Modified tensor method to power flow analysis

Santos, Erika Pequeno dos; Kobay, Bruna; Rosa, Mauro; Salgado, R.; Issicaba, Diego

doi:10.1049/iet-gtd.2018.6187

Cited by 3 publications

(2 citation statements)

References 25 publications

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“…Various improved Newton-Raphson methods have been developed, most of which combine new algorithms with traditional Newton-Raphson methods. In [1], the tensor concept is proposed based on Newton-Raphson method, and the quadratic term is retained for the expansion of Taylor's power flow equation. In [2], the optimal multiplier is introduced on the basis of Newton's method to change the iteration step, and the scalar multiplier is used to correct the deviation amount, which enhances the convergence speed of the power flow calculation.…”

Section: Introductionmentioning

confidence: 99%

A Power Flow Calculation Method Considering High-order Load Models

Pang

Jun

et al. 2023

J. Phys.: Conf. Ser.

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Given the popularity of new energy and the connection between large power electronic equipment and power system, the operation of power system becomes more complex and requires higher accuracy of power flow calculation. Therefore, a power flow calculation method considering high-order load model is proposed. On the basis of the Newton-Raphson method, when considering the load voltage characteristics, it is necessary to change the variables in the Newton-Raphson method power flow. Therefore, the established polynomial load model is introduced into the Newton-Raphson method, and the effect becomes more obvious with the increase of the order. Finally, constant power, constant current, constant impedance load and fifth order load models are tested in IEEE14-bus system respectively to verify the good accuracy and robustness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

A Power Flow Calculation Method Considering High-order Load Models

Pang

Jun

et al. 2023

J. Phys.: Conf. Ser.

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“…Power flow (PF) calculations (Tinney and Hart, 1967;Pourbagher, 2016;Issicaba, 2019) are a basic tool used to determine the steady-state operating condition of a power system based on the given operating environment and network structure, with the goal of facilitating the formulation of power supply schemes and real-time monitoring of the power grid. Therefore, rapid and reliable PF algorithms are urgently needed for power grids (Tang et al, 2019;Tostado-Véliz et al, 2019;Tostado-Véliz et al, 2021;Wei and Zhao, 2021;Xiao et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A Method for Directly Extracting the Jacobian Matrix of the Power Flow Equations of a Power System in Polar Coordinates

Lyu

Wei

2022

Front. Energy Res.

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This paper presents a method to directly extract the Jacobian matrix of a power system’s power flow (PF) equations in polar coordinates (termed as DEJMP method). This method is designed to reduce the computational complexity of the extraction process and improve the computational efficiency of the relevant PF algorithm. Direct extraction of the Jacobian matrix from the complex power equation in polar coordinates precludes an increase in both the number of procedural steps and the computational expense, which is a problem associated with the conventional PF (C-PF) algorithm due to its requirement that the derivatives of the active and reactive bus power equations be taken in separate steps. The DEJMP method avoids the trigonometric calculations used in the conventional method for computing the Jacobian matrix, resulting in a significant increase in computational efficiency. In addition, simulation results obtained for IEEE-300, S-1047, S-2383, and S-9241 bus systems validate the efficiency of the DEJMP-based PF algorithm. The DEJMP-based PF algorithm requires more than 20% less time to calculate the PF than the C-PF algorithm. This decrease in computing time is more pronounced for large systems.

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Tensor-Based Predictor–Corrector Algorithm for Power Generation and Transmission Reliability Assessment with Sequential Monte Carlo Simulation

Pequeno dos Santos,

Buss,

Rosa

et al. 2024

Energies

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The reliability assesment of large power systems, particularly when considering both generation and transmission facilities, is a computationally demanding and complex problem. The sequential Monte Carlo simulation is arguably the most versatile approach for tackling this problem. However, assessing sampled states in the sequential Monte Carlo simulation is time-intensive, rendering its use less appealing, particularly if nonlinear network representation must be deployed. In this context, this paper introduces a tensor-based predictor–corrector approach to reduce the burden of state evaluations in power generation and transmission reliability assessments. The approach allows for searching for sequences of operation points which can be assigned as success states within the sequential Monte Carlo simulation. If required, failure states are evaluated using a cross-entropy optimization algorithm designed to minimize load curtailments taking into account discrete variables. Numerical results emphasize the applicability of the developed algorithms using a small test system and the IEEE-RTS79 test system.

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Modified tensor method to power flow analysis

Cited by 3 publications

References 25 publications

A Power Flow Calculation Method Considering High-order Load Models

A Power Flow Calculation Method Considering High-order Load Models

A Method for Directly Extracting the Jacobian Matrix of the Power Flow Equations of a Power System in Polar Coordinates

Tensor-Based Predictor–Corrector Algorithm for Power Generation and Transmission Reliability Assessment with Sequential Monte Carlo Simulation

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