This study proposes a new technique which detects fault on the line, identifies faulty circuit/line-section and estimates location of fault (fault localisation) on the double-circuit three-terminal transmission line. The fault detection and faulty circuit/line-section identification has been carried out by estimating the superimposed components of current at remote end with reference to all the three terminals. Subsequently, the estimation of fault distance is performed by utilising phase angle of voltage and current at the fault point. The performance of the proposed technique has been evaluated by simulating 400 kV double-circuit three-terminal transmission line network using PSCAD/EMTDC software package. The results indicate that the presented technique is able to detect as well as recognise the faulty circuit/line-section correctly even in case of occurrence of a high resistance ground fault near the tap point. At the same time, it is also capable of estimating the precise value of fault location as the percentage error remains within ±1.3%, even under wide variation in system and fault parameters. The proposed technique is also valid for cross-country faults and its accuracy remains consistent even with considerable errors in the measurement of current transformers and capacitive voltage transformers.

Accurate and prompt transient stability prediction is one of the effective ways to reduce the risk of blackout or cascading failures. In an effort to achieve improvements in time efficiency and prediction accuracy, a new transient stability prediction method combining trajectory fitting (TF) and extreme learning machine (ELM) based on two-stage process, named hybrid method, is proposed here. ELM-based method is implemented in central station to ensure the time efficiency, while TF-based method is adopted in local station to guarantee the accuracy. Furthermore, data corruption is taken into consideration to assure the robustness of the proposed algorithm. The hybrid method is validated with the New England 39-bus test system and the simulation results indicate its effectiveness and reliability.

Frequency response analysis (FRA) is a usual method for diagnosing winding, core, insolation faults in transformer. By the change of the FRA traces, the faults can be detected. This study presents the interpretation on influence of untested winding's fault. A special power transformer of rating 10 kV/400 V, three-phase, 50 Hz, YNyn0 has been developed for carrying out FRA tests by practically simulated various winding faults in different phase. The windings of phase ‘A’ and phase ‘B’ on HV side are tested with different types of faults, respectively. The results of these experiments are displayed and discussed. It shows that when the untested winding is shorted, the influence of the inductive fault can be eliminated.

Here, the optimal placement and sizing of electric vehicle charging stations (EVCSs) are presented. High penetration of electric vehicles (EVs) and resulted losses in network would consequently impose more complexity to solution of application problem of EVCSs. To overcome this problem, the model would consider the incentive-based demand response programmes (DRPs), which is handled by particle swarm optimisation algorithm. Minimising investment cost, connection cost, total cost of losses, and demand response (DR) cost are the objective functions of this problem here. Finally, the proposed model is applied to a test system and results are discussed. By comparing the results obtained through different scenarios, it is concluded that the application of DRP results in a distinct reduction in grid losses and total costs.

Efficiency pursuit of the distribution system operation should be on the premise of security. This study proposes the network reconfiguration (NR) approach comprehensively considering N−1 security and network loss. A new approach called distribution system security region (DSSR) is first applied in NR problem. The DSSR is the feasible operation space of a system within N−1 security criterion and can quantify the N−1 security margin. Then, the NR is formulated by using the minimum network loss as objective function and the N−1 security margin, which is provided by the DSSR, as constraints. Moreover, the security margin constraints can be customised for each feeder individually, yielding proper compromises between security-related and efficient concerns. Different NR results for multiple security and efficiency requirements are presented on an extended IEEE-RBTS test system. Compared with the traditional minimum-loss NR, the proposed approach reduces the network loss as much as possible with desired security margin, well balancing the security and efficiency of NR.

The authors propose a novel modification of the conventional Newton–Raphson load flow solver for characterisation of the maximal system loadability. Within the proposed approach, the standard power flow equations are extended with (i) an algebraic representation of maximal and minimal voltage level conditions and (ii) with the so-called transversality condition restricting the set of solutions to the boundary of the solvability region. Solutions to this extended system of equation characterise the maximal load levels for which the solution of power flow equations exists and satisfies the standard feasibility constraints on voltage levels. The resulting system of equations is non-singular and can be solved with just a few standard Newton–Raphson type iterations. Different possible choices of transversality conditions are discussed together with fast algorithms for evaluating the transversality conditions and their gradients. Implementation of the algorithm is described in detail, and its performance is validated on several IEEE cases.

The massive development of energy storage systems (ESSs) may significantly help in the supply–demand balance task, especially under the existence of uncertain and intermittent sources of energy, such as solar and wind power. Using ESSs as complements of renewable generation has technical and economic consequences in both the short-term operation and the long-term expansion planning of the grid. The authors propose a transmission expansion planning model that incorporates decisions about the expansion of generic ESS units in order to study the interaction between the penetration and location of ESSs and the transmission investment decisions. The problem is formulated as a mixed-integer linear programming model and considers different demand blocks and their correlation with renewable generation, to account for the distinct features of the system over time. The authors' results show that ESSs are not only substitutes of transmission assets, but they may also be complemented with transmission assets depending on the power system characteristics. They use a 27-bus representation of the main Chilean network to illustrate the model proposed and to highlight some interesting results about the potential complementarity of ESSs and transmission expansion.

Power system security is a major concern in real-time operation. It is essential to protect the system from blackout by taking proper control actions. This study proposes a boosting algorithm for the precise and accurate prediction of static security assessment of power systems using synchronised measurements. In addition to security status, the proposed approach also predicts the type of violations which may be either line overload/voltage violation or both of the insecure operating conditions. To overcome the computational complexity, the number of input phasor measurements is reduced by a statistical approach based on class separability and correlation coefficient indices. In the classification stage, support vector machines (SVMs) are used as weak classifiers and a strong classifier is constructed as the linear combination of many weak SVM classifiers. The performance of the Adaptive Boosting (AdaBoost) algorithm is further improved by a new weight updation strategy using fuzzy clustering thresholding technique. The efficiency of the proposed approach is demonstrated on IEEE 14-bus, IEEE 30-bus, and Indian 246-bus systems. Further, the test results reveal that the proposed method of security assessment performs better than the other traditional classifiers viz. SVM, feed forward neural network and k-nearest neighbour classifier.

Different from the synchronisation stability for alternating current (AC) systems, the potential risk caused by the interaction between different terminals in voltage source converter-based multi-terminal direct current (VSC-MTDC) grids is emerging, which may impose negative influences on system operation and control. Focusing on this topic, a comprehensive modal analysis is presented to analyse and characterise the dynamic behaviours and interactions of VSC-MTDC grids. The state-space model of VSC-MTDC grids associated with AC systems is developed and participation factor analysis is utilised to identify the physical source of the oscillation modes. This study investigates the voltage fluctuations in VSC-MTDC grids induced by the oscillation modes with the application of extended participation factors. A Monte Carlo-based statistic method has been adopted for the calculations. The interactions between different terminals are identified using mode shape analysis, and quantitative calculation of eigenvalue sensitivities is presented to assess the effect of parameter variation on modal shift. Furthermore, an approach based on the singular value decomposition is proposed for the quantitative analysis of the interaction strength among different control loops. Simulations on a multi-terminal test system are carried out to verify the analytical results.

This study proposes a generalised Hopfield neural network (GHNN) for solving non-linear load flow equations. The proposed method was formulated with appropriate energy function for performing load flow analysis of n-bus system. The intended method has the advantages of simple to use, more general application, faster convergence and better optimal solution over the conventional method of load flow using Newton–Raphson (NR) technique. The proposed method of GHNN has been used to solve the power flow equation by calculating the power mismatches and this constraint is used to formulate the energy function of Hopfield neural network (HNN). This energy function is used to derive the weights and bias values of the network. The optimal solution can be found, based on the minimisation of the energy function of continuous HNN. The suggested method was tested in a typical 3-bus and 5-bus power system. The mathematical equation of the proposed method was coded using Matlab/R2014a software. The simulation results obtained have shown that the proposed method is more efficient than NR method in terms of reduction in computational complexity and convergence time with minimum number of iterations.

An efficient controller design is essential to damp out the rotor speed oscillations for real-life power systems during nominal and faulty conditions. This study presents a decentralised non-linear state observer and controller scheme for power system stabilisers (PSS). Conventional PSS designs are based on linearised models of power system, which is then followed by gain scheduling to cover the complete operating region. Here, the authors propose a derivative-free state-dependent Riccati equation (SDRE) controller and observer scheme for the PSS. Unlike the conventional methods, the proposed scheme is directly based on non-linear models and does not require linearised models. For the proposed SDRE scheme, the non-linear power system model is first converted in state-dependent coefficient form; then the SDRE controller is designed to achieve the desired performance. The SDRE observer is designed to estimate the states of the power systems based on output information; finally, the estimated states are fed back to the SDRE controller. The proposed combined SDRE observer–controller scheme is tested on a 68-bus benchmark system and is compared with the conventional control scheme. Extensive simulations are performed to show the efficacy of the proposed scheme under nominal and faulty conditions.

As the most common precipitation form, rain-lead corona problems are inevitably faced by designers of transmission lines. Through long-term observations of corona inception process under rain conditions by ultraviolet camera, a definition of minimum steady corona inception voltage is presented, which is more useful for practical application. To predict the minimum steady corona inception voltage, water droplet deformation model of smooth conductor is promoted based on the principle of minimising energy in this publication, which takes the influence of electric field force into consideration. Critical breakdown voltage and corresponding critical geometric dimensions of specific water droplet are calculated through the deformation model. The accuracy of the presented deformation model is proved to be >95%, by verification tests performed in a corona cage. Corona discharge model presented in the previous work is adopted to predict the water droplet corona inception voltage of given geometric dimensions. Finally, through the calculation results of both models, the defined minimum steady corona inception voltage of smooth conductor is calculated when there exist rain droplets on conductor lower surface. Also, the calculation error of minimum steady corona inception voltage is ∼8.0% when compared with the validation experiments.

Power losses in a distribution system are commonly minimised via optimal network reconfiguration (NR). Previously, research on NR was focused on planning, where the final configuration reporting the lowest power losses being the main goal. However, power losses during switching operations from the original state to the optimal state of configuration were not considered. This study discusses the optimal switching path for minimising power losses when reconfiguring a network. The simultaneous optimal NR and distributed generation (DG) output was also proposed. The proposed methodology involves: (i) optimal NR and DG output simultaneously and (ii) optimal switching path to convert the network from the initial configuration to the final configuration obtained from (i). The selected optimisation technique in this study is the firefly algorithm. The proposed method was tested using IEEE 33-bus, 69-bus, and 118-bus radial distribution networks, while also accounting for static and dynamic loads. The results confirmed the effectiveness of the proposed method in determining the optimal path of switching operations, as well as the optimal network configuration and optimal output of DG units.

The installation of photovoltaic (PV) systems is gaining great attention due to the matured PV technology and the lowered price of PV modules. With an increasing penetration of PV systems, the selectivity of distribution network protection may be affected which results in undesirable de-energisation of loads, damage of network equipment, and reduction of reliability. This study presents a method to preserve the protection coordination considering future PV systems installation with any penetration level and different locations along the distribution feeder. Depending on the accessibility of protection device settings or PV control parameters, the proposed method modifies the existing characteristic curve of overcurrent devices or limits the output current of PV sources, respectively. The proposed strategy does not change the structure of existing distribution network protection system and can also be implemented in the old and non-programmable relays. Meanwhile, it does not need the communication links. The merits of the proposed method are demonstrated through several case studies using the Isfahan distribution network.

In order to diagnose the ablation characteristics of circuit breakers, the dynamic contact resistance measurement (DRM) has been proposed for almost 20 years. The dynamic resistance curves are easily influenced by two factors: injected current and opening velocity. The two factors are greatly affected the curves and may led a wrong diagnosis in DRM tests. Through analysis of the influence factors, an experimental model is used to simulate the opening process of the breaker in this study. The effective contact area of contact finger which is used in the experimental model under different velocities and current are measured by using the laser scanning microscope. The measurement proves that the changing of effective contact area plays determinative roles in the influencing of injected current and opening velocity. Then, the kernel partial least squares regression method is used to establish the model formula between influencing parameters and the dynamic contact resistance to realise the prediction of the dynamic contact resistance curves. Furthermore, the prediction model also can be used in other current carrying dry sliding friction conditions.

Stability assessment of a lossy power system during a transient is challenging because of the stringent time limit for a conclusion to reliably support protection functions. A coverage-based stability assessment is pursued with focus on resolving computation and scalability issues. This approach involves online tracking of each generator's electromechanical state using a local quasi-steady-state sinusoidal measurement model, and determining whether the state is enclosed in an offline-computed post-fault region of attraction (RoA) at the time the RoA is established by a protection action. The RoA is numerically estimated offline with a scalable ellipsoidal expansion algorithm, and the need for the expansion is delineated. The approach to transient stability assessment is tested on a lossy 68-bus system subject to transmission faults. The study concludes that the coverage-based stability assessment can offer significant advantages in both reliability and swiftness over the existing assessment methods.

The goal of contingency ranking is to accurately choose a list of critical contingencies and rank them due to their severity. In this study, two novel and effective approaches are presented for contingency ranking. The first method proposes a static voltage stability based index which is calculated from the modal analysis and the branch participation matrix. Based on average participation factor for each line, the average branch influence factor is calculated and then root sum square index is applied to rank the contingencies. The second approach is based on dynamic voltage stability. The method employs the largest Lyapunov exponent, a stability tool adapted from the theory of chaos and non-linear dynamical system, for time series. Time-series data of the weakest bus voltage are employed for the largest Lyapunov exponent computing and based on this quantity, contingency ranking will be carried out. Test results on the IEEE 14 bus system are presented and compared with three previous indices to show the effectiveness of both methods.

There is an urgent need for constructing adequately accurate standard reduced-order models of various renewable sources for fast assessment of the stability and security of power grids. This study focuses on this theme considering solar-photovoltaic generators (SPVGs). The main objectives of this study include the construction of a valid reduced-order dynamic model for SPVGs, analysis of the impact of the SPVG model on the stability of the host power system in a mixed mode generation under various integration scenarios, and evaluation of the consistency of SPVGs with fault-ride through requirements based on relevant grid codes. Various modes of operations of SPVGs are analysed and considered using an enhanced search algorithm for maximum power point tracking. In addition, this study proposes an algorithm for the estimation of the maximum penetration level of SPVGs constrained by the small-signal stability of power systems. The results presented in this study are based on dynamic simulation and validation using the MATLAB, PSAT, and ETAP-software environments for stability assessment of power systems. The results show that the developed reduced-order model indicates an acceptable accuracy accompanied with simplicity in simulating complex dynamic performances of host power systems with SPVGs integration.

In a modern interconnected power system, it is challenging to estimate the amount of power delivered to loads through the transmission lines due to the individual associated generator. This study presents a mathematical approach which helps in the development of an important tool viz. power contribution coefficient, via which the share of power generated from an individual generator and delivered to the rest of the power system network has been traced efficiently. The proposed method presents a modest and spontaneous way of resolving real and reactive power flows through the transmission network due to all associated generators separately. It also gives the contribution of the individual generator to overall system losses and individual load distribution. To clarify the approach, the resolution of a sample case is provided using the proposed method. The performance of the developed technique has been investigated on IEEE 14-bus test system. To validate the method, the outcomes of the projected algorithm of the test system are compared with those obtained by using other conventional power tracing methods. Also, the execution time for different bus systems using the proposed methodology is observed to be comparatively less than other existing approaches, which justifies the fastness and robustness of the presented one.

Voltage dip and long duration interruption (LDI) are among the most costly power quality phenomena. In this study, a Monte-Carlo based approach is proposed to consider the cost of sensitive loads disruption caused by dip and LDI in the optimal planning of synchronous distributed generations (SDGs). The idea is to link between trip probability due to dip and LDI and their yearly costs by employing Monte-Carlo simulation and acquiring their total costs during the planning horizon. The addition of disruption cost along with the traditional planning objectives like network upgrade cost and loss cost allows utilities to include the customer's perception during planning. A formula for the probability of disruption due to dip is derived and a modified Monte-Carlo approach is proposed. The methodology is illustrated on the distribution level of the IEEE 30-bus system and the optimisation problem is solved by particle swarm optimisation algorithm. The results demonstrate that the sensitive loads performance is improved from the dip standpoint in the presence of SDGs. However, the LDI cost is either not affected or aggravated by the presence of SDGs depending on the protection model. The total disruption cost is decreased.

This study presents a passive wireless surface transverse wave (STW) torsion sensor for an overhead transmission line (OHTL). Two key techniques, namely the design of STW sensing element and clamping structure, were investigated. The relationship between the tension and the frequency shift of the STW resonator was analysed. A numerical analysis on the tension sensitivity and temperature coefficient using different cut types was performed. Results showed that Y − 51° cut quartz, which has a close to zero temperature coefficient of frequency, is a suitable substrate of the STW tension sensors. Other parameters were optimised to obtain a resonator with a Q value of >11,000. Two STW resonators were adopted as sensing element to form a differential structure to reduce the temperature interference. An OHTL clamping and tension transfer mechanical structure was designed, which has an ability of adjusting the tension sensitivity and can be easily installed at any point of OHTL. Moreover, the OHTL tension measurement system was set up and evaluated. Experimental results indicated that the STW tension sensitivity was 24.31 kHz/kN, the non-linearity was 0.26%, and the repeatability error was 0.32%. The OHTL tension measurement method is feasible for practical application.

This study proposes a cooperative secondary voltage control scheme in islanded microgrids, which can be seen as multi-agent systems with distributed generators being agents. Therefore, the voltage deviation caused by the primary control level can be compensated autonomously in a microgrid using a directed communication graph. An auxiliary centralised event-triggered controller is designed to deal with feedback control law. In this scheme, the estimates of agents are used to replace their actual values for feedback control. All agents receive the same event-triggered time from the auxiliary centralised controller. Thus, communication between agents is only needed when events are triggered, which highly reduces the burden of the communication network to make the control structure be more reliable. The stability analysis is also presented here. Simulation results based on an islanded microgrid test system in PSCAD/EMTDC are provided to validate the effectiveness of the proposed control strategy.

This study introduces an efficient management approach of the effective reactive power reserves considering the trade-off of the security level for N − 1 contingencies and economical concerns. The proposed method is deemed as an operational planning tool that simultaneously minimises the operating cost for a given forecasted load and control cost of the likely disturbances while ensuring that the level of available effective VAR reserves is adequate to withstand the credible severe contingencies without violating system security. The load shedding as a last resort control option is included in the problem formulation to guarantee that the voltage stability margins are maintained at a minimum control cost. The sensitivity of the load margin with respect to the generator VAR output is employed in order to determine the generator relative worth for keeping voltage security. Since the presented problem is a large-scale optimisation problem consisting of a base case and several sub-problems representing contingency states, a hybrid method based on particle swarm optimisation and conventional method is used as a solution methodology. The effectiveness of the proposed approach has been validated by its implementation on a six-bus system and IEEE 57-bus system.

Series flexible AC transmission systems devices, such as the variable series reactor, have the ability to continuously regulate the transmission line reactance so as to control power flow. This study presents a new approach to optimally locating such devices in the transmission network considering multiple operating states and contingencies. To investigate optimal investment, a single target year planning with three different load patterns is considered. The transmission contingencies may occur under any of the three load conditions and the coupling constraints between base case and contingencies are included. A reformulation technique transforms the original mixed integer non-linear programming model into mixed integer linear programming model. To further relieve the computational burden and enable the planning model to be directly applied to practical large-scale systems, a two-phase decomposition algorithm is introduced. Detailed numerical simulation results on IEEE 118-bus system and the Polish 2383-bus system illustrate the efficient performance of the proposed algorithm.

The conventional control strategies of shunt active power filter (SAPF) normally focus on the compensation for local non-linear loads, which may become uneconomical with a number of distributed non-linear loads. For an optimised network-wide harmonic suppression method, harmonic power flow calculation is the basis, and non-linear load modelling is the key which affects the accuracy and efficiency. First, this study discussed an accurate, but complicated non-linear load model, the coupled admittance matrix model for a typical harmonic source, phase-controlled rectifier, in detail, and proposed a fast calculation method which can simplify the calculation process evidently and explain the variation rules of model parameters clearly. Second, the main harmonic coupling characteristics of the rectifiers are analysed based on the calculation method, thus the rectifier matrix model is simplified and then an impedance-based network harmonic model for networks with distributed rectifiers is established. Finally, based on the network model, a promising control strategy of SAPF for network-wide harmonic suppression is presented, by which network parameters are acquired by online impedance measurement technique and good compensation performance is assured by the proposed network model. Experimental results and simulations are provided to validate the effectiveness of the proposed methods.

The ability of riding through the grid disturbances can increase the integration of microgrids into the distribution system. Consequently, a grid-connected microgrid should provide ancillary services such as low voltage ride-through (LVRT) capability and reactive power support to sustain the power system operations during abnormal grid conditions. The objective of this paper is to propose an LVRT scheme that improves the power quality of the entire microgrid. The developed method is implemented as the controller of the interface voltage-sourced converter (VSC) of a distributed energy resource and consists of primary and secondary control levels. The former includes the cascaded voltage and current control loops and the droop controller, while the latter controls the reactive power injection during the balanced/unbalanced voltage sags/swells. The proposed scheme is developed based on the independent control of each phase and does not require calculation of symmetrical components. Moreover, it can be employed in the VSC control systems with various reference frames and is effective for droop-based grid-connected microgrids with both single-phase and three-phase four-wire configurations. The proposed strategy is implemented using the hierarchical control system and preserves the plug and play capability. Several case studies are presented to verify the effectiveness of the proposed strategy.

This study presents a new robust state estimation (SE) approach for power systems that are monitored by synchronised phasor measurements. The proposed robust SE utilises the least absolute value (LAV) of residuals to determine the system state. Although conventional deterministic LAV-based SE is robust against bad measurements, it is vulnerable with respect to the network parameters’ errors. In other words, the conventional LAV-SE method is not robust against the network parameters’ errors and these errors can make the SE results inaccurate. The proposed robust SE aims at solving this problem of the conventional LAV-SE. Robust optimisation, strong duality theorem, and Big-M linearisation technique have been used to construct the proposed SE approach, which is robust against the network parameters’ errors. Additionally, the proposed robust SE is finally formulated as a tractable mixed-integer linear programming optimisation problem. Comprehensive numerical experiments and a probabilistic evaluation approach are presented to evaluate the effectiveness of the proposed robust SE compared to the conventional deterministic SE in the presence of the uncertainty source of network parameters’ errors.

This study proposes an optimal voltage control scheme to deal with long-term voltage stability of power systems. The control of voltage is accomplished by model predictive control (MPC) scheme. The control objective function considers the control efforts and the difference between the predicted and reference voltages. Also, this study considers the detailed non-linear dynamic model of the system including doubly-fed induction generator wind turbines, over excitation limiter and under-load tap changer, which are important elements, should be considered in voltage stability evaluation of power systems. The proposed approach composed of the following two major stages at each time instance: first, the power system non-linear dynamic equations are linearized and optimal control laws are obtained by MPC technique;in the second stage, the system dynamic behavior is investigated via time-domain simulations by applying the attained optimal control signals at the first step. The proposed MPC-based voltage control scheme is implemented on a well-known test system, under variable wind speed and fault conditions. Also, this method's performance is compared with state feedback control technique. The obtained numerical results validate the capability of the proposed control scheme to preserve voltage stability at the presence of stochastic wind speed variations and severe disturbances.

Modern power transmission grids are facing more and more critical short-term voltage stability problems. This study proposes a novel robust dynamic VAR planning approach for improving the short-term voltage stability level under uncertainties including the peak load level, the maximum proportion of dynamic load, fault clearing time and deviation of the actual capacity of dynamic VAR compensators from rated capacity when contingencies occur. The robust dynamic VAR planning problem is formulated as a multi-objective optimisation model with objectives including the investment cost, the expectation and robustness of the short-term voltage stability level. The complexity of the planning model is firstly reduced by selecting severe contingencies and potential buses, leading to a simplified multi-objective optimisation model. Latin hypercube sampling is then used for the uncertainty quantification. The simplified multi-objective optimisation model is then solved by the combination of a multi-objective evolutionary algorithm called -NSGAII and extreme learning machine-based surrogate modelling with adaptive training data sampling. This combination significantly reduces the unaffordable computing burden. Simulations are carried on the IEEE 39-bus system, illustrating that the authors proposed methodology is reliable with high computational efficiency, and offering decision-makers planning solutions with high mean performance and strong robustness with respect to the short-term voltage stability level.

This paper presents an algorithm for detection and location of faults in large transmission network using the minimum number of phasor measurement units (PMUs). The transfer impedance between the fault point and the respective PMU buses, may be far away from the fault point, are used to define a non-linear set of voltage and current equations, which is then transformed into linear least square estimation problem where fault location is the unknown quantity. The algorithm starts by reducing the search area using a faulted bus identification index so as to speed-up the search process. Then considering all the transmission lines within the search area, a fault location identification index together with the fault location algorithm is used to identify the faulted line along with fault location. A PMU placement scheme, to find the minimum number of PMUs and their location, required for the proposed algorithm is also presented here. The proposed algorithm is tested and validated on the IEEE 14, 30, 39, and 118-bus systems for various fault conditions. Comparative results confirm that the number of PMUs obtained by the proposed placement scheme is minimum and sufficient for detection and location of faults irrespective of fault resistance and fault type.