Development and Comparison of Efficient Newton-Like Methods for Voltage Stability Assessment

Tostado‐Véliz, Marcos; Kamel, Salah

doi:10.1080/15325008.2021.1908452

Cited by 6 publications

(6 citation statements)

References 39 publications

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“…The values corresponding to CP (critical point) for each system studied and the error between the obtained value in relation to the desired are detailed in Table 2. Tables 3-5 display the values of the weights of the connections between the input and hidden layers, between the hidden layer and the output layer, as well as the corresponding bias values of the hidden and output layers, for the neural network with the configuration [2,3,10]. Figures 6b, 8b, and 10b depict the validation phase of the model via ANN.…”

Section: Discussionmentioning

confidence: 99%

“…The volume of losses in transmission and distribution systems is significant, typically ranging between 3% and 13%, highlighting their relevance to the efficiency of the system as a whole [1]. The analysis of electrical power systems often uses load flow calculation, a fundamental and widely used approach [2][3][4]. Many applications, from expansion planning to network reconfiguration and storage capacity, depend on these calculations [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Total Real and Reactive Power Losses in Electrical Power Systems via Artificial Neural Network

da Silva,

de Queiroz,

Garbelini

et al. 2024

ASI

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Total real and reactive power losses in electrical power systems are an inevitable phenomenon and occur due to several factors, such as conductor resistance, transformer impedance, line reactance, equipment losses, and phase unbalance. Minimizing them is crucial to the system’s efficiency. In this study, an artificial neural network, specifically a Multi-layer Perceptron, was employed to predict total real and reactive power losses in electrical systems. The network is composed of three layers: an input layer consisting of the variables loading factor, real and reactive power generated on the slack bus, a hidden layer, and an output layer representing the total real and reactive power losses. The training method used was backpropagation, adjusting the weights based on the desired output. The results obtained, using datasets from IEEE systems with 14, 30, and 57 buses, showed satisfactory performance, with a mean squared error of around 10−4 and a coefficient of determination (R2) of 0.998. In validation with 20% of the data that was not part of the training, the network demonstrated effectiveness, with a mean squared error around 10−3. This indicates that the network was able to accurately predict total power losses based on loads, generating estimates close to the desired values.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimation of Total Real and Reactive Power Losses in Electrical Power Systems via Artificial Neural Network

da Silva,

de Queiroz,

Garbelini

et al. 2024

ASI

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“…This process is repeated various times until the whole continuation curve is drawn, which may imply many PFCs and therefore the whole process can be very time-consuming. Recent studies [29] have demonstrated that the usage of HONL techniques may alleviate the computational cost of CPF, which may suppose an unvaluable contribution for real-time security tools, in which CPF is widely employed.…”

Section: Potential Applications Of the Developed Solversmentioning

confidence: 99%

On Various High-Order Newton-Like Power Flow Methods for Well and Ill-Conditioned Cases

2021

Self Cite

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Recently, the high-order Newton-like methods have gained popularity for solving power flow problems due to their simplicity, versatility and, in some cases, efficiency. In this context, recent research studied the applicability of the 4th order Jarrat’s method as applied to power flow calculation (PFC). Despite the 4th order of convergence of this technique, it is not competitive with the conventional solvers due to its very high computational cost. This paper addresses this issue by proposing two efficient modifications of the 4th order Jarrat’s method, which present the fourth and sixth order of convergence. In addition, continuous versions of the new proposals and the 4th order Jarrat’s method extend their applicability to ill-conditioned cases. Extensive results in multiple realistic power networks serve to sow the performance of the developed solvers. Results obtained in both well and ill-conditioned cases are promising.

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“…Energies 2023, 16, 7583 2 of 13 to determine the loading margin, is the main tool in contingency studies. The continuation power flow (CPF) with parameterization techniques [5][6][7][8][9] is the method used to obtain these curves, as they can generate the entire P-V curve by using the appropriate parameter.…”

Section: Introductionmentioning

confidence: 99%

“…Ref [5] introduces efficient correction techniques based on Newton-like methods to expedite continuation power flow, showcasing their superiority over the conventional Newton-Raphson method in terms of computational time. A parameterization to continuation power flow is presented in [6], proposing a coordinated combination of methods to enhance convergence.…”

Section: Introductionmentioning

confidence: 99%

Post-Contingency Loading Margin through Plane Change in the Continuation Power Flow

dos Santos,

Bonini Neto,

Gabriel Filho

2023

Energies

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This paper introduces a parameterization technique to obtain complete P-V curves for electrical power systems under various conditions, including contingencies (N-1, N-1 severe, and N-2) as well as normal operating conditions N-0 (pre-contingency). The distinct feature of this methodology lies in the utilization of the new (θk, Vk) plane for constructing the P-V curve. In this new framework, the solution trajectory exhibits a linear characteristic in the vicinity of the maximum loading point (MLP), effectively mitigating any numerical challenges. Another crucial aspect is the point denoted as the center of the set of lines, point O (λ0, Vk0). This point can be adjusted along the ordinate axis, further enhancing the method’s ability to achieve a smoother ‘flat start’. The ‘flat start’ approach employed in the proposed methodology enables the determination of the loading margin for any system subjected to both simple and severe contingencies. Additionally, it facilitates the use of larger steps in acquiring complete P-V curves with a reduced number of iterations. A procedure presented is to not update the Jacobian matrix at each iteration but only when the system undergoes significant changes. This technique reduced the CPU Ratio by 29.74% in obtaining the P-V curve for all scenarios.

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Development and Comparison of Efficient Newton-Like Methods for Voltage Stability Assessment

Cited by 6 publications

References 39 publications

Estimation of Total Real and Reactive Power Losses in Electrical Power Systems via Artificial Neural Network

Estimation of Total Real and Reactive Power Losses in Electrical Power Systems via Artificial Neural Network

On Various High-Order Newton-Like Power Flow Methods for Well and Ill-Conditioned Cases

Post-Contingency Loading Margin through Plane Change in the Continuation Power Flow

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