Iron stability in drinking water distribution systems in a city of China

A field study on the estimation and analysis of iron stability in drinking water distribution system was carried out in a city of China. The stability of iron ion was estimated by pC-pH figure. It was found that iron ion was unstable, with a high Fe （OH）3 precipitation tendency and obvious increase in turbidity. The outer layer of the corrosion scale was compact, while the inner core was porous. The main composition of the scale was iron, and the possible compound constitutes of the outer scale were α-FeOH, γ-FeOOH, α-Fe2O3, γ-F2O3, FeCl3, while the inner were Fe3O4, FeCl2, FeCO3. According to the characteristics of the corrosion scale, it was thought that the main reason for iron instability was iron release from corrosion scale. Many factors such as pipe materials, dissolved oxygen and chlorine residual affect iron release. Generally, higher iron release occurred with lower dissolved oxygen or chlorine residual concentration, while lower iron release occurred with higher dissolved oxygen or chlorine residual concentration. The reason was considered that the passivated out layer of scale of ferric oxide was broken down by reductive reaction in a condition of low oxidants concentration, which would result more rapid corrosion of the nine and red water phenomenon.

Repulsive firefly algorithm-based optimal switching device placement in power distribution systems

To achieve optimal configuration of switching devices in a power distribution system,this paper proposes a repulsive firefly algorithm-based optimal switching device placement method.In this method,the influence of territorial repulsion during firefly courtship is considered.The algorithm is practically applied to optimize the position and quantity of switching devices,while avoiding its convergence to the local optimal solution.The experimental simulation results have showed that the proposed repulsive firefly algorithm is feasible and effective,with satisfying global search capability and convergence speed,holding potential applications in setting value calculation of relay protection and distribution network automation control.

A Hybrid Decoupled Power Flow Method for Balanced Power Distribution Systems

This paper proposes a hybrid decoupled power flow method for balanced power distribution systems with distributed generation sources. The method formulates the power flow equations in active power and reactive power decoupled form with polar coordinates. Second-order terms are included in the active power mismatch iteration, and constant Jacobian and Hessian matrices are used. A hybrid direct and indirect solution technique is used to achieve efficiency and robustness of the algorithm. Active power correction is solved by means of a sparse lower triangular and upper triangular （LU） decomposition algorithm with partial pivoting, and the reactive power correction is solved by means of restarted generalized minimal residual algorithm with an incomplete LU pre-conditioner. Typical distribution generation models and distribution load models are included. The impact of zero-impedance branches is explicitly modeled through reconfiguring of the adjacent branches with impedances. Numerical examples on a sample distribution system with widespread photovoltaic installations are given to demonstrate the effectiveness of the proposed method.

HPDS133-bus:A Benchmark Test System for Distribution Systems with High Penetration of Distributed Generation

The benchmark test system for distribution systems is necessary and important for system analysis and result data checking.In order to meet the development demand of the distribution systems which integrate with a high penetration of distributed generation(DG),a benchmark test system for the distribution systems which adapts to current and future development trends is proposed.Based on the concentric zone theory and the typical regional settlement model in China,three typical distribution system scenarios corresponding to different system circle structures and regional development characteristics are designed in this paper.In order to adapt to the trend that the distribution systems will present the mixed state of AC and DC,a typical improvement scheme of distribution systems in urban scenario is presented.The benchmark test system of low-voltage distribution systems in a rural scenario is also designed because of the high penetration of DG.Moreover,the system structure,load parameters,integrated capacity and output characteristics of varies types of DG in different scenarios are described in detail.Finally,the simulation results,such as the time series power flow,reliability evaluation and hosting capacity of DGs are given.The benchmark test system proposed in this paper will lay a foundation for future research on distribution systems with a high proportion of DG and effectively support the distribution systems planning,design,operations and dispatches.

Intermittent Arc Fault Detection Based on Machine Learning in Resonant Grounding Distribution Systems

In resonant grounding systems,most single-phaseto-ground faults evolve from IAFs(Intermittent Arc Faults).Earlier detection of IAFs can facilitate fault avoidance.This work proposes a novel method based on machine learning for detecting IAFs in three steps.First,the feature of zero-sequence current is automatically extracted and selected by a newlydesigned FINET(“For IAFs,Neuron Elaboration Net”),instead of traditional feature selection based on time-frequency decomposition.Moreover,data of the zero-sequence current divided by different time windows are successively input into the trained FINET.A proposed PSF(principal-subordinate factor)analyses the results obtained from FINET to improve anti-interference in the mentioned IAF detection algorithm.Experiments using PSCAD/EMTDC software simulation data show the proposed method is feasible and highly adaptable.In addition,the detection result of on-site recorded data demonstrates the effectiveness of the proposed method in practical resonant grounding systems.

Enhancing Security and Privacy in Distributed Face Recognition Systems through Blockchain and GAN Technologies

The use of privacy-enhanced facial recognition has increased in response to growing concerns about data securityand privacy in the digital age. This trend is spurred by rising demand for face recognition technology in a varietyof industries, including access control, law enforcement, surveillance, and internet communication. However,the growing usage of face recognition technology has created serious concerns about data monitoring and userprivacy preferences, especially in context-aware systems. In response to these problems, this study provides a novelframework that integrates sophisticated approaches such as Generative Adversarial Networks (GANs), Blockchain,and distributed computing to solve privacy concerns while maintaining exact face recognition. The framework’spainstaking design and execution strive to strike a compromise between precise face recognition and protectingpersonal data integrity in an increasingly interconnected environment. Using cutting-edge tools like Dlib for faceanalysis,Ray Cluster for distributed computing, and Blockchain for decentralized identity verification, the proposedsystem provides scalable and secure facial analysis while protecting user privacy. The study’s contributions includethe creation of a sustainable and scalable solution for privacy-aware face recognition, the implementation of flexibleprivacy computing approaches based on Blockchain networks, and the demonstration of higher performanceover previous methods. Specifically, the proposed StyleGAN model has an outstanding accuracy rate of 93.84%while processing high-resolution images from the CelebA-HQ dataset, beating other evaluated models such asProgressive GAN 90.27%, CycleGAN 89.80%, and MGAN 80.80%. With improvements in accuracy, speed, andprivacy protection, the framework has great promise for practical use in a variety of fields that need face recognitiontechnology. This study paves the way for future research in privacy-enhanced face recognition systems, emphasizingthe significance of using cutting-edge technology to meet rising privacy issues in digital identity.

A Novel High-Efficiency Transaction Verification Scheme for Blockchain Systems

Blockchain can realize the reliable storage of a large amount of data that is chronologically related and verifiable within the system.This technology has been widely used and has developed rapidly in big data systems across various fields.An increasing number of users are participating in application systems that use blockchain as their underlying architecture.As the number of transactions and the capital involved in blockchain grow,ensuring information security becomes imperative.Addressing the verification of transactional information security and privacy has emerged as a critical challenge.Blockchain-based verification methods can effectively eliminate the need for centralized third-party organizations.However,the efficiency of nodes in storing and verifying blockchain data faces unprecedented challenges.To address this issue,this paper introduces an efficient verification scheme for transaction security.Initially,it presents a node evaluation module to estimate the activity level of user nodes participating in transactions,accompanied by a probabilistic analysis for all transactions.Subsequently,this paper optimizes the conventional transaction organization form,introduces a heterogeneous Merkle tree storage structure,and designs algorithms for constructing these heterogeneous trees.Theoretical analyses and simulation experiments conclusively demonstrate the superior performance of this scheme.When verifying the same number of transactions,the heterogeneous Merkle tree transmits less data and is more efficient than traditional methods.The findings indicate that the heterogeneous Merkle tree structure is suitable for various blockchain applications,including the Internet of Things.This scheme can markedly enhance the efficiency of information verification and bolster the security of distributed systems.

Observer-based dynamic event-triggered control for distributed parameter systems over mobile sensor-plus-actuator networks

We develop a policy of observer-based dynamic event-triggered state feedback control for distributed parameter systems over a mobile sensor-plus-actuator network.It is assumed that the mobile sensing devices that provide spatially averaged state measurements can be used to improve state estimation in the network.For the purpose of decreasing the update frequency of controller and unnecessary sampled data transmission, an efficient dynamic event-triggered control policy is constructed.In an event-triggered system, when an error signal exceeds a specified time-varying threshold, it indicates the occurrence of a typical event.The global asymptotic stability of the event-triggered closed-loop system and the boundedness of the minimum inter-event time can be guaranteed.Based on the linear quadratic optimal regulator, the actuator selects the optimal displacement only when an event occurs.A simulation example is finally used to verify that the effectiveness of such a control strategy can enhance the system performance.

Effects of O3/Cl2 disinfection on corrosion and opportunistic pathogens growth in drinking water distribution systems

The effects of O3/Cl2 disinfection on corrosion and the growth of opportunistic pathogens in drinking water distribution systems were studied using annular reactors （ARs）. The corrosion process and most probable number （MPN） analysis indicated that the higher content of iron-oxidizing bacteria and iron-reducing bacteria in biofilms of the AR treated with O3/Cl2 induced higher Fe304 formation in corrosion scales. These corrosion scales became more stable than the ones that formed in the AR treated with Cl2 alone. O3/Cl2 disinfection inhibited corrosion and iron release efficiently by changing the content of corrosion-related bacteria. Moreover, ozone disinfection inactivated or damaged the opportunistic pathogens due to its strong oxidizing properties. The damaged bacteria resulting from initial ozone treatment were inactivated by the subsequent chlorine disinfection. Compared with the AR treated with Cl2 alone, the opportunistic pathogens M. auium and L. pneumophila were not detectable in effluents of the AR treated with O3/Cl2, and decreased to （4.60 ± 0.14） and （3.09 ± 0.12） loglo （gene copies/g corrosion scales） in biofilms, respectively. The amoeba counts were also lower in the AR treated with O3/Cl2. Therefore, O3/Cl2 disinfection can effectively control opportunistic pathogens in effluents and biofilms of an AR used as a model for a drinking water distribution system.

Dynamic Load Restoration Considering the Interdependencies Between Power Distribution Systems and Urban Transportation Systems

After a major outage,mobile emergency resources(MERs)can be dispatched via the transportation system(TS)for service restoration to critical loads in the power distribution system(PDS).In this case study,the efficiency of service restoration in the PDS is associated with the traffic efficiency of the TS,and vice versa,because the PDS and TS are mutually coupled through traffic lights and MERs.This paper proposes a service restoration method considering interdependency between the PDS and TS,which is formulated as a mixed-integer linear program(MILP).The objective includes maximizing the efficiency of both PDS restoration and TS.By solving the MILP,the dynamic load restoration and MER dispatch strategies can be obtained.For the PDS,the availability of MERs,including mobile sources and repair crews,relates to their dispatch in the TS,and their relationship is formulated as mathematical models.For the TS,the dynamic traffic flow is modeled using the cell transmission model and the effect of traffic lights is considered.Case studies validate the effectiveness of the proposed method.

Characterization of bacterial community and iron corrosion in drinking water distribution systems with O3-biological activated carbon treatment

Bacterial community structure and iron corrosion were investigated for simulated drinking water distribution systems（DWDSs） composed of annular reactors incorporating three different treatments： ozone, biologically activated carbon and chlorination（O3-BAC-Cl2）;ozone and chlorination（O3-Cl2）; or chlorination alone（Cl2）. The lowest corrosion rate and iron release, along with more Fe3O4 formation, occurred in DWDSs with O3-BAC-Cl2 compared to those without a BAC filter. It was verified that O3-BAC influenced the bacterial community greatly to promote the relative advantage of nitrate-reducing bacteria（NRB）in DWDSs. Moreover, the advantaged NRB induced active Fe（III） reduction coupled to Fe（II） oxidation, enhancing Fe3O4 formation and inhibiting corrosion. In addition, O3-BAC pretreatment could reduce high-molecular-weight fractions of dissolved organic carbon effectively to promote iron particle aggregation and inhibit further iron release. Our findings indicated that the O3-BAC treatment, besides removing organic pollutants in water, was also a good approach for controlling cast iron corrosion and iron release in DWDSs.

Fault Line Detection Using Waveform Fusion and One-dimensional Convolutional Neural Network in Resonant Grounding Distribution Systems

Effective features are essential for fault diagnosis.Due to the faint characteristics of a single line-to-ground(SLG)fault,fault line detection has become a challenge in resonant grounding distribution systems.This paper proposes a novel fault line detection method using waveform fusion and one-dimensional convolutional neural networks(1-D CNN).After an SLG fault occurs,the first-half waves of zero-sequence currents are collected and superimposed with each other to achieve waveform fusion.The compelling feature of fused waveforms is extracted by 1-D CNN to determine whether the fused waveform source contains the fault line.Then,the 1-D CNN output is used to update the value of the counter in order to identify the fault line.Given the lack of fault data in existing distribution systems,the proposed method only needs a small quantity of data for model training and fault line detection.In addition,the proposed method owns fault-tolerant performance.Even if a few samples are misjudged,the fault line can still be detected correctly based on the full output results of 1-D CNN.Experimental results verified that the proposed method can work effectively under various fault conditions.

The Averaged-value Model of a Flexible Power Electronics Based Substation in Hybrid AC/DC Distribution Systems

The concept of a flexible power electronics substation(FPES)was first applied in the Zhangbei DC distribution network demonstration project.As a multi-port power electronics transformer(PET)with different AC and DC voltage levels,the FPES has adopted a novel topology integrating modular multilevel converter(MMC)and four-winding medium frequency transformer(FWMFT)based multiport DC-DC converter,which can significantly reduce capacitance in each sub-module(SM)of a MMC and also save space and cost.In this paper,in order to accelerate speed of electromagnetic transient(EMT)simulations of FPES based hybrid AC/DC distribution systems,an averaged-value model(AVM)is proposed for efficient and accurate representation of FPES.Assume that all SM capacitor voltages are perfectly balanced in the MMC,then the MMC behavior can be modeled using controlled voltage sources based on modulation voltages from control systems.In terms of the averaged current transfer characteristics among the windings of the FWMFT,we consider that all multiport DC-DC converters are controlled with the same dynamics,a lumped averaged model using controlled current and voltage sources has been developed for these four-port DC-DC converters connected to the upper or lower arms of the MMC.The presented FPES AVM model has been tested and validated by comparison with a detailed IGBT-based EMT model.Results show that the AVM is significantly more efficient while maintaining its accuracy in an EMT simulation.

Two-dimensional pipe leakage through a line crack in water distribution systems

In water distribution systems,water leakage from cracked water pipes is a major concern for water providers.Generally,the relationship between the leakage rate and the water pressure can be modeled by a power function developed from the orifice equation.This paper presents an approximate solution for the computation of the steady-state leakage rate through a longitudinal line crack of a water distribution pipe considering the surrounding soil properties.The derived solution agrees well with results of numerical simulations.Compared with the traditional models,the new solution allows assessment of all the parameters that related with leakage including the pressure head inside the pipe,hydraulic conductivity,crack size and its position,and pipe size and its depth.

Developing a chloramine decay index to understand nitrification:A case study of two chloraminated drinking water distribution systems

The management of chloramine decay and the prevention of nitrification are some of the critical issues faced by water utilities that use chloramine as a disinfectant.In this study,potential association between high performance size exclusion chromatography（HPSEC）data obtained with multiple wavelength Ultraviolet（UV） detection from two drinking water distribution systems in Australia and nitrification occurrence was investigated.An increase in the absorbance signal of HPSEC profiles with UV detection at λ = 230 nm between apparent molecular weights of 200 to 1000 Da was observed at sampling sites that experienced rapid chloramine decay and nitrification while its absorbance signal at λ =254 nm decreased.A chloramine decay index（C.D.I） defined as the ratio of area beneath the HPSEC spectra at two different wavelengths of 230 and 254 nm,was used in assessing chloramine decay occurrences.The C.D.Is of waters at locations that experienced nitrification were consistently higher than locations not experiencing nitrification.A simulated laboratory study showed that the formation of nitrite/nitrate and/or soluble microbial products and/or the release of extracellular polymeric substances（EPS） during nitrification may contribute to the C.D.I.increase.These findings suggest that C.D.I derived from HPSEC with multiple wavelength UV detection could be an informative index to track the occurrence of rapid chloramine decay and nitrification.

The control of red water occurrence and opportunistic pathogens risks in drinking water distribution systems:A review

Many problems in drinking water distribution systems(DWDSs)are caused by microbe,such as biofilm formation,biocorrosion and opportunistic pathogens growth.More iron release from corrosion scales may induce red water.Biofilm played great roles on the corrosion.The iron-oxidizing bacteria(IOB)promoted corrosion.However,when iron-reducing bacteria(IRB)and nitrate-reducing bacteria(NRB)became the main bacteria in biofilm,they could induce iron redox cycling in corrosion process.This process enhanced the precipitation of iron oxides and formation of more Fe3 O4 in corrosion scales,which inhibited corrosion effectively.Therefore,the IRB and NRB in the biofilm can reduce iron release and red water occurrence.Moreover,there are many opportunistic pathogens in biofilm of DWDSs.The opportunistic pathogens growth in DWDSs related to the bacterial community changes due to the effects of micropollutants.Micropollutants increased the number of bacteria with antibiotic resistance genes(ARGs).Furthermore,extracellular polymeric substances(EPS)production was increased by the antibiotic resistant bacteria,leading to greater bacterial aggregation and adsorption,increasing the chlorine-resistance capability,which was responsible for the enhancement of the particle-associated opportunistic pathogens in DWDSs.Moreover,O3-biological activated carbon filtration-UV-Cl2 treatment could be used to control the iron release,red water occurrence and opportunistic pathogens growth in DWDSs.

Fast restoration of large area breakdown for power distribution systems

An adjacent table-based simplified model of distribution networks containing medium voltage buses of a substation is established.Identification of bus outage and the condition to start fast restoration procedure are discussed.A complex load shading parameter is set up to describe various load shading schemes.The imaginary part of the load shading parameter describes the states of switches of load shading schemes while the real part is the corresponding amount of shaded load.A new concept of independent tripping operation is also put forward.The procedure to search the operation with the least amount of shaded load for a feeder and a connected domain are detailed.The procedure for fast restoration of a large area breakdown of the whole distribution network under emergency states is dealt with using a typical grid distribution network as an example.Results of analysis show that the direct load shading scheme under the most balanced topology is not always the optimal scheme.The proposed method can obtain the optimal operating mode with the least amount of shaded load thus showing its feasibility.

Research on Volt/Var Control of Distribution Networks Based on PPO Algorithm

In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.

STATIONARY DISTRIBUTIONS OF INFINITE PARTICLE SYSTEMS WITH NONCOMPACT STATE SPACE.

This paper deals with the preblem of existence and uniqueness of the stationary distributions (abbr., s. d.'s) for the processes constructed in [4] .The main results are stated in § 1. For the reader's convenience we first restate the existence theorems (Theorem 1 and 2) of the processes given in [4]. Then two existence theorems (Theorem 3 and 4) and a uniqueness theorem (Theorem 5) for the s. d.'s of the processes are presented. The last result (Theorem 6), as an application of the previous ones, is about the Schlgl model which comes from nonequilibrium statisticali physics. The details of the proofs of Theorem 3—6 are given in § 2—4.

Providing Global Awareness in Distributed Dynamic Systems

The paper investigates applicability of the developed high-level model and technology for solution of diverse problems in large distributed dynamic systems which can provide sufficient awareness of their structures,organization,and functionalities.After the review of meanings of awareness and existing approaches for its expression and support,the paper shows application of the Spatial Grasp Model and Technology(SGT)and its basic Spatial Grasp Language(SGL)for very practical awareness solutions in large distributed dynamic systems,with obtaining any knowledge from any point inside or outside the system.The self-evolving,self-replicating,and self-recovering scenario code in SGL can effectively supervise distributed systems under any circumstances including rapidly changing number of their elements.Examples are provided in SGL for distributed networked systems showing how in any node any information about other nodes and links,including the whole system,can be obtained by using network requesting patterns based on recursive scenarios combining forward and backward network matching and coverage.The returned results may be automatically organized in networked patterns too.The presented exemplary solutions are parallel and fully distributed,without the need of using vulnerable centralized resources,also very compact.This can be explained by fundamentally different philosophy and ideology of SGT which is not based on traditional partitioned systems representation and multiple agent communications.On the contrary,SGT and its basic language supervise and control distributed systems by holistic self-spreading recursive code in wavelike,virus-like,and even“soul-like”mode.