scholarly journals Application of Genetic Algorithm to Estimation of Function Parameters in Lightning Currents Approximations

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
V. Javor ◽  
K. Lundengård ◽  
M. Rančić ◽  
S. Silvestrov
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Lightning Discharge ◽  
Lightning Protection ◽  
Lightning Stroke ◽  
Vertical Antenna ◽  
Stroke Models ◽  
Triggered Lightning ◽  
Extended Function ◽  
Good Agreement

Genetic algorithm (GA) is applied for the estimation of two-peaked analytically extended function (2P-AEF) parameters in this paper. 2P-AEF is used for approximation of measured and typical lightning discharge currents. Lightning discharge channel is often modeled as thin-wire vertical antenna at perfectly conducting ground. Engineering lightning stroke models assume that the current along that channel is related to the channel-base current which may be measured at the instrumented tall towers and in triggered lightning experiments. Mathematical modeling of lightning currents is important in verification of lightning strokes models based on simultaneously measured electromagnetic fields at various distances, so as in lightning protection studies, computation of lightning induced effects and simulation of overvoltages in power systems. Typical lightning discharge currents of the first positive, first negative, and subsequent negative strokes are defined by IEC 62305 Standard based on comprehensive measurements. Parameters of 2P-AEF’s approximation of the typical negative first stroke current are determined by GA and compared to approximations obtained by other functions. Measured currents at Monte San Salvatore in Switzerland, at Morro de Cachimbo Station in Brazil, and in rocket-triggered lightning experiments at Camp Blanding in Florida are approximated by 2P-AEFs, and good agreement with experimentally measured waveshapes is obtained.

scholarly journals Selected Issues of Safe Operation of the Railway Traffic Control System in the Event of Exposition to Damage Caused by Lightning Discharges

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5808
Author(s):  
Renata Markowska ◽  
Zofia Wróbel
Keyword(s):  
Control System ◽  
Power Systems ◽  
Traffic Control ◽  
Lightning Discharge ◽  
Lightning Protection ◽  
Current Standard ◽  
Protection Measures ◽  
Railway Traffic ◽  
Protective Devices ◽  
Traffic Control System

Lightning discharge becomes a serious source of interference and damage for electronic and electrical power systems. Safe and reliable operation of railway traffic control systems requires proper protection against the effects of lightning. However, the current standards on lightning protection, PN-EN/EN/IEC 62305, do not cover railway objects. Moreover, there are no other standards or recommendations dedicated to the railway. The paper is an attempt to apply the procedure of lightning risk management according to PN-EN 62305-2 to select the proper protection measures in railway objects. A case study for the signal box with installed relaying and digital stations of the railway traffic control system is analyzed. The analysis comprises calculations based on the current standard PN-EN 62305-2:2012 but including the issues specific to railway traffic control. The risks of lightning losses have been calculated for two cases: without lightning protection measures and with protection measures proposed to decrease the risks below the tolerable values. The results show that a practically effective solution to reduce the risks is applying surge protective devices with proper characteristics. Another way is replacing unshielded incoming lines with shielded ones of given shield bonding way, and supplementing it with surge protective devices when necessary.

Modeling of artificially triggered lightning currents by multi-peaked analytically extended functions

2018 ◽  
Vol 37 (4) ◽  
pp. 1354-1365
Author(s):  
Vesna Javor ◽  
Karl Lundengård ◽  
Milica Rančić ◽  
Sergei Silvestrov
Keyword(s):  
Electromagnetic Field ◽  
Electromagnetic Fields ◽  
Wire Antenna ◽  
Lightning Protection ◽  
Approximation Procedure ◽  
Content Type ◽  
Lightning Channel ◽  
Triggered Lightning ◽  
Lightning Discharges ◽  
Extended Function

Purpose This paper aims to present the approximation of lightning currents waveshapes by the multi-peaked analytically extended function (MP-AEF) for the experimentally measured channel-base currents in the artificially triggered lightning discharges. Modified transmission line model of lightning return strokes having the channel current both linearly decaying and sinusoidally changing with height (MTLSIN) is used to calculate the lightning electromagnetic field. Design/methodology/approach MP-AEF’s parameters for the artificially triggered lightning channel-base currents are calculated by using Marquardt least squares method (MLSM). Lightning electromagnetic fields are calculated based on electromagnetic theory relations, thin-wire antenna model of the vertical lightning channel and the assumption of the perfectly conducting ground. MTLSIN model as an engineering model of lightning strokes is used to obtain the electric field results as these are simultaneously measured in rocket-triggered lightning experiments together with the channel-base currents. Findings MP-AEF approximates multi-peaked pulse waveshapes. Some important function parameters are chosen prior to the approximation procedure, such as current peaks and the corresponding time moments of those peaks, which presents an advantage in comparison to other functions. The desired accuracy of approximation is obtained by choosing an adequate number of function terms. MLSM is used for the estimation of unknown parameters. Using MTLSIN model, the influence of the channel height and return stroke speed on the lightning electromagnetic field waveshape is analyzed in this paper. Research limitations/implications MP-AEF may be used for approximation of various multi-peaked waveshapes. It has no errors in the points of maxima which is important for the lightning protection systems design. MTLSIN model may be validated by using simultaneously measured lightning electromagnetic fields at various distances from the channel and for channel heights estimated in the experiments. It is also possible to approximate measured current derivatives by MP-AEF and use them for further computation. Originality/value MTLSIN model is proposed in this paper for the evaluation of lightning electromagnetic fields induced by artificially triggered lightning discharges. The procedure is based on the approximation of lightning channel-base currents by the multi-peaked analytically extended function previously proposed by the authors. This function may be used not only for representing lightning currents but also for other waveshapes as current derivatives, electric and magnetic fields and their derivatives, which are all important for the lightning protection design. MTLSIN gives lightning electromagnetic fields results which are in better agreement with measured fields than those obtained by other models from literature.

Genetic algorithm-based method for contingency screening in power systems

1996 ◽  
Vol 116 (2) ◽  
pp. 99-111 ◽  
Author(s):  
Hiroumi Saitoh ◽  
Yutaka Takano ◽  
Junichi Toyoda
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Contingency Screening

Predicting Seepage of Earth Dams Using Neural Network and Genetic Algorithm

2011 ◽  
Vol 403-408 ◽  
pp. 3081-3085 ◽  
Author(s):  
Xin Ying Miao ◽  
Jin Kui Chu ◽  
Jing Qiao ◽  
Ling Han Zhang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Field Data ◽  
Back Propagation ◽  
Earth Dam ◽  
Earth Dams ◽  
Gradient Descent Algorithm ◽  
Levenberg Marquardt ◽  
Lm Algorithm ◽  
Good Agreement

Measurements of seepage are fundamental for earth dam surveillance. However, it is difficult to establish an effective and practical dam seepage prediction model due to the nonlinearity between seepage and its influencing factors. Genetic Algorithm for Levenberg-Marquardt(GA-LM), a new neural network(NN) model has been developed for predicting the seepage of an earth dam in China using 381 databases of field data (of which 366 in 2008 were used for training and 15 in 2009 for testing). Genetic algorithm(GA) is an ecological system algorithm, which was adopted to optimize the NN structure. Levenberg-Marquardt (LM) algorithm was originally designed to serve as an intermediate optimization algorithm between the Gauss-Newton(GN) method and the gradient descent algorithm, which was used to train NN. The predicted seepage values using GA-LM model are in good agreement with the field data. It is demonstrated here that the model is capable of predicting the seepage of earth dams accurately. The performance of GA-LM has been compared with that of conventional Back-Propagation(BP) algorithm and LM algorithm with trial-and-error approach. The comparison indicates that the GA-LM model can offer stronger and better performance than conventional NNs when used as a quick interpolation and extrapolation tool.

scholarly journals Multiobjective Optimization Methods for Congestion Management in Deregulated Power Systems

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
K. Vijayakumar
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Electricity Market ◽  
Optimization Methods ◽  
Evolutionary Programming ◽  
Congestion Management ◽  
Transmission Congestion ◽  
Nsga Ii ◽  
Line Overload ◽  
Nondominated Sorting

Congestion management is one of the important functions performed by system operator in deregulated electricity market to ensure secure operation of transmission system. This paper proposes two effective methods for transmission congestion alleviation in deregulated power system. Congestion or overload in transmission networks is alleviated by rescheduling of generators and/or load shedding. The two objectives conflicting in nature (1) transmission line over load and (2) congestion cost are optimized in this paper. The multiobjective fuzzy evolutionary programming (FEP) and nondominated sorting genetic algorithm II methods are used to solve this problem. FEP uses the combined advantages of fuzzy and evolutionary programming (EP) techniques and gives better unique solution satisfying both objectives, whereas nondominated sorting genetic algorithm (NSGA) II gives a set of Pareto-optimal solutions. The methods propose an efficient and reliable algorithm for line overload alleviation due to critical line outages in a deregulated power markets. The quality and usefulness of the algorithm is tested on IEEE 30 bus system.

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