Chengke Zhou

Modeling of Load Demand Due to EV Battery Charging in Distribution Systems

This paper presents a methodology for modeling and analyzing the load demand in a distribution system due to electric vehicle (EV) battery charging. Following a brief introduction to the common types of EV batteries and their charging characteristics, an analytical solution for predicting the EV charging load is developed. The method is stochastically formulated so as to account for the stochastic nature of the start time of individual battery charging and the initial battery state-of-charge. A comparative study is carried out by simulating four EV charging scenarios, i.e., uncontrolled domestic charging, uncontrolled off-peak domestic charging, “smart” domestic charging and uncontrolled public charging-commuters capable of recharging at the workplace. The proposed four EVs charging scenarios take into account the expected future changes to the electricity tariffs in the electricity market place and appropriate regulation of EVs battery charging loads. A typical U.K. distribution system is adopted as an example. The time-series data of EV charging loads is taken from two commercially available EV batteries: lead-acid and lithium-ion. Results show that a 10% market penetration of EVs in the studied system would result in an increase in daily peak demand by up to 17.9%, while a 20% level of EV penetration would lead to a 35.8% increase in peak load, for the scenario of uncontrolled domestic charging-the “worst-case” scenario.

Modeling of the Cost of EV Battery Wear Due to V2G Application in Power Systems

This paper presents an analysis of the cost of utilizing battery electric vehicle (BEV) batteries as energy storage in power grids [also known as vehicle-to-grid (V2G)] associated with lessening battery cycle life due to more frequent charging and discharging activities and utilization in elevated ambient temperature. Comparison is made between V2G in the U.K., where annual electricity peak demand is reached in winter, and in China, where peak demand is reached in summer due to the air conditioning load. This paper presents mathematical correlations between charging-discharging, ambient temperature, depth of discharge (DoD), and the degradation of electric vehicle batteries based on manufacturers data. Simulation studies were carried out for V2G in both the U.K. and China. Numerical results show that ambient temperature and DoD of a BEV battery play a crucial role in the cost of battery wear. Lead-acid and NiMH battery powered BEVs are not cost effective in V2G use due to the present electricity tariff. Under the present electricity tariff structure, no vehicles would be cost effective for the peak power sources in China. However, lithium-ion battery powered BEVs are cost effective in the U.K. due to a much longer cycle life.

A Methodology for Optimization of Power Systems Demand Due to Electric Vehicle Charging Load

This paper presents a methodology of optimizing power systems demand due to electric vehicle (EV) charging load. Following a brief introduction to the charging characteristics of EV batteries, a statistical model is presented for predicting the EV charging load. The optimization problem is then described, and the solution is provided based on the model. An example study is carried out with error and sensitivity analysis to validate the proposed method. Four scenarios of various combinations of EV penetration levels and charging modes are considered in the study. A series of numerical solutions to the optimization problem in these scenarios are obtained by serial quadratic programming. The results show that EV charging load has significant potential to improve the daily load profile of power systems if the charging loads are optimally distributed. It is demonstrated that flattened load profiles may be achieved at all EV penetration levels if the EVs are charged through a fast charging mode. In addition, the implementation of the proposed optimization is discussed with analyses on the impact of travel pattern and the willingness of customers.

Load model for prediction of electric vehicle charging demand

Increasing environmental concerns, the decarbonisation of future auto industry, the consequent regulatory requirements and the depletion of oil have made the fuel independent battery electric vehicle (EV), with zero emission increasingly more attractive as practical and economical alternative to the gasoline fuelled car. The expected increasing number of EV connected to power systems for charging will have significant impact on power systems, such as generation capacity, transformer loading level, line congestion level and load profile, among which, the impact of EV charging load on the system load profile claims most attention. This paper develops a methodology to determine the EV battery charging load on the power system load profile. Three scenarios were simulated, comprising uncontrolled charging, controlled off-peak charging and smart charging. The proposed method in this paper takes into account the initial state of charge and start time of EV battery charging. Results show that uncontrolled charging will impose a new peak to the system and may cause congestion issues to local network. Controlled off-peak charging can shift EVs charging load to an off-peak time, however, EV can also introduce a new peak or near peak in early off-peak time. Smart charging method which optimises the start time of EVs charging is the most beneficial charging method to both distribution network operator and EV users.

Analysis of a ferroresonant circuit using bifurcation theory and continuation techniques

In this contribution, the analysis of the dynamics of a ferroresonant circuit are presented using continuation techniques and bifurcation theory. Despite its great simplicity, this circuit can assume a diverse range of steady-state regimes including fundamental and subharmonic ferroresonance, quasiperiodic oscillations, and chaos. The system dynamics are explored through the continuation of periodic solutions of the associated circuit equations. A detailed picture is drawn of various transitions between the individual periodic steady-state regimes of the circuit. Bifurcation points are computed, revealing a clearly defined succession of periodic steady-state regimes, including the Feigenbaum route to chaos through a cascade of period doublings. The analysis presented is performed using the freely available software package XPPAUT. The contribution of this paper is to provide a detailed description of how to define the circuit equations in XPPAUT and how to conduct the interactive bifurcation analysis. The proposed approach is shown to be both computationally efficient and robust, as it eliminates the need for numerically critical and long lasting transient simulations.

Application of K-Means method to pattern recognition in on-line cable partial discharge monitoring

On-line Partial Discharge (PD) monitoring is being increasingly adopted in an effort to improve asset management of the vast network of MV and HV power cables. This paper presents a novel method for autonomous recognition of PD patterns recorded under conditions in which a phase-reference voltage waveform from the HV conductors is not available, as is often the case in on-line PD based insulation condition monitoring. The paper begins with an analysis of two significant challenges for automatic PD pattern recognition. A methodology is then proposed for applying the K-Means method to the task of recognizing PD patterns without phase reference information. Results are presented to show that the proposed methodology is capable of recognising patterns of PD activity in on-line monitoring applications for both single-phase and three-phase cables and is also effective technique for rejecting interference signals.

DSP based partial discharge characterisation by wavelet analysis

This paper reports the results of an investigation of an intelligent DSP-based PD analyzer using wavelet analysis for partial discharge characterisation. The basic theory of wavelet transform is firstly introduced followed by an analysis of the possible applications of the wavelet transform in partial discharge analysis. The practical implementation of such a novel DSP analyzer is then proposed. The advantages of the proposed approach are discussed.

Analysis of Significant Factors on Cable Failure Using the Cox Proportional Hazard Model

This paper proposes the use of the Cox proportional hazard model (Cox PHM), a statistical model, for the analysis of early-failure data associated with power cables. The Cox PHM analyses simultaneously a set of covariates and identifies those which have significant effects on the cable failures. In order to demonstrate the appropriateness of the model, relevant historical failure data related to medium voltage (MV, rated at 10 kV) distribution cables and High Voltage (HV, 110 kV and 220 kV) transmission cables have been collected from a regional electricity company in China. Results prove that the model is more robust than the Weibull distribution, in that failure data does not have to be homogeneous. Results also demonstrate that the method can single out a case of poor manufacturing quality with a particular cable joint provider by using a statistical hypothesis test. The proposed approach can potentially help to resolve any legal dispute that may arise between a manufacturer and a network operator, in addition to providing guidance for improving future practice in cable procurement, design, installations and maintenance.

The effect of Distributed Generation on distribution system reliability

Concerns on environmental and economical issues drive the increasing developments that support small scale generators to be connected close to distribution networks, i.e. distributed generation (DG). However, the connection of DG would affect the distribution system structure and operation greatly. Since these DG sources are normally placed close to consumption centers and are added mostly at the distribution level, the effect of DG on distribution system reliability becomes a growing concern to the customers and electric utilities. This paper analyses the reliability improvement effect of DG on distribution system by comparing the system reliability indices before and after connection of DG. As is known, distribution system consists of hundreds of thousands of components. The acquisition of all component parameters is impossible. Therefore, in this paper, an interval algorithm is introduced to deal with the uncertainty of component data to calculate the interval reliability indices. At last, through comparison of the interval reliability indices when DG connected in different locations on distribution feeder, this paper also analyses the effect of connecting location on distribution system reliability.

Isolation and in vitro culture of zygotes and central cells of Oryza sativa L.

Abstract All component cells of the embryo-sac before and after fertilization in rice were isolated by manual microdissection under conditions either free of enzymes or combined with a short pulse of enzymatic treatment.In general, the frequency of isolated unfertilized or fertilized egg cells or central cells reached 15–40%. Various component cells of the embryo-sac after isolation were distinguished by their own morphological characteristics. The isolated cells were cultured in a microchamber and fed with dividing rice suspension cells. Both unfertilized and fertilized egg cells and central cells were induced to divide. Among them only the fertilized egg cells (the zygotes) developed into proembryo-like multicellular structures. The frequency of the first zygotic division and the frequency of multicellular structures were higher using the non-enzymatic method than using the enzymatic one.