead (Pb) exposure in children is known to cause a deficit in learning and memory. In vitro studies have demonstrated that Pb altered protein kinase C (PKC) activityt Especially, hippocampal PKC has been correlated with performance in several learning tasks. The effects of Pb exposure on hippocampal PKC were investigated during development at various postnatal ages: postnatal day (PN) 7, 14, 28, and 56. Two-tenth % Pb acetate was administered to pregnant and lactating dams and then administered to weanling rats in drinking water. PKC activity was measured in both membrane and cytosolic fractions from the hippocampi of the controls and Pb-exposed animals. Pb-induced increase in PKC activity in the cytosolic fraction was obsereved in the PN56 rats. In contrast, PKC activity was decreased by Pb at PN7 in the membrane fraction. Furthermore, a significant decrease in the ratio of membrane to cytosolic PKC activity which is representative of PKC distribution was observed in the PN28 and PN56 Pb-exposed rats relative to the same-age controls. This study indicates that chronic Pb exposure during development influences hippocampal PKC activity and distribution. These changes may be involved in the subclinical neurotoxicity of chronic Pb exposure in young children.

Ultrafine Fraction and Aerosol Attached Activity Size Distribution of Radon Progeny in Living Room

Inhalation of 222Rn progeny in the domestic environment contributes the greatest fraction of the natural radiation exposure to the public. The ultrafine activity of these progeny amounts up to about l 0 percent of the total activity （attached and ultrafine）, but is considered to yield about 50 percent of the total radiation dose. Therefore, measurements of ultrafine fraction are essential for the estimation of radiation dose. The current study presents measured data on the total equilibrium equivalent concentration （EEC） and ultrafine equilibrium equivalent concentration （EECUn）, ultrafine fraction （fb）, attached and unattached activity size distributions of radon progeny in the low ventilated rooms at Minia University, Minia city, Egypt. A screen diffusion battery was used for collection the ultrafine fraction and measuring the total activity concentration of radon progeny. The attached activity size distribution of 214pb is determined by using a low pressure cascade impactor. The EEC of radon progeny varied between 1.3 and 18.9 Bq/m3 with a mean value of 5.2 ± 0.48 Bq/m2. The mean activity thermodynamic diameter （AMTD） ofultrafine of radon progeny was determined to be 1.26 nm with relative mean geometric standard deviations （GSD） of 1.3. The ultrafine fraction of radon progeny, fb, has a range 0.01 to 0.21 with an average of 0.08 ± 0.03. A relative mean GSD of 2.7 was determined for attached 2Lapb at a mean active median aerodynamic diameter （AMD） of 350 nm. Based on the above experimental results, the deposition fractions have been evaluated in each air way generation through the human lung by applying a lung deposition model. The bronchial deposition efficiencies of particles in the size range of attached radon progeny were found to be lower than those of ultrafine progeny. The effect of radon progeny deposition by adult male has been also studied for various levels of physical exertion. The dose conversion factor has been discussed as a function of fb.

Diazinon Toxicokinetics, Tissue Distribution and Anticholinesterase Activity in the Rat

The toxicokinetics, tissue distribution, and anticholinesteruse (antiChE ) activity of diazinon were investigated in the rat. Plasma concentrations most adequately fitted a two-compartment open model after iv administration of 10 mg/kg and a one-compartment model after oral administration of 80 mg/kg. Diazinon elimination half-life following iv and oral dosing was 4.70 and 2.86 h, respectively. The oral bioavailabllity was found to be low (35.5%). Hepatic extraction ratios after iv administration of 5 or 10 mg

Optimal Location and Sizing of Distributed Generator via Improved Multi-Objective Particle Swarm Optimization in Active Distribution Network Considering Multi-Resource

In the framework of vigorous promotion of low-carbon power system growth as well as economic globalization,multi-resource penetration in active distribution networks has been advancing fiercely.In particular,distributed generation(DG)based on renewable energy is critical for active distribution network operation enhancement.To comprehensively analyze the accessing impact of DG in distribution networks from various parts,this paper establishes an optimal DG location and sizing planning model based on active power losses,voltage profile,pollution emissions,and the economics of DG costs as well as meteorological conditions.Subsequently,multiobjective particle swarm optimization(MOPSO)is applied to obtain the optimal Pareto front.Besides,for the sake of avoiding the influence of the subjective setting of the weight coefficient,the decisionmethod based on amodified ideal point is applied to execute a Pareto front decision.Finally,simulation tests based on IEEE33 and IEEE69 nodes are designed.The experimental results show thatMOPSO can achieve wider and more uniformPareto front distribution.In the IEEE33 node test system,power loss,and voltage deviation decreased by 52.23%,and 38.89%,respectively,while taking the economy into account.In the IEEE69 test system,the three indexes decreased by 19.67%,and 58.96%,respectively.

Blockchain-Based Power Transaction Method for Active Distribution Network

A blockchain-based power transaction method is proposed for Active Distribution Network(ADN),considering the poor security and high cost of a centralized power trading system.Firstly,the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks.Secondly,considering the transaction needs between users and power suppliers in ADN,an energy request mechanism is proposed,and the optimization objective function is designed by integrating cost aware requests and storage aware requests.Finally,the particle swarm optimization algorithm is used for multi-objective optimal search to find the power trading scheme with the minimum power purchase cost of users and the maximum power sold by power suppliers.The experimental demonstration of the proposed method based on the experimental platform shows that when the number of participants is no more than 10,the transaction delay time is 0.2 s,and the transaction cost fluctuates at 200,000 yuan,which is better than other comparison methods.

EFFECTS OF EXTERNAL DONOR ON ACTIVE CENTER DISTRIBUTION OF SUPPORTED ZIEGLER-NATTA CATALYST

The composition distribution (CD) and microisotacticity distribution (ID) of propene/1-hexene copolymer synthesized by MgCl2/DIBP/TiCl4 (DIBP: diisobutyl phthalate) were determined by fractionating the copolymers according to crystallinity and characterizing the fractions by (CNMR)-C-13. The effects of two alkoxysilane donors, triethoxyphenylsilane (PTES) and dimethoxydi-tert-butylsilane (TBMS), on CD and ID of the copolymers were compared. Three main parts in the CD diagram of each copolymer were distinguished, which were correlated to active center distribution (ACD) based on three groups of different active centers. By studying the changes in l-hexene content, microisotacticity and reactivity ratio product of three typical fractions, the effects of external donor on ACD were better elucidated. It was found that TBMS shows much stronger effects on ACD than PTES. In the former system, most fractions were produced on active centers with relatively lower r(1)r(2), higher reactivity to I-hexene, and higher stereospecificity as compared to the system without external donor. It is concluded that the observed very extensive changes in ACD are mainly resulted by the formation of new types of active centers, possibly by coordination of external donor to certain positions on the catalyst.

DEPENDENCE OF THE DISTRIBUTION OF ACTIVE CENTERS ON MONOMER IN SUPPORTED ZIEGLER-NATTA CATALYSTS

Distribution of active centers(ACD)of ethylene or 1-hexene homopolymerization and ethylene-1-hexene copolymerization with a MgCl_2/TiCl_4 type Z-N catalyst were studied by deconvolution of the polymer molecular weight distribution into multiple Flory components.Each Flory component is thought to be formed by a certain type of active center. ACD of ethylene-1-hexene copolymer with very low 1-hexene incorporation was compared with that of ethylene homopolymer to see the effect of introducingα-olefin on ethyle...

Radioactive Element Distribution Characteristics of Red Mud based Field Road Cement before and after Hydration

Red mud was firstly used as a raw material in sintering field road cement. Then, the radioactive element distribution characteristics of red mud based field road cement（RFC） before and after hydration were comparatively investigated. The experimental results indicated that the specific activity of ^（226）Ra and ^（232）Th increased after sintering process from raw material to clinker, as a result of concentrating effect on ^（226）Ra and ^（232）Th during sintering process, but the specific activity of ^（40）K decreased after sintering process as a result of volatilization effect. Radionuclide ^（226）Ra mainly distributed in RFC silicate phases（C_xS）, ^（232）Th distributed more in RFC interstitial phases than RFC silicate phases（C_xS）, ^（40）K mainly distributed in RFC interstitial phases. With increasing hydration ages of RFC pastes, the specific activity of ^（226）Ra kept increasing, ^（232）Th remained consistency all the same and ^（40）K declined. The radioactivity of RFC was in the recommended safe limit of Chinese National Standards GB6566-2010 during its preparation and application process.

Real-time Operation Optimization in Active Distribution Networks Based on Multi-agent Deep Reinforcement Learning

The increasing integration of intermittent renewable energy sources(RESs)poses great challenges to active distribution networks(ADNs),such as frequent voltage fluctuations.This paper proposes a novel ADN strategy based on multiagent deep reinforcement learning(MADRL),which harnesses the regulating function of switch state transitions for the realtime voltage regulation and loss minimization.After deploying the calculated optimal switch topologies,the distribution network operator will dynamically adjust the distributed energy resources(DERs)to enhance the operation performance of ADNs based on the policies trained by the MADRL algorithm.Owing to the model-free characteristics and the generalization of deep reinforcement learning,the proposed strategy can still achieve optimization objectives even when applied to similar but unseen environments.Additionally,integrating parameter sharing(PS)and prioritized experience replay(PER)mechanisms substantially improves the strategic performance and scalability.This framework has been tested on modified IEEE 33-bus,IEEE 118-bus,and three-phase unbalanced 123-bus systems.The results demonstrate the significant real-time regulation capabilities of the proposed strategy.

A Privacy-preserving Energy Management System Based on Homomorphic Cryptosystem for IoT-enabled Active Distribution Network

Active distribution network(ADN),as a typically cyber-physical system,develops with the evolution of Internet of Things(IoTs),which makes the network vulnerable to cybersecurity threats.In this paper,the eavesdropping attacks that lead to privacy breaches are addressed for the IoT-enabled ADN.A privacy-preserving energy management system(EMS)is proposed and empowered by secure data exchange protocols based on the homomorphic cryptosystem.During the information transmission among distributed generators and load customers in the EMS,private information including power usage and electricity bidding price can be effectively protected against eavesdropping attacks.The correctness of the final solutions,e.g.,optimal market clearing price and unified power utilization ratio,can be deterministically guaranteed.The simulation results demonstrate the effectiveness and the computational efficiency of the proposed homomorphically encrypted EMS.

Leader-follower Optimal Selection Method for Distributed Control System in Active Distribution Networks

Aiming at the shortcomings of a traditional centralized control in an active distribution network(AND),this paper proposes a leader-follower distributed group cooperative control strategy to realize multiple operation and control tasks for an ADN.The distributed information exchange protocols of the distributed generation(DG)group devoted to node voltage regulation or exchange power control are developed using a DG power utilization ratio as the consensus variable.On these bases,this study further investigates the leader optimal selection method for a DG group to improve the response speed of the distributed control system.Furthermore,a single or multiple leader selection model is established to minimize the constraints of the one-step convergence factor and the number of leaders to improve the response speed of the distributed control system.The simulation results of the IEEE 33 bus standard test system show the effectiveness of the proposed distributed control strategy.In addition,the response speed of a DG control group can be improved effectively when the single or multiple leaders are selected optimally.

Joint Planning of Active Distribution Network and EV Charging Stations Considering Vehicle-to-Grid Functionality and Reactive Power Support

This paper proposes a collaborative planning model for active distribution network(ADN)and electric vehicle(EV)charging stations that fully considers vehicle-to-grid(V2G)function and reactive power support of EVs in different regions.This paper employs a sequential decomposition method based on physical characteristics of the problem,breaking down the holistic problem into two sub-problems for solution.Subproblem I optimizes the charging and discharging behavior of autopilot electric vehicles(AEVs)using a mixed-integer linear programming(MILP)model.Subproblem II uses a mixed-integer secondorder cone programming(MISOCP)model to plan ADN and retrofit or construct V2G charging stations(V2GCS),as well as multiple distributed generation resources(DGRs).The paper also analyzes the impact of bi-directional active-reactive power interaction of V2GCS on ADN planning.The presented model is tested in the 47-node ADN in Longgang District,Shenzhen,China,and the IEEE 33-node ADN,demonstrating that decomposition can significantly improve the speed of solving large-scale problems while maintaining accuracy with low AEV penetration.

Decentralized control in active distribution grids via supervised and reinforcement learning

While moving towards a low-carbon, sustainable electricity system, distribution networks are expected to host a large share of distributed generators, such as photovoltaic units and wind turbines. These inverter-based resources are intermittent, but also controllable, and are expected to amplify the role of distribution networks together with other distributed energy resources, such as storage systems and controllable loads. The available control methods for these resources are typically categorized based on the available communication network into centralized, distributed, and decentralized or local. Standard local schemes are typically inefficient, whereas centralized approaches show implementation and cost concerns. This paper focuses on optimized decentralized control of distributed generators via supervised and reinforcement learning. We present existing state-of-the-art decentralized control schemes based on supervised learning, propose a new reinforcement learning scheme based on deep deterministic policy gradient, and compare the behavior of both decentralized and centralized methods in terms of computational effort, scalability, privacy awareness, ability to consider constraints, and overall optimality. We evaluate the performance of the examined schemes on a benchmark European low voltage test system. The results show that both supervised learning and reinforcement learning schemes effectively mitigate the operational issues faced by the distribution network.

North-South Asymmetry of the Interplanetary Magnetic Field Magnitude and the Geomagnetic Indices

Data of the daily interplanetary magnetic field (IMF), and the geomagnetic indices (aa, Ap, Kp, and DST) have been used to examine the asymmetry between the solar field north and south of the heliospheric current sheet, over the period (1975-2013). It important to note that during the positive polarity epochs: (T) refers to Toward the South of the heliospheric current sheet (Southern Hemisphere), and (A) refers to Away from North of the heliospheric current sheet (Northern Hemisphere). While, during the negative polarity epochs the opposite will be happened. The present study finds no clear indication of the presence of north-south asymmetry in the field magnitude, and also there is no magnetic solar cycle dependence that is evident. During the considered period, the north-south asymmetry for the considered parameters reaches maximum values around the declining phase or near to the minimum of the solar cycle. The geomagnetic indices have a clear asymmetry during the positive solar magnetic polarity period (qA > 0) and have a northern dominance during cycles (22 & 23) and southern dominance during cycles (21 & 24). From the power spectrum density, the considered parameters showed significant peaks which appeared in the north-south asymmetry but the 10.7 yr solar cycle was absent. In addition, the main periodicity of the asymmetry may be 5.2, 4.0 and 3.3 years that exist in the parameters with higher confidence levels. Finally, one can conclude that the asymmetry of the interplanetary parameters and the geomagnetic indices may provide multiple causes for producing the observed asymmetric modulations of cosmic rays.

Smart Transformer/Large Flexible Transformer

Solid-state transformer-based smart transformer(ST)can provide the dc connectivity and advanced services to improve the grid performance and to increase the penetration of the power electronics interfaced resources(e.g.,distributed generators and electric vehicle charging stations)in modern electricity distribution grids.Since the ST is a new and effective paradigm of the electricity grid evolution to well understand the ST,this paper systematically presents the basic architecture and the typical control schemes of the ST and then the advanced services that ST can provide to improve the electricity grids performances in terms of the power flow control,power quality improvement,active damping and active contribution to improve distribution grid resilience by means of enabling autonomous microgrids operation as well as launching a restoration procedure following a general blackout.

Kinetic analysis and modeling of maize straw hydrochar combustion using a multi-Gaussian-distributed activation energy model

Combustion kinetics of the hydrochar was investigated using a multi-Gaussian-distributed activation energy model(DAEM)to ex-pand the knowledge on the combustion mechanisms.The results demonstrated that the kinetic parameters calculated by the multi-Gaussian-DAEM accurately represented the experimental conversion rate curves.Overall,the feedstock combustion could be divided into four stages:the decomposition of hemicellulose,cellulose,lignin,and char combustion.The hydrochar combustion could in turn be divided into three stages:the combustion of cellulose,lignin,and char.The mean activation energy ranges obtained for the cellulose,lignin,and char were 273.7-292.8,315.1-334.5,and 354.4-370 kJ/mol,respectively,with the standard deviations of 2.1-23.1,9.5-27.4,and 12.1-22.9 kJ/mol,re-spectively.The cellulose and lignin contents first increased and then decreased with increasing hydrothermal carbonization(HTC)temperature,while the mass fraction of char gradually increased.

Two-stage Optimization for Active Distribution Systems Based on Operating Ranges of Soft Open Points and Energy Storage System

Due to the lack of flexible interconnection devices,power imbalances between networks cannot be relieved effectively.Meanwhile,increasing the penetration of distributed generators exacerbates the temporal power imbalances caused by large peak-valley load differences.To improve the operational economy lowered by spatiotemporal power imbalances,this paper proposes a two-stage optimization strategy for active distribution networks(ADNs)interconnected by soft open points(SOPs).The SOPs and energy storage system(ESS)are adopted to transfer power spatially and temporally,respectively.In the day-ahead scheduling stage,massive stochastic scenarios against the uncertainty of wind turbine output are generated first.To improve computational efficiency in massive stochastic scenarios,an equivalent model between networks considering sensitivities of node power to node voltage and branch current is established.The introduction of sensitivities prevents violations of voltage and current.Then,the operating ranges(ORs)of the active power of SOPs and the state of charge(SOC)of ESS are obtained from models between networks and within the networks,respectively.In the intraday corrective control stage,based on day-ahead ORs,a receding-horizon model that minimizes the purchase cost of electricity and voltage deviations is established hour by hour.Case studies on two modified ADNs show that the proposed strategy achieves spatiotemporal power balance with lower cost compared with traditional strategies.

Mineralogical and Active Mechanical Excitation Characteristics of Filled Fly Ash Cementitious Materials

To reveal the influence of mechanical activation on the performance of fly ash, the microanalysis（the energy spectroscopy, XRD and SEM）, the distribution size of particle of fly ash and cement paste intensity of various age for different grinding time were studied. The relationships of the activity and the composition of fly ash, microstructure and the distribution of particle size by mechanical activation of fly ash were obtained. The internal glass beads with activity were released by grinding fly ash for a certain time. The particle specific surface area was improved and the hydration reaction of the interface and the surface active center was increased by grinding. The granularity distributing of fly-ash trended towards optimization. The polar molecules or ions were easier to intrude into the internal cavity of the vitreous body. The active silica and alumina of fly ash were rapidly depolymerized. Each performance index of fly ash was increased before grinding for 20 min. Cement paste intensity of various age increased along with the grinding time, and the early strength increase range was big, but the later period intensity increase range hastened slightly. The internal part of vitreous of fly ash was destroyed if the fly ash continued to be ground and the activity of fly ash was reduced. It is suggested that Guozhuang＇s fly ash should be ground for 20 min.

Two-stage Optimal Dispatching of AC/DC Hybrid Active Distribution Systems Considering Network Flexibility

The increasing flexibility of active distribution systems(ADSs)coupled with the high penetration of renewable distributed generators(RDGs)leads to the increase of the complexity.It is of practical significance to achieve the largest amount of RDG penetration in ADSs and maintain the optimal operation.This study establishes an alternating current(AC)/direct current(DC)hybrid ADS model that considers the dynamic thermal rating,soft open point,and distribution network reconfiguration(DNR).Moreover,it transforms the optimal dispatching into a second-order cone programming problem.Considering the different control time scales of dispatchable resources,the following two-stage dispatching framework is proposed.d dispatch uses hourly input data with the goal(1)The day-ahea of minimizing the grid loss and RDG dropout.It obtains the optimal 24-hour schedule to determine the dispatching plans for DNR and the energy storage system.(2)The intraday dispatch uses 15-min input data for 1-hour rolling-plan dispatch but only executes the first 15 min of dispatching.To eliminate error between the actual operation and dispatching plan,the first 15 min is divided into three 5-min step-by-step executions.The goal of each step is to trace the tie-line power of the intraday rolling-plan dispatch to the greatest extent at the minimum cost.The measured data are used as feedback input for the rolling-plan dispatch after each step is executed.A case study shows that the comprehensive cooperative ADS model can release the line capacity,reduce losses,and improve the penetration rate of RDGs.Further,the two-stage dispatching framework can handle source-load fluctuations and enhance system stability.