Traveling wave based fault location for power transmission lines using morphological filters and clarke modal components

This article presents a fast and accurate fault location approach for power transmission lines based on the theory of traveling waves. In fact, when faults occur, they give rise to transient voltages and currents that propagate at a speed close to that of light along the transmission line as traveling waves. Moreover, according to the superposition theorem, each of these transients is a combination of a steady-state quantity and an incremental quantity. These transient signals measured at both ends of the line are first transformed to the Clarke (0-α-β components) components in order to categorize the type of faults, and then multi-scale morphological gradient filters are used to extract equivalent quantities to the incremental quantities to form what are called characteristic signals. These latter will be used to identify the fault location according to the proposed algorithm

Multi-scale morphological gradient algorithm based ultra-high-speed directional transmission line protection for internal and external fault discrimination

This paper introduces an ultra-high-speed directional transmission line protection scheme based on multi-scale morphological gradient algorithm (MSMGA). The directional protection scheme sets down the rules for determining the fault position in relation to the relaying point. The MSMGA is used to extract the fault-induced transient characteristics contained in the voltage and current signals. The associated signals are formed from these transient characteristics and the polarity of their local modulus maxima allow the discrimination between internal and external faults

A Comparison Study of Reactive Power Control Strategies in Wind Farms with SVC and STATCOM

In the recent years, the integration of the wind farms into the electrical grids has increased rapidly. Especially, the wind power plants made up with doubly fed induction generators due to its many advatanges, such as being able to control its reactive power. Hence, some countries have published grid code requirements related to the reactive power that the wind turbines have to satisfy. This paper presents a coordinated reactive power control strategy in which STATCOM and doubly fed induction generators in wind power plants are used in order to bring back the voltage at the point of common coupling in the allowable range. First, reactive power requirements that the wind farms have to fulfill in some European countries are introduced. Second, the reactive power limitations of 2MW doubly fed induction generator are determined. Then, the static synchronous compensator (STATCOM) and the synchronous var compensator (SVC) FACTS (Flexible AC Transmission Systems) devices are presented. Finaly, various reactive power control strategies are applied to 10 MW wind farm, and the simulation results are analysed and compared

A real-time fault diagnosis system for high-speed power system protection based on machine learning algorithms

This paper puts forward a real-time smart fault diagnosis system (SFDS) intended for high-speed protection of power system transmission lines. This system is based on advanced signal processing techniques, traveling wave theory results, and machine learning algorithms. The simulation results show that the SFDS can provide an accurate internal/external fault discrimination, fault inception time estimation, fault type identification, and fault location. This paper presents also the hardware requirements and software implementation of the SFDS

An analytical multicriteria model based on graph theory for reliability enhancement in distribution electrical networks

The electrical distribution network is a critical and complex system in terms of safety and reliability, because it is composed of different components (switches, reclosers, etc.). The improvement of its reliability is therefore one of the most important tasks through the good management of remote-controlled switches and reclosers in this network. This paper presents an analytical model based on graph theory to evaluate SAIDI and SAIFI indices based on the network architecture and the location of remote-controlled reclosers and switches. These indicators have been used to formalize a multi-objective mathematical model that respects the real operation constraints of equipments in smart grid. The applied model, in this article, was evaluated on an IEEE 13 bus network using the TOPSIS method to determine the optimal location of the switches and reclosers and to improve the overall reliability of the distribution network

Optimal location and reactive power injection of wind farms and SVC’s units using voltage indices and PSO

Nowadays, the use of the wind energy has known an important increase because it is clean and cheap. However, many technical issues could occur due to the integration of wind power plants into power grids. As a result, many countries have published grid code requirements that new installed wind turbines have to satisfy in order to facilitate its intergration to electrical networks. Among those requirements, the wind farms must be able to participate to ancillary services for instance voltage regulation and reactive power control. Nevertheless, in case of small wind farms having not the necessary reactive power capability to contribute to reactive power support, Flexible AC Transmission Systems (FACTS) devices could also be used to participate to reactive power support. In this paper, an optimization method based on particle swarm optimization (PSO) technique is presented. This method allows getting the optimal location and reactive power injection of both wind power plants (WPP) and synchronous var compensators (SVC) with the objective to improve the voltage profile and to minimize the active power losses. The IEEE 14 bus system and a 20 MW wind farm based doubly fed induction generator (DFIG) are used to validate the proposed algorithm. The simulation results are analysed and compared

Active power ouptut optimization for wind farms and thermal units by minimizing the operating cost and emissions

In recent years, many works have been done in order to discuss economic dispatch in which wind farms are installed in electrical grids in addition to conventional power plants. Nevertheless, the emissions caused by fossil fuels have not been considered in most of the studies done before. In fact, thermal power plants produce important quantities of emissions for instance, carbon dioxide (CO2) and sulphur dioxide (SO2) that are harmful to the environment. This paper presents an optimization algorithm with the objective to minimize the emission levels and the production cost. A comparison of the results obtained with different optimization methods leads us to opt for the grey wolf optimizer technique (GWO) to use for solving the proposed objective function. First, the method used to estimate the wind power of a plant is presented. Second, the economic dispatch models for wind and thermal generators are presented followed by the emission dispatch model for the thermal units.Then, the proposed objective function is formulated. Finally, the simulation results obtained by applying the GWO and other known optimization techniques are analysed and compared

Study of State Estimation Using Weighted Least Squares Method

Power state estimation constitutes the core of the on-line security analysis function. The challenge number one of a state estimator is to provide the optimal estimates of system state with minimum of measurement data. This paper describes weighted least squares state estimation method and investigates how the efficiency of WLS state estimation changes according to 4 parameters: number of measurements, measurement type, measurement weight and level of noise. Different simulation cases are tested on 3-bus system and IEEE 14-bus system. The results show that accurate estimates of system state can be obtained with minimum of measurement data on condition to choose a good combination of accurate measurements with a minimum of voltage measurements and power injection measurements and these data should be properly distributed throughout the system. For best results, the two factors (weight and noise) must be combined to obtain the best estimation. Indeed, the most accurate measurements (lower level of noise) should have greater weight compared to bad measurements (higher level of noise), specially voltage measurements due to their big impact