In this study, extensive dynamic simulation studies are carried out to explore the impact of synchronous machine (SM)-based distributed generation (DG) integration on existing radial fuse–recloser protection infrastructure. Furthermore, dynamic simulation studies are also conducted to highlight the use of superconducting fault current limiters (SFCLs) to mitigate such an impact. These studies have included the effects of SM-based DG sources on fuse–recloser coordination and recloser sensitivity adequacy. In addition, a comparison between the performances of two different SFCL types has been also offered. The dynamic results of these investigations have shown that the presence of SFCLs has prevented any excessive fault current contribution from SM-based DG sources, as a result, it has restored the fuse–recloser coordination and recloser sensitivity adequacy. Within the frame of reference of the study is the dynamic simulations of a test benchmark that have been conducted using the PSCAD/EMTDC software.

In this paper, a decentralized control strategy for inverter-based distributed generation (DG) is proposed to enhance the accuracy of power sharing under unbalanced load conditions in low-voltage microgrids. The proposed method includes two important saliences: (1) accurate unbalanced current injection from DGs, and (2) reduction of circulating real and reactive powers in an islanded microgrid. The features are complied with the proposed droop strategy utilized in the control system of each phase of DG converters. Based on the proposed triple-droop control strategy, the real power sharing in an AC low-voltage microgrid is significantly improved via P–V control strategy and the reactive power sharing accuracy is enhanced via Q–f control strategy. By this method, the amplitude of the output voltage of each phase of the converters is determined based on the amount of load connected to that phase. In addition, the efficiency of the microgrid is increased due to the circulating current reduction between DGs. A virtual impedance concept is also utilized to improve the accuracy of the proposed power sharing method. The feasibility and effectiveness of the proposed strategy are validated using MATLAB/SIMULINK software for International Council for Large Electric Systems (CIGRE) low-voltage distribution network benchmark.

Traditional distance protection may mal-operate or refuse to operate in the case of non-metallic faults, endangering the safety of power system. Therefore, a new adaptive distance protection scheme based on the impedance complex plane is proposed in this study. First, by utilising the phase relationship between the negative sequence current at the relaying point and the current at the fault point, the fault supplementary impedance angle caused by the fault resistance is calculated. Then, the effective fault impedance from the fault point to the relaying point is obtained by the trigonometric function relationship of the effective fault impedance, measured impedance and fault supplementary impedance on the impedance complex plane. On this basis, the criterion of the adaptive distance protection is constructed. Finally, test results on real-time digital simulator demonstrate that the protection scheme proposed in this study is applicable to various types of faults, and has a good adaptability to different system operating conditions. Compared with traditional distance protection scheme, the proposed scheme is immune to the fault resistance, thus mal-operation or operation-rejection of distance protection caused by the fault resistance could be effectively avoided.

Spot network has very high supply reliability and it is beneficial for integrating distributed energy resources (DERs). In conventional spot network, all the feeders are the sole power source, providing unidirectional power to the secondary network. The equipped network protector prevents power flow from the network to the feeder, to protect the transformer against upstream fault. If there are amounts of DERs injected, excess power inside the network will lead to frequently mistrip of the protector because the cause of reverse power cannot be differentiated. This study presents an improved protection for spot network with high penetration of DERs. It is based on the sequence current component and its power direction. There are various positive and negative components when different types of fault occur at different locations. Based on the sequence current variation, the reverse power caused by fault or by DERs can be differentiated. Then the fault can be located by comparing the sequence power direction among feeders. Based on this theory, the sectionalized bus-bar protection is also discussed. The simulation results prove that the proposed method functions effectively on enhancing the penetration amount of DERs and improving the supply reliability further.

Low-voltage network is concerned on the penetration of low carbon technologies. Distribution transformer thermal capacity is one of the most concerned, due to the aged and capital-intensive nature of the transformer fleet. Extensive studies have been done on this topic, and most of them have applied exiting thermal models such as IEC 60076 thermal model to estimate the hot-spot temperature (HST). However, it is lack of consideration on how accurate the thermal model is or how to refine the thermal model for more accurate estimation of HST. In this study, a methodology is introduced to improve the accuracy of IEC thermal model by refining its thermal parameters based on measured temperature data during the heat run test. Verification of the methodology under one 1 MVA 6.6/0.415 kV distribution transformer shows that the accuracy of predicting the HST is improved by reducing the maximum error from 25.8 to 3.6 K under constant loads and 8.15 to 4.16 K under cyclic loads. Also, a worst-case scenario study under the penetration of electric vehicles (EVs) shows the maximum penetration level of EVs is improved by 9% by applying refined thermal parameters to estimate the HST of the distribution transformer.

The study deals with the determination of the heat losses for a switchgear busbar system. The losses were computed for both naturally ventilated and hermetic switchgear configurations. For each configuration, several levels of current were considered. The heat losses were computed in three ways. The first approach was a direct method that uses the temperatures of the busbar and the surrounding air and the heat transfer coefficient computed from the empirical correlations. In the second algorithm, an energy balance of the switchgear was performed. This approach included convective and radiative heat transfer from the casing and, in the case of ventilated switchgear, the heat removed with the air flowing through the unit. The last method was based on the data obtained from the electrical measurements of the voltage and current on the considered busbar system. An uncertainty analysis was performed to compare the accuracy of the presented approaches and to validate the quality of the solution. The results revealed good agreement between the first two approaches with respect to the electric measurement uncertainty and exhibited the deficiencies of the last one.

In an interconnected bulk power system, wide-area measurement system (WAMS) can provide abundant remote measurement for the coordinated control system. However, WAMS data have obvious time delays, which affect the performance of the control system and should be properly considered. Time-delay stability margin (TDSM) is an index to reflect the maximum delay that a time-delay system can sustain without losing its stability. To construct a coordinated control system based on WAMS data, it is crucial to accurately and rapidly determine the TDSM value. In this paper, a novel Jordan-Taylor-Schur (JTS) approach to determine the TDSM value of power system is proposed. It consists of three, Jordan standardization, Taylor separation and Schur simplification. With the three procedures of this method, the model dimension of time-delay system can be reduced, and the stability criterion derivation can be rebuilt to omit some unnecessary variables so that both the computational efficiency and accuracy can be boosted. Further, it is worth highlighting that the proposed method can be applied to various Lyapunov-based stability criteria to improve their efficiency with small errors. Finally, three power systems with time delays have been used to demonstrate the effectiveness of the proposed method.

Ferroresonance is phenomena, which emerged in case of different circumstances such as short circuit and breaker phase failure. In addition, plant outage is another cause of ferroresonance. Ferroresonance may cause maloperation of some protective devices such as differential protection. In this study, Manitoba hydro network is analysed in power systems computer-aided design/electro-magnetic transient design and control to recognise ferroresonant configurations in case of plant outage. Impact of ferroresonance on maloperation of differential protection is analysed. A static var compensator (SVC) is installed at the mid-point of the network to mitigate ferroresonance. Operation of relay is assessed in the presence of SVC; furthermore, effect of parameters and components of SVC on operation of differential protection is investigated. Then, an adaptive algorithm is designed in differential relay to recognise ferroresonance and prevent maloperation of the relay.

With the growing application of electric vehicles (EVs), it is of great significance to have a deep understanding of EV users driving and charging patterns for charging forecasting. However, the rapid growth scale of EV taxis with charging patterns that are closely coupled with human behaviours of temporal–spatial charging choices was not compatible with most previous coordinated strategies. Unlike the majority of existing approaches, a large volume of second-level EV global positioning system (GPS) data was used to study the behaviour patterns of EV users. In practise, a mobile crowdsensing system that records GPS data and transmits information to the server was deployed in a fleet of electric-taxi cabs in Shenzhen, China, making it possible to record the exact behaviour of each vehicle. Travelling and charging statuses of EVs were recorded and analysed into different characteristics of behaviour for each user. The load forecast methods proved to be more effective with more knowledge of both history and real-time data.

Automatic generation control (AGC) plays an important role in power systems, where it maintains the system frequency and tie-line power flow at their desired values. This study presents a novel symbiotic organisms search (SOS) algorithm in order to optimally design the proportional–integral–derivative (PID) controllers in the AGC of interconnected multiple-area power systems including wind farms uncertainty and system non-linearity. The PID controllers’ parameters define the design variables of the optimisation problem. The SOS algorithm is applied to different objective functions such as integral square error and integral absolute of error. The efficacy of the proposed controller is compared with other competing evolutionary algorithms-based proportional–integral or PID controller. The system performance is evaluated under different operating conditions such as different loading, variation of system parameters, and an addition of wind energy uncertainty. For obtaining realistic responses, real wind speed data that extracted from Zafarana location in Egypt is used in this study. The validity of the proposed controller is extensively confirmed using the simulation results. With the SOS-based PID controllers, the dynamic responses for the AGC of interconnected power systems, including wind farms uncertainty can be further enhanced.

This study proposes a particle filter (PF)-based dual estimation method for tracking the dynamic states of a synchronous generator. The authors consider the situation where the field voltage measurements are not readily available. The PF is modified to treat the field voltage as an unknown input which is sequentially estimated along with the other dynamic states. To exploit the tracking results from the estimator, the authors consider the application of use the estimated field voltage to identify internal failures in the excitation subsystem. The proposed method is tested on a 10-machine, 39-bus system to assess selectivity between estimation for regular external disturbances and both physical failure, and modelling abnormality within excitation system. The presented studies show that the proposed method (i) provides reasonable tracking results for the dynamic states and the field voltage simultaneously, (ii) rapidly tracks minor excitation loss due to exciter internal failure while maintaining selectivity and (iii) is robust to measurement noise.

The transmission capacity of the power grid is growing to meet the increasing electrical load demand in the past few decades. It makes the level of severity that short-circuit current (SCC) exceeds the interruption capability of circuit breakers much higher. To limit SCC, this study proposes a bi-objective optimisation model to determine the optimal tripping transmission lines scheme. In this proposed model, the objectives include the maximal effectiveness on limiting SCC and the minimal adverseness on voltage stability, which evaluate by the sensitivities of SCC and voltage stability margin on the tripping lines. Intelligence algorithms have been applied to solve the similar multi-objective problem. However, the optimisation methods cannot meet the requirement of the real-time application because the full-dimensional set of decision variables including all transmission lines is considered in the optimisation procedure. Thereby, the coordinated optimisation algorithm is adapted to accurately and fast achieve the optimal solution. The case study on the IEEE 39-bus system and a real-world 500 kV network in Guangdong province of China verify the effectiveness and practicality of the proposed method.

Increasing penetration of plug-in electric vehicles (PEVs) in the power system makes a need to consider the impact of PEVs on the transmission expansion planning (TEP) studies especially for large-scale PEV parking lots. Modelling of PEVs (as vehicle to grid (V2G)) is highly dependent on the owner's behaviour. In this study, a systematic method based on multi-state Markov model is utilised to represent the uncertainty of V2G's presence. To investigate the impact of PEVs, a probabilistic TEP in the presence of V2Gs (P_TEP^V2G) is proposed. In the proposed TEP model, the objective function consists of the total line and risk costs (RCs). Moreover, the optimal place and capacity of PEV parking lots are considered as the decision variables. It is assumed that there is an electric vehicle fleet operator for the management of electric vehicles. Because P_TEP^V2G is a complex and non-linear optimisation problem, an improved cuckoo search algorithm (ICS) is utilised to effectively solve the problem. On the IEEE 24-bus system, simulation results show that the availability of the PEVs at the proper bus leads to decreasing RC and deferring construction of new transmission lines.

Power-frequency parameters of long-distance extreme-high-voltage (EHV) and ultra-high-voltage (UHV) transmission lines are the basis of power system modelling and analysis, but these parameters are especially difficult to accurately measure due to the reactance-dominated nature and strong external interference. An accurate power-frequency parameter measurement approach is proposed in this study. The idea is to utilise frequency response curve to indirectly extrapolate transmission line parameters at power frequency. As no direct measurement is conducted at power frequency, the potential power-frequency interference is avoided. A resonance-based measurement method is employed to eliminate the effect of large impedance phase angle of EHV/UHV systems and identify positive- and zero-sequence resistance with enhanced accuracy. In order to validate the effectiveness of the proposed approach, a prototype instrument was developed and used to measure power-frequency parameters of a scale-down laboratory transmission line system. Comparative results confirmed the accuracy priority of the proposed approach over existing power-frequency measurement methods. In addition, the anti-interference performance in terms of the impact of the parallel in-service transmission line also indicates the proposed approach is more advantageous as it has lower capacity requirement on the measurement device.

Unified power flow controller (UPFC) has impact on the performance of distance relay during power swing. Generally, power system's parameters oscillate during power swing and since UPFC operation depends on some of these parameters (bus voltage, active and reactive power), the UPFC injects oscillated series voltage and draws oscillated shunt current. These oscillating series voltage and shunt current influence distance relays, as the impedance seen by a distance relay during power swing changes in UPFC-compensated lines. This study shows how and why series voltage and shunt current change during power swing. Moreover, the admittance swing characteristic is proposed in this study and effects of series and shunt branches of UPFC on the admittance seen by a distance relay during power swing have been examined.

Marine current farm (MCF) equipped with squirrel cage induction generators (SCIGs) influences on the voltage stability of the power network. Thevenin-based voltage instability risk indicator is a simple and local index that can be used for voltage instability prediction from a load or zero injection bus. This indicator is modified to evaluate the voltage stability from MCF bus. In addition, a Thevenin-power flow tracing-based load shedding approach is also presented for preventing voltage instability. The method compares two equivalent Thevenin impedances of the main network and MCF for total active and reactive power calculations. Then, the total values are used for load sharing and load shedding by power flow tracing algorithm. The proposed hybrid method is tested on IEEE 14-bus test system considering different contingencies. The results confirm the capability of the proposed indicator and load shedding approach in timely prediction and proper prevention of voltage instability problems, respectively.

Electric vehicles, EVs, provide temporary distributed energy storage capacity for the evolving distribution grid. An aggregated storage capacity of multiple EVs is more meaningful for a distribution grid. Commercial car parks at metropolitan cities and parking lots (PLs) of hospitals, shopping centres, universities etc. are the potential areas that can be organised for these purposes. This study presents a distributed storage capacity formulation of an EV PL that can be used in distribution system reliability improvement. The storage capacity was determined by sequential Monte-Carlo simulations. Real car arrival-departure data provided by the PL authority of Istanbul, technical parameters (SoC of the batteries, battery capacity of EVs, charging and discharging rates), and some side-specific probabilistic parameters (driver behaviour, mean transportation distance etc.) were used for realistic model development. Special attention was given to some critical time periods when the storage support was more crucial for the utility grid. Moreover, future expectations for city urban planning and for travel behaviour of the community were also included in the model. Finally, impacts of several important parameters on the storage capacity of the PL were determined through sensitivity analysis.

The substantial potential for the integration of renewable energy into power systems using power electronics converters might result in stability issues because of a lack of inertia. For this reason, this study introduces the concept of a virtual synchronous machine (VSM) control algorithm that emulates the properties of traditional synchronous machines. The literature includes references to several differently structured control algorithms. However, synchronous machine inertia and damping characteristics must be mimicked, which makes the cost and simplicity of implementation important from an economic perspective. This study presents a comprehensive comparison of VSM control algorithms. The most significant factor investigated in the work presented in this study is the viability of VSM algorithms during the kind of abnormal operation that might raise instability issues with respect to practical discrete time operation. The test system used in this study, which was simulated in a PSCAD/EMTDC environment, consisted of simulated voltage source converters based on a fully detailed switching model with two AC voltage levels. The results indicate a significant outcome that can facilitate a determination of the most effective VSM control algorithm.

In this study, two current inner products have been defined to implement adaptive single-phase autoreclose for high-voltage transmission lines with shunt reactors. The inner product of fault phase current in shunt reactor and the current in the neutral point reactor is defined as initialisation inner product, and the inner product of the derivative of fault phase current in shunt reactor and the current in the neutral point reactor is defined as compensation inner product. In case of permanent faults and transient faults in the second arc stage, the initialisation inner product will keep bigger than compensation inner product. As for transient faults after arc extinction, low-frequency oscillation is observed in both curves of current inner products which have 90° phase differences; and two curves will have points of intersection. According to this phenomenon, the intersection of two current inner product curves is used to identify fault nature and detect the arc extinction. The proposed algorithm needs no threshold and no calculation in frequency domain. The electromagnetic transients program simulations have verified its correctness and effectiveness.

Regional transmission organisations and independent system operators include different types of security requirements to approximate system security issues. Transmission line contingencies are well handled in state-of-art market models with line outage distribution factors and, at the same time, the impacts of transmission line contingencies are reflected in energy prices. However, there is a lack of efficient mechanisms to handle generator contingencies and reflect the impacts of generator contingencies on energy prices. In this study, a set of security constraints to withstand single-generator-failure contingencies are presented and the market implications are studied. A new component of locational marginal prices, a marginal security component, which is a weighted shadow price of the security constraints, is proposed to better represent energy prices. A 3-bus system example is given to illustrate the market implications. The results are confirmed on a 73-bus system test case.

Demand side management is one of the key topics of smart grids. This study integrates the service computing paradigm in smart grid domain and proposes a demand side personalised recommendation system (PRS). The proposed PRS employs service recommendation techniques to infer residential users’ potential interests and needs on energy saving appliances, and then it recommends energy saving appliances to users, therefore potentially creating opportunities to save energy for the grid. The proposed approach starts by applying a non-intrusive appliance load monitoring (NILM) method based on generalised particle filtering to disaggregate the end users’ household appliance utilisation profiles from the smart meter data. Based on the NILM results, several inference rules are applied to infer the preferences and energy consumption patterns, and to form the user profile. In parallel, information retrieval techniques are applied to extract keywords from the textual appliance advertisements (Ads), and to define the appliance profile. Finally, the similarity measurement method is applied to compare the user profile and appliance profile, to rank the appliance Ad, and to make the recommendations. Experiments are conducted to validate the proposed system.

Penetration of renewable, advanced metering capabilities, and the urge for situational awareness, all calls for power system state estimation (SE). The SE with phasor measurement units (PMUs) is a powerful technique for full system observability. The results of the SE are more accurate, when using PMUs with optimal locations in the complex power systems. In this study, a proposed technique for optimal PMUs placement is discussed and implemented. The optimal PMUs locations will be determined using improved particle swarm optimisation algorithm. This study also presented an optimisation solution technique for the problem of SE using the weighted least square method, improved and based on optimal PMUs placement. A numerical observability analysis is also presented to check the validity of the proposed technique in power system SE based on gain matrix factorisation. The technique applies to the standard IEEE 14-, 30-, and 118-buses systems. The results showed high efficiency and good performance in power system SE when using optimal PMUs locations with full observability.

This study aims to ensure the observability of voltage sags in the entire distribution system (DS) for any short-circuit manifested by the optimal allocation of monitors focusing on power quality. After determining a voltage sag matrix for each type of short-circuit (balanced or unbalanced), a resulting binary matrix is determined which simultaneously observes the voltage sags for all types of faults. Later, a proposal is made to reduce this matrix to decrease the computational effort in large DS. Furthermore, the vulnerability of each node is analysed to establish the monitors’ installation priority. The IEEE 13-nodes distribution test system is used to describe each step of the methodology in detail. Moreover, the IEEE 123-nodes distribution test system is used to validate the results observed so far.

The implementation of a positive sequence model for a squirrel cage induction motor speed control drive for use in time-domain simulations of power systems is addressed. The drive model modulates the motor stator voltage magnitude and frequency to maintain constant rotor speed. A non-ideal operation of the rectifier has been assumed. The performance of the model is assessed using a three-machine nine bus WSCC equivalent system and a test distribution system. To simulate the time-domain behaviour, an independently developed simulation program is used. It shows that the behaviour of the motor model in the independently developed simulation program is comparable and coincident to the behaviour of a motor model in commercial software. Furthermore, the need to include induction motor speed drive models in commercial software to analyse the behaviour of realistic systems is highlighted.

This study proposes a robust optimisation-based optimal scheduling model for microgrid operation considering constraints of islanding capability. The objective is to minimise the total operation cost, including generation cost and spinning reserve cost of local resources as well as purchasing cost of energy from the main grid. To ensure the resiliency of a microgrid and improve the reliability of the local electricity supply, the microgrid is required to maintain enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation when the supply of power from the main grid is interrupted suddenly, i.e. microgrid transitions from grid-connected into islanded mode. Prevailing operational uncertainties in renewable energy resources and load are considered and captured using a robust optimisation method. With proper robust level, the solution of the proposed scheduling model ensures successful islanding of the microgrid with minimum load curtailment and guarantees robustness against all possible realisations of the modelled operational uncertainties. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling model.

For cross-regional transmission projects, the two-part transmission pricing mechanism is suggested so as to promote the sustainable development of cross-regional electricity trading. In the two-part transmission pricing mechanism, appropriately determining the capacity charging ratio (CCR) is an important issue not well solved. Given this background, a Z-number-based risk-minimised negotiation model is developed for a transmission company and a power purchaser to achieve an agreeable CCR under incomplete information. The uncertainty distribution of the future annual electricity transmission quantity is first estimated by the Z-number-based multiple Z-valuations; and then, the benefit and risk loss measured by the well-established conditional value at risk (CVaR) are analysed for the participating two parties. Subsequently, the negotiation model where each negotiator is to minimise its risk loss under a given lowest acceptable benefit constraint and the estimations of the opponent's risk tolerance and negotiation strategy is presented to determine the optimal offer. Finally, the ± 500 kV Xiluodu−Guangdong direct current (DC) transmission project in the southern region of China is employed to demonstrate the basic characteristics of the proposed model.

Increasing penetration rate of renewable energy sources makes it a trend for power system to be dominated by power electronics, which brings challenges for reliability and stability: first, unlike synchronous generator, converters do not have inherent inertia which is important for frequency response. Second, more complex interaction induced by renewable energies causes problems of power system dynamics, for example damping oscillation. In addition, converters cannot support high fault current, leading to limitation of some existing control schemes during transient events. However, compared with converters, synchronous generator has some advantages to solve aforementioned problems. Therefore, this study proposes a synchronous motor-generator pair (MGP) system as a possible grid-connection way for high penetration of renewable energies to improve stability. State equations for analysis of small signal stability are established based on proposed equivalent rotor angle, which is verified by experiment. Results of mode shape analysis and transient simulation show that MGP can effectively enhance frequency response, damp oscillation and isolate and weaken the negative effects brought by wind farm. Effects on damping ratio with different proportions of MGP are also investigated in different penetration rates.

Voltage stability in general is of paramount importance with increasing penetration levels of variable-speed wind power generators (VSWGs) in power systems. Limited knowledge exists considering the impact of VSWGs on long-term voltage stability (LTVS) of power systems, focusing on doubly fed induction generators and full-converter wind generators. This paper presents the results of a comprehensive study on the impact of VSWGs on LTVS. Integration of wind generators while operating the existing synchronous generators improves the LTVS. However, it is unlikely that power systems will retain all existing synchronous generators operating, with high wind penetration levels. Therefore, this study compares the capability of the synchronous generators and VSWGs on LTVS by considering the dynamic reactive power capabilities. The significance of overload capability of synchronous generators on LTVS is highlighted. It is also illustrated that integrating wind farms at remote and local locations from load centres has distinct impacts on LTVS. Replacement of synchronous generators located in close proximity to load centres has a detrimental effect on LTVS. Furthermore, this study demonstrates the impact of different wind generator loading levels on LTVS. The study outcomes highlight several distinct factors which influence the LTVS of power systems with high wind penetration levels.

Smart grids introduce new technological elements into power systems which take prevalent challenges to a new level by shaping parameters of power systems towards a complex regime of uncertainties. Rapid proliferation of advanced metering infrastructure (AMI) and integration of renewable energy sources in smart grids increase system-wide complexities. This study proposes an innovative approach to classify the energy consumptions of smart meter customers with typical profiles by processing with multi-layered clustering of energy consumption data of smart consumers extracted from the AMI. There are two stages for the approach of which the first stage analyses the data for intra-cluster similarity of energy consumption patterns and in case the patterns do not have a high intra-cluster similarity, they are fed back for re-clustering with multi-layered clustering process until the clearly identifiable energy patterns with high intra-cluster similarity is obtained. The second stage linearises the complex energy patterns using interpolant and curve fitting techniques until stabilised profiles are obtained. This study also proposes a methodology for smart meter load modelling for Monte Carlo (MC) simulation applications to reduce the computing time compared with traditional alternatives. This study validates the robustness of the approach and provides the corroboration of the method for MC simulation applications in a smart grid environment.

A modified field-to-line coupling model for simulating the corona effect on the lightning induced voltages of the overhead multi-conductor transmission lines is proposed in this study. Since the model is non-linear, it is solved in an iterative way combining with the time-domain finite-element method and is validated by the measurements of Inoue's experiments. Furthermore, the unconditional stability of the numerical method is theoretically proved. The proposed model is a simplified method according to the method recently proposed by Thang et al., in which finite difference time domain (FDTD) is used to calculate the induced voltages. Compared with FDTD, the proposed model can achieve good efficiency because the transmission line theory is adopted instead of the electromagnetic solution. Both the effects of the corona and the lossy ground on the induced voltage are studied, furthermore, the relationship between the corona effect and the soil conductivity is discussed. The simulation results demonstrate that the corona effect will cause a rise time increase and waveform distortion of the induced voltage, and the magnitudes of induced voltages in the presence of corona discharge are larger than those computed without considering corona.