Power flow variation based on extreme learning machine algorithm in power system

The main focus of this paper is a study that empowers us to understand how the temperature variation affects the transmission line resistance and as a result the power flow analysis with a specific end goal to assess losses in the electrical network. The paper is composed of two sections; the first part is a power flow study under normal conditions utilizing the neural network approach while the second investigated extreme learning machine algorithm efficiency and exactitude. Extreme learning machine algorithm has been used to settle several complications in power system: load forecasting, fault diagnosis, economic dispatch, security, transient stability; Thus, we proposed to study this technique to figure out this sort of complex issue.The study was conducted for IEEE 30 bus test system. The simulation results are exposed and analyzed in detail at the end of this paper

The Transient Stability Study of a Synchronous Generator Based on the Rotor Angle Stability

Transient stability is an important aspect in the operation of electrical power system. In case of fault occurs in the system, the determining of fault clearing time of circuit breaker is considered one of the main factors to ensure power transfer of the system. This paper is aim to study the transient stability of single machine infinite bus system (SMIB), based on the rotor angle stability. The study is performed to determine the influence of the critical clearing time of the circuit breakers on the rotor angle stability of the generator in the case of three phase fault. For obtaining and determining numerically the nature of the rotor angle of machine, we applied the Step-by-step method for different values of fault clearing time. The results of simulation indicate that determine of critical clearing time is a major evaluation in stability studies. The system model is created in MATLAB/ SIMULINK software

Contribution of DGs in the stability and voltage drop reduction for future MV network in desert regions

Day by day, the integration of decentralized generation in medium voltage networks becomes more important during the last years and even in the near future. This increase causes, at the same time, several negative effects and rarely positive impacts on the stability of the network. Therefore, this work aims at analyzing the impact of ambient temperature on radial distribution network parameters’ e.g.: voltage drop and stability voltage level (index). Based on MATLAB program, different analyses of distributed generation (DG) insertion influence’s on voltage drop in the radial distribution feeder, as well as the influence of climatic conditions such as ambient temperature on network parameters. The Integration of Photovoltaic DGs in MV networks can play an important role in reducing the global warming effect (in voltage drop, and voltage stability index) especially in radial distribution feeder. Furthermore, it protects network’s parameters if its location and power are well selected

A Neuro-fuzzy Approach for Predicting Load Peak Profile

Load forecasting has many applications for power systems, including energy purchasing and generation, load switching, contract evaluation, and infrastructure development. Load forecasting is a complex mathematical process characterized by random data and a multitude of input variables.To solve load forecasting, two different approaches are used, the traditional and the intelligent one.Intelligent systems have proved their efficiency in load forecasting domain. Adaptive neuro-fuzzy inference systems (ANFIS) are a combination of two intelligent techniques where we can get neural networks and fuzzy logics advantages simultaneously. In this paper, we will forecast night load peak of Algerian power system using multivariate input adaptive neuro-fuzzy inference system (ANFIS) introducing the effect of the temperature and type of the day as input variables

Load flow analysis using Newton-Raphson method in presence of distributed generation

Distributed generations (DG), specially including renewable sources such as wind and sun are offering several opportunities for the currently in existence distribution networks and becoming one of the keys of treatment of its problems. Knowing the effects of each kind of DG on distribution networks is a primordial task because DG impacts differ from one kind to another. In this paper, we have analyzed and compared the effects of two kinds of DG, DG which provides real power only and DG which provides real power and reactive power at the same time connected at the critical bus in DN on the voltage profile, real and reactive power losses. We have proposed Newton Raphson method using Matlab to investigate the impacts of these two kinds of DG on 57-bus IEEE distribution test system. The obtained results have been exposed in detail at the end of this paper

Optimal Power Flow Solution of Hybrid AC–DC Network Using Particle Swarm Method

In this article, we have tackled the multi-objective optimization problem of hybrid AC-DC networks using a metaheuristic method called particle swarm optimization (PSO). The approach of our work answers the following questions: how to model and integrate a direct current (DC) system, including VSC lines and converter stations, into the power optimization computation (OPF) process. To do this, the entire DC system (lines and VSC stations) is converted into a notional AC equivalent system using appropriate modeling, enabling the application of traditional AC OPF methods. Within the framework of multi-objective optimization, the Pareto technique is used to select the optimal solution from among those satisfying the defined objectives. The algorithm developed was implemented in the Matlab environment and tested on a modified IEEE-30 bus test network. The results obtained were compared with those of similar work published previously. The contribution of our research in the field of AC-DC hybrid power system optimization lies in the modeling of VSC stations integrated in an AC network, aiming to perform multi-objective optimization using tools developed for AC networks

Optimal number and location of UPFC devices to enhence voltage profile and minimizing losses in electrical power systems

The fast increase of loads around the world has made electrical networks more and more complex and difficult to operate close to its capacities. This is has led to many problems such as voltage collapse and energy losses. Therefore, flexible alternating current transmission systems (FACTS) are considred as a best solution for solving these problems. Unified Power Flow Controller UPFC is one of the most important and powerful FACTS devices due to its ability to increase the transmission capacity of the power system and reduce the total line losses. The problem of optimizing its number, location and size has become an important requirement for best advantages of this device. In this paper, a proposed relationship to identify the maximum number of FACTS devices that can be installed for a given power network is introduced in the search process code to determine the optimal number, optimal placement and size of UPFC device to enhance voltages profile and reduce overall system losses in the standard IEEE 14 bus test system using genetic algorithm (GA). The obtained results show clearly that all control parameters of UPFCs in each case are within their limits, and whenever the number of UPFCs installed increases, both voltage deviation and total losses well decreases. They also show that the application of the proposed relationship in the search process code facilitates greatly the search for optimal number, optimal placement and size of UPFC devices and reduces the calculation time. On the other hand, the obtained results has been scientifically justified and compared with other works reported in the literature

Control of Power and Voltage of Solar Grid Connected

Renewable energy is high on international agendas. Currently, grid-connected photovoltaic systems are a popular technology to convert solar energy into electricity. Control of power injected into the grid, maximum power point, high efficiency, and low total harmonic distortion of the currents injected into the grid are the requirements for inverter connection into the grid. Consequently, the performance of the inverters connected to the grid depends largely on the control strategy applied. In this paper the simulation and design of grid connected three phase photovoltaic system using Matlab/Simulink has examined. The proposed system consists photovoltaic panels, boost and inverter the PV system convert the sun irradiation into direct current, thereafter we have used a boost to track the maximum power point of the PV system, three-phase inverter and LC output filter. A VOC control strategy based on the phase shifting of the inverter output voltage with respect to the grid voltage. The proposed control strategy requires few hardware and computational resources. As a result, the inverter implementation is simple, and it becomes an attractive solution for low power grid connected applications

Active and reactive power sharing in micro grid using droop control

The development of renewable energy contributes to the global objectives of reducing our greenhouse gas emissions, obtaining and increasing our energy efficiency. In the face of these changes, the electric-network must adapt, while maintaining a high level of reliability and a quality of energy production. To meet this objective, it is recommended to use highly developed electrical network by integrating renewable energy sources in order to adapt the energy consumption to their production, using electro-technical software information and telecommunications technologies. We are talking about intelligent grids (Smart Grid). The main objective of the work presented in this paper is the contribution to the study of intelligent network for efficient management of energy produced by several sources linked to the AC bus via the voltage inverters. Numerical simulations have been presented to validate the performance of the proposed active and reactive power controller (Droop Control)

Control of power and voltage of solar grid connected

Renewable energy is high on international agendas. Currently, grid-connected photovoltaic systems are a popular technology to convert solar energy into electricity. Control of power injected into the grid, maximum power point, high efficiency, and low total harmonic distortion of the currents injected into the grid are the requirements for inverter connection into the grid. Consequently, the performance of the inverters connected to the grid depends largely on the control strategy applied. In this paper the simulation and design of grid connected three phase photovoltaic system using Matlab/Simulink has examined. The proposed system consists photovoltaic panels, boost and inverter the PV system convert the sun irradiation into direct current, thereafter we have used a boost to track the maximum power point of the PV system, three-phase inverter and LC output filter. A VOC control strategy based on the phase shifting of the inverter output voltage with respect to the grid voltage. The proposed control strategy requires few hardware and computational resources. As a result, the inverter implementation is simple, and it becomes an attractive solution for low power grid connected applications.</jats:p