ON THE SINGULAR DIRECTIONS OF VALUE DISTRIBUTION OF HOLOMORPHIC CURVES IN P^n(C)

This article proves the existence of singular directions of value distribution theory for some transcendental holomorphic curves in the n-dimensional complex projective space P^n（C）.. An example is given to complement these results.

Direct Yaw Moment Control for Distributed Drive Electric Vehicle Handling Performance Improvement

For a distributed drive electric vehicle（DDEV） driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control（DYC） has been widely studied and applied to vehicle stability control. Good vehicle handling performance： quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts： a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error（ITAE） function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method： yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.

Size distribution,directional source contributions and pollution status of PM from Chengdu,China during a long-term sampling campaign

Long-term and synchronous monitoring of PMIo and PM2.s was conducted in Chengdu in China from 2007 to 2013. The levels, variations, compositions and size distributions were investigated. The sources were quantified by two-way and three-way receptor models （PMF2, ME2-2way and ME2-3way）, Consistent results were found： the primary source categories contributed 63.4% （PMF2）, 64.8% （ME2-2way） and 66.8% （ME2-Bway） to PMIo, and contributed 60.9% （PMF2）, 65.5% （ME2-2way） and 61.0% （ME2-3way） to PM2.s. Secondary sources contributed 31.8% （PMF2）, 32.9% （ME2-2way） and 31.7% （ME2-3way） to PMIo, and 35.0% （PMF2）, 33.8% （ME2-2way） and 36.0% （ME2-3way） to PM2.s. The size distribution of source categories was estimated better by the ME2-3way method. The three-way model can simultaneously consider chemical species, temporal variability and PM sizes, while a two-way model independently computes datasets of different sizes. A method called source directional apportionment （SDA） was employed to quantify the contributions from various directions for each source category. Crustal dust from east-north-east （ENE） contributed the highest to both PM^o （12.7%） and PMzs （9.7%） in Chengdu, followed by the crustal dust from south-east （SE） for PMao （9.8%） and secondary nitrate ＆ secondary organic carbon from ENE for PMzs （9.6%）. Source contributions from different directions are associated with meteorological conditions, source locations and emission patterns during the sampling period. These findings and methods provide useful tools to better understand PM pollution status and tn dovolon offoctive nolhltion control gtrateMeg.

Distributed adaptive direct position determination based on diffusion framework

The conventional direct position determination（DPD） algorithm processes all received signals on a single sensor.When sensors have limited computational capabilities or energy storage,it is desirable to distribute the computation among other sensors.A distributed adaptive DPD（DADPD）algorithm based on diffusion framework is proposed for emitter localization.Unlike the corresponding centralized adaptive DPD（CADPD） algorithm,all but one sensor in the proposed algorithm participate in processing the received signals and estimating the common emitter position,respectively.The computational load and energy consumption on a single sensor in the CADPD algorithm is distributed among other computing sensors in a balanced manner.Exactly the same iterative localization algorithm is carried out in each computing sensor,respectively,and the algorithm in each computing sensor exhibits quite similar convergence behavior.The difference of the localization and tracking performance between the proposed distributed algorithm and the corresponding CADPD algorithm is negligible through simulation evaluations.

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.

Multi-objective Day-ahead Polarity Switching Optimization for Voltage Unbalance in Bipolar DC Distribution Networks

Bipolar direct current(DC)distribution networks can effectively improve the connection flexibility for renewable generations and loads.In practice,concerns regarding the potential voltage unbalance issue of the distribution networks and the frequency of switching still remain.This paper proposes a day-ahead polarity switching strategy to reduce voltage unbalance by optimally switching the polarity of renewable generations and loads while minimizing the switching times simultaneously in the range of a full day.First,a multi-objective optimization model is constructed to minimize the weighted sum of voltage unbalance factors and the sum of number of switching actions in the day based on the power flow model.Second,a two-step solution strategy is proposed to solve the optimization model.Finally,the proposed strategy is validated using 11-node and 34-node distribution networks as case studies,and a switching and stabilizing device is designed to enable unified switching of renewable generations and loads.Numerical results demonstrate that the proposed strategy can effectively reduce the switching times without affecting the improvement of voltage balance.

Localization of Oscillation Source in DC Distribution Network Based on Power Spectral Density

Direct current(DC)bus voltage stability is essential for the stable and reliable operation of a DC system.If an oscillation source can be quickly and accurately localized,the oscillation can be adequately eliminated.We propose a method based on the power spectral density for identifying the voltage oscillation source.Specifically,a DC distribution network model combined with the component connection method is developed,and the network is separated into multiple power modules.Compared with a conventional method,the proposed method does not require determining the model parameters of the entire power grid,which is typically challenging.Furthermore,combined with a novel judgment index,the oscillation source can be identified more intuitively and clearly to enhance the applicability to real power grids.The performance of the proposed method has been evaluated using the MATLAB/Simulink software and PLECS RT Box experimental platform.The simulation and experimental results verify that the proposed method can accurately identify oscillation sources in a DC distribution network.

Coordination Control of Power Flow Controller and Hybrid DC Circuit Breaker in MVDC Distribution Networks

The two main challenges of medium voltage direct current(MVDC)distribution network are the flexible control of power flow(PF)and fault protection.In this paper,the power flow controller(PFC)is introduced to regulate the PF and inhibit the fault current during the DC fault.The coordination strategy of series-parallel PFC(SP-PFC)and hybrid DC circuit breaker(DCCB)is proposed.By regulating the polarity and magnitude of SP-PFC output voltage during the fault,the rising speed of fault current can be suppressed so as to reduce the breaking current of hybrid DCCB.The access mode of SP-PFC to the MVDC distribution network and its topology are analyzed,and the coordination strategy between SP-PFC and hybrid DCCB is investigated.Moreover,the emergency control and bypass control strategies of SP-PFC are developed.On this basis,the mathematical model of SP-PFC in different fault stages is derived.With the equivalent model of SP-PFC,the fault current of the MVDC distribution network can be calculated accurately.A simulation model of the MVDC distribution network containing SP-PFC is established in MATLAB/Simulink.The fault current calculation result is compared with the simulation result,and the effectiveness of the proposed coordination strategy is verified.

A Scheduling Optimization Technique Based on Reuse in Spark to Defend Against APT Attack

Advanced Persistent Threat （APT） attack, an attack option in recent years, poses serious threats to the security of governments and enterprises data due to its advanced and persistent attacking characteristics. To address this issue, a security policy of big data analysis has been proposed based on the analysis of log data of servers and terminals in Spark. However, in practical applications, Spark cannot suitably analyze very huge amounts of log data. To address this problem, we propose a scheduling optimization technique based on the reuse of datasets to improve Spark performance. In this technique, we define and formulate the reuse degree of Directed Acyclic Graphs （DAGs） in Spark based on Resilient Distributed Datasets （RDDs）. Then, we define a global optimization function to obtain the optimal DAG sequence, that is, the sequence with the least execution time. To implement the global optimization function, we further propose a novel cost optimization algorithm based on the traditional Genetic Algorithm （GA）. Our experiments demonstrate that this scheduling optimization technique in Spark can greatly decrease the time overhead of analyzing log data for detecting APT attacks.

Plug-in Gate-loop Compensators for Series-connected IGBT Drivers in a Solid-state Fault Current Limiter

A solid-state fault current limiter(SSFCL)is the key protective equipment in a direct current distribution network.In order to meet the high voltage requirements and reduce costs,implementing a SSFCL based on series-connected insulated gate bipolar transistors(IGBTs)is a promising approach.However,voltage unbalancing of IGBTs would be introduced if the gateloops of the IGBTs are non-identical.In this paper,a plug-in gate-loop compensator with discrete gate voltage feedback and pulsewidth current compensation is proposed.The main merits are:1)with the plug-in structure,the extra current sources only provide small power to fine-tune the gate-loop without affecting the functions provided by the commercial IGBT gate driver;2)the gate-emitter voltages of IGBTs are compared with the preset thresholds to obtain control criterion,and the pulsewidths of the current sources are controlled for gate-loop compensation,thus both analog-digital and digital-analog converters are avoided;3)the control law is easy to implement in FPGA,and is robust to voltage variation of power-loops.With the proposed compensator,the voltage unbalancing is alleviated immediately at the present switching cycle,and further eliminated cycle-by-cycle during the current limitation process.Experimental results verify the feasibility of the proposed compensator.