Steady-State Single-Phase Models of Power System Components

Author(s):  
Edmund Handschin ◽  
Antonio Otero ◽  
José Cidrás
2017 ◽  
pp. 51-94
Author(s):  
Edmund Handschin ◽  
Antonio F. Otero ◽  
José Cidrás

2021 ◽  
Vol 2120 (1) ◽  
pp. 012024
Author(s):  
Siew Ting Chew ◽  
Yap Hoon ◽  
Hafisoh Ahmad

Abstract The study presents a new proposed reference current generation algorithm based on the synchronous reference frame (SRF) conventional algorithm in single-phase power system for an active power filtering. Shunt active power filter (SAPF) is often used as it can mitigate harmonic currents in the AC networks due to its superiority in dynamic-state conditions. The reference current generation algorithm is the most important control algorithms to control SAPF as it has the simplest implementation features. A proposed STF-based fundamental component identifier (STF-FCI) algorithm is implemented for the major improvements such as the removal of the unnecessary cosine function to reduce complexity of algorithm, employment of self-tuning filter (STF) to extract accurate fundamental component and to generate a sinusoidal reference current. The purpose of developing STF-FCI algorithm is to replace low pass filter (LPF) with a mean as it can generate a fast and accurate fundamental reference current to operate the SAPF in reducing the harmonics content of the power system and provide a fast response time in the dynamic-state conditions. This paper is presented under both steady-state which is capacitive (RC) load or inductive (RL) load as well as dynamic condition where capacitive load change to inductive load. The performance of steady-state condition will be evaluated in terms of THD values, ripple factor, power factor and phase difference. Under dynamic-state condition, the dynamic speed will be evaluated to capture the speed of the amplitude change in nonlinear load in a period of time. MATLAB-Simulink is used to design and evaluate the proposed STF-FCI algorithm with mean algorithm and LPF algorithm for comparison purpose. The simulation results had shown the major improvement when THD values, ripple factor, power factor and phase difference are reduced. The response time of the changing load is shorter by using mean algorithm compare to LPF algorithm. The simulation results obtained proved success when the proposed STF-FCI algorithm using mean algorithm are much better than LPF algorithm in steady-state and dynamic conditions under two voltage conditions i.e. ideal and distorted voltage.


Author(s):  
Sunil S. Damodhar

Abstract The solution of the adjusted power flow problem involves handling power system components whose control characteristics possess operational limits. Examples include generator reactive power limits, tap-changing and phase-shifting transformers, and FACTS devices. While the conventional method involves checking for limit violations in an outer loop drawn around the unadjusted power flow problem being solved by the Newton-Raphson (NR) method, for iterative processes, it is desirable to have smooth, continuously differentiable models implicitly handled within a single loop. A novel formulation for a subset of devices is presented for implicit handling within power flow. The steady state characteristics of tap-changing and phase-shifting transformers, and FACTS devices SVC and STATCOM, can be described using the “cut function”, a piecewise linear function traditionally employed in neural networks. A new approximation of the cut function is used for formulating novel equations describing the steady state characteristics. An augmented set of equations is formed and solved by the NR method, eliminating the need of an outer loop. The efficacy of the proposed method is demonstrated by employing it for plotting bus voltage profiles and determining maximum loadability of test systems. Comparisons with the conventional method show that significant savings in computation can be achieved.


2020 ◽  
Vol 2 (2) ◽  
pp. 4-9
Author(s):  
El’mar M. FARKHADZADE ◽  
◽  
Audin Z. MURADALIYEV ◽  
Tamara K. RAFIYEVA ◽  
Aisel’ AliPanach kyzy RUSTAMOVA ◽  
...  

2020 ◽  
Vol 10 (14) ◽  
pp. 4761
Author(s):  
Milorad Papic ◽  
Svetlana Ekisheva ◽  
Eduardo Cotilla-Sanchez

Modern risk analysis studies of the power system increasingly rely on big datasets, either synthesized, simulated, or real utility data. Particularly in the transmission system, outage events have a strong influence on the reliability, resilience, and security of the overall energy delivery infrastructure. In this paper we analyze historical outage data for transmission system components and discuss the implications of nearby overlapping outages with respect to resilience of the power system. We carry out a risk-based assessment using North American Electric Reliability Corporation (NERC) Transmission Availability Data System (TADS) for the North American bulk power system (BPS). We found that the quantification of nearby unscheduled outage clusters would improve the response times for operators to readjust the system and provide better resilience still under the standard definition of N-1 security. Finally, we propose future steps to investigate the relationship between clusters of outages and their electrical proximity, in order to improve operator actions in the operation horizon.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1717
Author(s):  
Camilo Andrés Ordóñez ◽  
Antonio Gómez-Expósito ◽  
José María Maza-Ortega

This paper reviews the basics of series compensation in transmission systems through a literature survey. The benefits that this technology brings to enhance the steady state and dynamic operation of power systems are analyzed. The review outlines the evolution of the series compensation technologies, from mechanically operated switches to line- and self-commutated power electronic devices, covering control issues, different applications, practical realizations, and case studies. Finally, the paper closes with the major challenges that this technology will face in the near future to achieve a fully decarbonized power system.


2021 ◽  
Vol 377 ◽  
pp. 111149
Author(s):  
Taiyang Zhang ◽  
Erik R. Smith ◽  
Caleb S. Brooks ◽  
Thomas H. Fanning

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 148
Author(s):  
Lili Wu ◽  
Ganesh K. Venayagamoorthy ◽  
Jinfeng Gao

Power system steady-state security relates to its robustness under a normal state as well as to withstanding foreseeable contingencies without interruption to customer service. In this study, a novel cellular computation network (CCN) and hierarchical cellular rule-based fuzzy system (HCRFS) based online situation awareness method regarding steady-state security was proposed. A CCN-based two-layer mechanism was applied for voltage and active power flow prediction. HCRFS block was applied after the CCN prediction block to generate the security level of the power system. The security status of the power system was visualized online through a geographic two-dimensional visualization mechanism for voltage magnitude and load flow. In order to test the performance of the proposed method, three types of neural networks were embedded in CCN cells successively to analyze the characteristics of the proposed methodology under white noise simulated small disturbance and single contingency. Results show that the proposed CCN and HCRFS combined situation awareness method could predict the system security of the power system with high accuracy under both small disturbance and contingencies.


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