Application of automatic differentiation in power system trajectory sensitivity analysis

2014 ◽  
Author(s):  
Guangchao Geng ◽  
Venkataramana Ajjarapu ◽  
Quanyuan Jiang
Keyword(s):  
Sensitivity Analysis ◽  
Power System ◽  
Automatic Differentiation ◽  
Trajectory Sensitivity ◽  
System Trajectory

Escape System Trajectory Sensitivity Analysis.

1978 ◽  
Author(s):  
John J. Piacentino ◽  
James F. McEnerney ◽  
Gene C. Eberly
Keyword(s):  
Sensitivity Analysis ◽  
Trajectory Sensitivity ◽  
System Trajectory

Application of Trajectory Sensitivity for the Evaluation of the Effect of TCSC Placement on Transient Stability

2007 ◽  
Vol 8 (1) ◽  
Author(s):  
Dheeman Chatterjee ◽  
Arindam Ghosh
Keyword(s):  
Sensitivity Analysis ◽  
Power System ◽  
Transient Stability ◽  
Operating Conditions ◽  
Variable Capacitor ◽  
Trajectory Sensitivity ◽  
Thyristor Controlled Series Compensator ◽  
Bus System

This paper investigates the use of trajectory sensitivity analysis (TSA) technique for assessing the transient stability of a power system at various operating conditions. The effect of placement of a thyristor controlled series compensator (TCSC) as well as the influence of the change in firing angle is also discussed. The TCSC is modeled by a variable capacitor, the value of which changes with the firing angle. The systems studied are the WSCC 3-machine, 9-bus system and IEEE 16 machine 68 bus system. The results using TSA are validated by PSCAD/EMTDC simulation.

scholarly journals Optimal Placement and Sizing of an Energy Storage System Using a Power Sensitivity Analysis in a Practical Stand-Alone Microgrid

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1598
Author(s):  
Dongmin Kim ◽  
Kipo Yoon ◽  
Soo Hyoung Lee ◽  
Jung-Wook Park
Keyword(s):  
Sensitivity Analysis ◽  
Energy Storage ◽  
Power System ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Optimization Techniques ◽  
Optimal Placement ◽  
Stable Operation ◽  
Analytical Approaches

The energy storage system (ESS) is developing into a very important element for the stable operation of power systems. An ESS is characterized by rapid control, free charging, and discharging. Because of these characteristics, it can efficiently respond to sudden events that affect the power system and can help to resolve congested lines caused by the excessive output of distributed generators (DGs) using renewable energy sources (RESs). In order to efficiently and economically install new ESSs in the power system, the following two factors must be considered: the optimal installation placements and the optimal sizes of ESSs. Many studies have explored the optimal installation placement and the sizing of ESSs by using analytical approaches, mathematical optimization techniques, and artificial intelligence. This paper presents an algorithm to determine the optimal installation placement and sizing of ESSs for a virtual multi-slack (VMS) operation based on a power sensitivity analysis in a stand-alone microgrid. Through the proposed algorithm, the optimal installation placement can be determined by a simple calculation based on a power sensitivity matrix, and the optimal sizing of the ESS for the determined placement can be obtained at the same time. The algorithm is verified through several case studies in a stand-alone microgrid based on practical power system data. The results of the proposed algorithm show that installing ESSs in the optimal placement could improve the voltage stability of the microgrid. The sizing of the newly installed ESS was also properly determined.

Direct Sensitivity Analysis of Multibody Systems: A Vehicle Dynamics Benchmark

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
Alfonso Callejo ◽  
Daniel Dopico
Keyword(s):  
Sensitivity Analysis ◽  
Multibody Systems ◽  
Automatic Differentiation ◽  
Time Integration ◽  
General Purpose ◽  
Contact Forces ◽  
Design Parameters ◽  
Computational Techniques ◽  
Computationally Efficient ◽  
Integration Algorithm

Algorithms for the sensitivity analysis of multibody systems are quickly maturing as computational and software resources grow. Indeed, the area has made substantial progress since the first academic methods and examples were developed. Today, sensitivity analysis tools aimed at gradient-based design optimization are required to be as computationally efficient and scalable as possible. This paper presents extensive verification of one of the most popular sensitivity analysis techniques, namely the direct differentiation method (DDM). Usage of such method is recommended when the number of design parameters relative to the number of outputs is small and when the time integration algorithm is sensitive to accumulation errors. Verification is hereby accomplished through two radically different computational techniques, namely manual differentiation and automatic differentiation, which are used to compute the necessary partial derivatives. Experiments are conducted on an 18-degree-of-freedom, 366-dependent-coordinate bus model with realistic geometry and tire contact forces, which constitutes an unusually large system within general-purpose sensitivity analysis of multibody systems. The results are in good agreement; the manual technique provides shorter runtimes, whereas the automatic differentiation technique is easier to implement. The presented results highlight the potential of manual and automatic differentiation approaches within general-purpose simulation packages, and the importance of formulation benchmarking.

Analytical Derivatives Technology for Parametric Shape Design and Analysis in Structural Applications

2006 ◽  
Author(s):  
Srikanth Akkaram ◽  
Jean-Daniel Beley ◽  
Bob Maffeo ◽  
Gene Wiggs
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Automatic Differentiation ◽  
Thermal Response ◽  
Aircraft Engine ◽  
Design Parameters ◽  
Shape Design ◽  
Computer Simulation Model ◽  
Structural Applications ◽  
Analytical Derivatives

The ability to perform and evaluate the effect of shape changes on the stress, modal and thermal response of components is an important ingredient in the ‘design’ of aircraft engine components. The classical design of experiments (DOE) based approach that is motivated from statistics (for physical experiments) is one of the possible approaches for the evaluation of the component response with respect to design parameters [1]. Since the underlying physical model used for the component response is deterministic and understood through a computer simulation model, one needs to re-think the use of the classical DOE techniques for this class of problems. In this paper, we explore an alternate sensitivity analysis based technique where a deterministic parametric response is constructed using exact derivatives of the complex finite-element (FE) based computer models to design parameters. The method is based on a discrete sensitivity analysis formulation using semi-automatic differentiation [2,3] to compute the Taylor series or its Pade equivalent for finite element based responses. Shape design or optimization in the context of finite element modeling is challenging because the evaluation of the response for different shape requires the need for a meshing consistent with the new geometry. This paper examines the differences in the nature and performance (accuracy and efficiency) of the analytical derivatives approach against other existing approaches with validation on several benchmark structural applications. The use of analytical derivatives for parametric analysis is demonstrated to have accuracy benefits on certain classes of shape applications.

Sign in / Sign up

Export Citation Format

Share Document