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 master-slave adaptive linear neuron-based approach for cost-effective use of battery energy storage systems in wind farms

Nowadays, clean and sustainable energy development is of essential concern, which justifies use of renewable energy sources. Wind energy is an important resource to provide such a demand. Due to the high costs of wind power generation compared to other renewable sources, the wind turbines should be designed in such a way that they usually operate at the highest point of their power. In this case, because of the random and alternating wind speed, the output power of the wind turbine generators and thus the windfarms fluctuate. When the capacity of windfarms is increased, the power injected from the windfarm into the grid can have significant negative effects on the power grid stability. In order to prevent these effects, it is necessary to use BESSs in windfarms. To this end, a waveform with acceptable fluctuations is considered for the windfarm output power. This waveform is compared with the output power waveform and then the difference between the two waveforms is compensated by a BESS. Proper tracking with the minimum delay reduces the required BESS capacity and thus initial investment cost for the windfarms is significantly reduced. In this paper, using real windfarm data, the conventional tracking methods for the windfarm output power waveform are analyzed and compared, first. Then, a novel tracking scheme, namely the MSA, is proposed, which is based on a two-fold master-slave adaptive linear neuron. Acquired results show that compared with the conventional methods, using the MSA scheme can reduce the costs of a 99 MW windfarm by 4.8 million dollars

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