Application of ANN and Genetic Algorithm for Evaluation the Optimum Location of Arresters on Power Networks due to the Switching Overvoltages

Switching surges are of primary importance in insulation co-ordination of EHV lines, as well as in designing insulation of apparatuses. The magnitude and shape of the switching overvoltages vary with the system parameters, network configuration and the point-on-wave where the switching operation takes place. This paper presents an artificial neural network (ANN) based approach to estimate the peak value of overvoltages and the global risk of failure generated by switching transients during line energizing or re-energizing in different nodes of a power network. Then a genetic algorithm (GA) based method is developed to find the best position of surge arresters on power networks so as to minimize the global risk of the network

Power system flexibility improvement with a focus on demand response and wind power variability

Unpredictable system component contingencies have imposed vulnerability on power systems, which are under high renewables penetration nowadays. Intermittent nature of renewable energy sources has made this unpredictability even worse than before and calls for excellent adaptability. This paper proposes a flexible security-constrained structure to meet the superior flexibility by coordination of generation and demand sides. In the suggested model, demand-side flexibility is enabled via an optimum real-time (RT) pricing program, while the commitment of conventional units through providing up and down operational reserves improves the flexibility of supply-side. The behaviour of two types of customers is characterized to define an accurate model of demand response and the effect of customers' preferences on the optimal operation of power networks. Conclusively, the proposed model optimizes RT prices in the face of contingency events as well as wind power penetration. System operators together with customers could benefit from the proposed method to schedule generation and consumption units reliably.fi=vertaisarvioitu|en=peerReviewed

Determination of the Ampacity of Buried Cable in Non-Homogenous Environmental Condition by 3D Computation

Abstract -Finite Volume Method (FVM) is chosen to calculate the heat transfer field and the heat generation with in the cable and heat dissipation in the surrounding soil of a three phase 145kV underground cable brunch that make it possible to analyze the ampacity of the cable. FLUENT as the proper software in this field is used to generate and solve the problem. Non-homogenous environment is considered for cable ampacity calculation and results are compare with homogenous environment conditio

A comparative review of different transformer modelling methods in TRV studies in case of transformer limited faults

One of the most serious possible faults in power systems is transformer limited fault (TLF), in which transient recovery voltage (TRV) characteristics is determined by the closest transformer to the circuit breaker and due to the immense variety of transformers; performing experimental tests to determine TRV in all cases is impossible. Therefore, simulation is recommended. Purpose of this paper is to review existing methods for transformers modeling in TRV studies and compare their results with the measurement results. Three different models including impedance model, simplified model and frequency dependent model are studied. All models are obtained using transformer FRA results. Then modelling is done for three separate transformers. Also the application and proposed guidelines of model selection are suggested. Finally, TRV simulations are performed in EMTPWorks using capacitive current injection method. As a result, amplitude factor and TRV frequency are calculated for each model and simulation and measurement results are compared. Keywords: Transformer modelling, Transient recovery voltage, Transformer limited fault, FRA test, Current injection method, TRV frequenc

REPLACING DIESEL GENERATOR WITH WIND TURBINE & LI-ION BATTERY IN VIRTUAL POWER PLANT

ABSTRACT: Diesel generators are the most common distributed generatio