Hybrid Differential Algebraic Equations approach for modeling interconnected power systems

Author(s):  
Maria Fernanda Mejia ◽  
Sylvain Claude Leirens
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>


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.


Author(s):  
Navid Gholizadeh ◽  
Joseph M Hood ◽  
Roger A Dougal

The Linear Implicit Quantized State System (LIQSS) method has been evaluated for suitability in modeling and simulation of long duration mission profiles of Naval power systems which are typically characterized by stiff, non-linear, differential algebraic equations. A reference electromechanical system consists of an electric machine connected to a torque source on the shaft end and to an electric grid at its electrical terminals. The system is highly non-linear and has widely varying rate constants; at a typical steady state operating point, the electrical and electromechanical time constants differ by three orders of magnitude—being 3.2 ms and 2.7 s respectively. Two important characteristics of the simulation—accuracy and computational intensity—both depend on quantization size of the system state variables. At a quantization size of about 1% of a variable’s maximum value, results from the LIQSS1 method differed by less than 1% from results computed by well-known continuous-system state-space methods. The computational efficiency of the LIQSS1 method increased logarithmically with increasing quantization size, without significant loss of accuracy, up to some particular quantization size, beyond which the error increased rapidly. For the particular system under study, a “sweet spot” was found at a particular quantum size that yielded both high computational efficiency and good accuracy.


Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1393
Author(s):  
Andrés González-Zumba ◽  
Pedro Fernández-de-Córdoba ◽  
Juan-Carlos Cortés ◽  
Volker Mehrmann

In this paper, we discuss stochastic differential-algebraic equations (SDAEs) and the asymptotic stability assessment for such systems via Lyapunov exponents (LEs). We focus on index-1 SDAEs and their reformulation as ordinary stochastic differential equations (SDEs). Via ergodic theory, it is then feasible to analyze the LEs via the random dynamical system generated by the underlying SDEs. Once the existence of well-defined LEs is guaranteed, we proceed to the use of numerical simulation techniques to determine the LEs numerically. Discrete and continuous QR decomposition-based numerical methods are implemented to compute the fundamental solution matrix and use it in the computation of the LEs. Important computational features of both methods are illustrated via numerical tests. Finally, the methods are applied to two applications from power systems engineering, including the single-machine infinite-bus (SMIB) power system model.


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