scholarly journals Efficient Adjoint Computation of Hybrid Systems of Differential Algebraic Equations with Applications in Power Systems

2016 ◽  
Author(s):  
Shrirang Abhyankar ◽  
Mihai Anitescu ◽  
Emil Constantinescu ◽  
Hong Zhang
2020 ◽  
Author(s):  
Gilles Mpembele ◽  
Jonathan Kimball

<div>The analysis of power system dynamics is usually conducted using traditional models based on the standard nonlinear differential algebraic equations (DAEs). In general, solutions to these equations can be obtained using numerical methods such as the Monte Carlo simulations. The use of methods based on the Stochastic Hybrid System (SHS) framework for power systems subject to stochastic behavior is relatively new. These methods have been successfully applied to power systems subjected to</div><div>stochastic inputs. This study discusses a class of SHSs referred to as Markov Jump Linear Systems (MJLSs), in which the entire dynamic system is jumping between distinct operating points, with different local small-signal dynamics. The numerical application is based on the analysis of the IEEE 37-bus power system switching between grid-tied and standalone operating modes. The Ordinary Differential Equations (ODEs) representing the evolution of the conditional moments are derived and a matrix representation of the system is developed. Results are compared to the averaged Monte Carlo simulation. The MJLS approach was found to have a key advantage of being far less computational expensive.</div>


Author(s):  
Radu Serban ◽  
Antonio Recuero

We present an adjoint sensitivity method for hybrid discrete—continuous systems, extending previously published forward sensitivity methods (FSA). We treat ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) of index up to two (Hessenberg) and provide sufficient solvability conditions for consistent initialization and state transfer at mode switching points, for both the sensitivity and adjoint systems. Furthermore, we extend the analysis to so-called hybrid systems with memory where the dynamics of any given mode depend explicitly on the states at the last mode transition point. We present and discuss several numerical examples, including a computational mechanics problem based on the so-called exponential model (EM) constitutive material law for steel reinforcement under cyclic loading.


2020 ◽  
Author(s):  
Gilles Mpembele ◽  
Jonathan Kimball

The analysis of power system dynamics is usually conducted using traditional models based on the standard nonlinear differential algebraic equations (DAEs). In general, solutions to these equations can be obtained using numerical methods such as the Monte Carlo simulations. The use of methods based on the Stochastic Hybrid System (SHS) framework for power systems subject to stochastic behavior is relatively new. These methods have been successfully applied to power systems subjected to stochastic inputs. This study discusses a class of SHSs referred to as Markov Jump Linear Systems (MJLSs), in which the entire dynamic system is jumping between distinct operating points, with different local small-signal dynamics. The numerical application is based on the analysis of the IEEE 37-bus power system switching between grid-tied and standalone operating modes. The Ordinary Differential Equations (ODEs) representing the evolution of the conditional moments are derived and a matrix representation of the system is developed. Results are compared to the averaged Monte Carlo simulation. The MJLS approach was found to have a key advantage of being far less computational expensive.


2020 ◽  
Author(s):  
Gilles Mpembele ◽  
Jonathan Kimball

<div>The analysis of power system dynamics is usually conducted using traditional models based on the standard nonlinear differential algebraic equations (DAEs). In general, solutions to these equations can be obtained using numerical methods such as the Monte Carlo simulations. The use of methods based on the Stochastic Hybrid System (SHS) framework for power systems subject to stochastic behavior is relatively new. These methods have been successfully applied to power systems subjected to</div><div>stochastic inputs. This study discusses a class of SHSs referred to as Markov Jump Linear Systems (MJLSs), in which the entire dynamic system is jumping between distinct operating points, with different local small-signal dynamics. The numerical application is based on the analysis of the IEEE 37-bus power system switching between grid-tied and standalone operating modes. The Ordinary Differential Equations (ODEs) representing the evolution of the conditional moments are derived and a matrix representation of the system is developed. Results are compared to the averaged Monte Carlo simulation. The MJLS approach was found to have a key advantage of being far less computational expensive.</div>


2015 ◽  
Vol 18 (3) ◽  
pp. 47-54
Author(s):  
Khanh Tuan Dang ◽  
Liem Van Nguyen

As the power demand has been increasing rapidly, today’s modern power system becomes to be more complex and faces many challenges. It is envisaged that transient stability will play the important role in ensuring the steady state operation of power systems in the event of three phases fault or switching of lines. This paper investigates models of Flexible AC Transmission Systems (FACTS) and applications of FACTS devices for improving the rotor angle stability. FACTS devices are applicable in shunt connection Static Var Compensator (SVC), in series connection Thyristor-Controlled Series Capacitor (TCSC), or in the combination of both. Mathematical models of power systems having FACTS devices are set of Differential - Algebraic Equations (DAEs). Trapezoidal rule and Newton - Raphson method are applied to solve DAEs. The simulation results of rotor angles demonstrate the effectiveness and robustness of proposed the SVC and TCSC on transient stability enhancement of power systems.


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