Probabilistic harmonic load flow using fast point estimate method

Mohammadi, Mohammad

doi:10.1049/iet-gtd.2014.0669

Cited by 37 publications

(8 citation statements)

References 25 publications

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“…The harmonic remains stochastically volatile under certain stable working conditions in practice while it also may reflect rhythmic/regular changes along with time, operation parameters or other potential possible factors from the perspective of probability [6]. These characteristics are measured and observed throughout TPSS and make it quite a complex challenge for describing the dynamic harmonic phenomena with one analytic model.…”

Section: A Current Problemsmentioning

confidence: 99%

Measurement-Based Compartmental Modeling of Harmonic Sources in Traction Power-Supply System

Gao

et al. 2017

IEEE Trans. Power Delivery

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 Harmonic pollution of traction power supply system (TPSS) has become a vital concern for its adverse impacts on the tractive drive system of the train and power quality issues of both TPSS and connected power system. Harmonic modeling is the precondition to evaluate the harmonic pollution for TPSS. This paper systematically discusses main harmonic sources in TPSS as well as their characteristics based on accurate field measurement. Moreover, the background harmonic voltage of the connected utility system and the harmonic of the train are compartmentalized and modeled with consideration of the stochastic and statistical features. This paper studies the background harmonic voltage with time slicing and probability statistics technique. Meanwhile，the harmonic of the train is described with Norton equivalent model, which considers the interaction between harmonic voltage and harmonic current. Moreover, the influence of the working conditions and power output on the harmonic distribution is mentioned in the low-order harmonic modeling of the train. The results suggests the proposed methods can effectively restore the distribution and characteristics of the harmonics in TPSS.Index Terms-harmonic modeling, traction power supply system, stochastic and statistical features, compartmental modeling, field data.

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Section: A Current Problemsmentioning

confidence: 99%

Measurement-Based Compartmental Modeling of Harmonic Sources in Traction Power-Supply System

Gao

et al. 2017

IEEE Trans. Power Delivery

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“…On one hand, neglecting harmonics in the capacitor placement problem causes errors in the calculation. On the other hand, lack of proper modeling of nonlinear loads and inappropriate selection of the place and size of capacitor banks can cause more problems in the power quality of the power system by generating resonances at harmonic frequencies between capacitors and multiple inductors installed in the system [2,[8][9][10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Method of Optimal Capacitor Placement in the Presence of Harmonics for Power Distribution Network Using NSGA-II Multi-Objective Genetic Optimization Algorithm

Moghadam

Falaghi

Farhadi

2020

MCA

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One of the effective ways of reducing power system losses is local compensation of part of the reactive power consumption by deploying shunt capacitor banks. Since the capacitor’s impedance is frequency-dependent and it is possible to generate resonances at harmonic frequencies, it is important to provide an efficient method for the placement of capacitor banks in the presence of nonlinear loads which are the main cause of harmonic generation. This paper proposes a solution for a multi-objective optimization problem to address the optimal placement of capacitor banks in the presence of nonlinear loads, and it establishes a reasonable reconciliation between costs, along with improvement of harmonic distortion and a voltage index. In this paper, while using the harmonic power flow method to calculate the electrical quantities of the grid in terms of harmonic effects, the non-dominated sorting genetic (NSGA)-II multi-objective genetic optimization algorithm was used to obtain a set of solutions named the Pareto front for the problem. To evaluate the effectiveness of the proposed method, the problem was tested for an IEEE 18-bus system. The results were compared with the methods used in eight other studies. The simulation results show the considerable efficiency and superiority of the proposed flexible method over other methods.

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“…Since the early seventies that the uncertainty in demand was first considered, the PPF methods has been proposed [13]. Based on the strategy of solving PPF problem, these methods are essentially classified into three main categories: simulation [14][15][16], approximate [17][18][19][20][21] and analytical methods [22][23][24]. Monte Carlo simulation is commonly known as a systemdimension independent method (MCS) that can provide accurate results.…”

Section: Introductionmentioning

confidence: 99%

“…Although this method is straight-forward and can be applied to the systems with correlations, it cannot cope with distribution systems and microgrids, efficiently and may have some hardships in systems with high number of correlations. Generally, point estimate method (PEM) [17,18], and its derivatives such as two-point estimate method (2PEM) [19], 2n + 1 PEM [20] and fast point estimate method (FPEM) [21] are all computationally rapid and are simply applied to PPF problem using the knowledge of first few statistical moments of inputs [19]. However, PEMs do not provide the PDF for the results, and they hold a low accuracy to provide higher statistical moments.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy unscented transform for uncertainty quantification of correlated wind/PV microgrids: possibilistic–probabilistic power flow based on RBFNNs

Baghaee

Mirsalim

Gharehpetian

et al. 2017

IET Renewable Power Generation

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The probabilistic power flow (PPF) of active distribution networks and microgrids based on the conventional power flow algorithms is almost impossible or at least cumbersome. Always, Mont Carlo simulation is a reliable solution. However, its computation time is relatively high that makes it unattractive to be a reliable solution for large interconnected power systems. This study presents a new method based on fuzzy unscented transform and radial basis function neural networks (RBFNN) for possibilistic-PPF in the microgrids including uncertain loads, correlated wind and solar distributed energy resources and plug-in hybrid electric vehicles. When sufficient historical data of the system variables is not available, a probability density function might not be defined, while they must be represented in another way namely possibilistically. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution methodology is needed. The proposed method exploits the ability of RBFNN and unscented transform in non-linear mapping with an acceptable level of accuracy, robustness and reliability. Simulation results for the proposed PPF algorithm and its comparison with the reported methods for different test power systems reveals its efficiency, accuracy, robustness and authenticity.

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Probabilistic harmonic load flow using fast point estimate method

Cited by 37 publications

References 25 publications

Measurement-Based Compartmental Modeling of Harmonic Sources in Traction Power-Supply System

Measurement-Based Compartmental Modeling of Harmonic Sources in Traction Power-Supply System

A Novel Method of Optimal Capacitor Placement in the Presence of Harmonics for Power Distribution Network Using NSGA-II Multi-Objective Genetic Optimization Algorithm

Fuzzy unscented transform for uncertainty quantification of correlated wind/PV microgrids: possibilistic–probabilistic power flow based on RBFNNs

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