Solution des systemes de controle de grandes dimensions basee sur les boucles de retroaction dans la simulation des reseaux electriques

The generation of electrical energy, as well as its transportation and consumption, requires complex control systems for the regulation of power and frequency. These control systems must take into account, among others, new energy sources such as wind energy and new technologies for interconnection by high voltage DC link. These control systems must be able to monitor and achieve such regulation in accordance with the dynamics of the energy source, faults and other events which may induce transients phenomena into the power network. Such transients conditions have to be analyzed using the most accurate and detailed hence, complex models of control system.;In addition, in the feasibility study phase, the calibration or the setup of equipment as well as in the operation of the power network, one may require decision aid tools for engineers. This includes, for instance, knowledge of energy dissipated into the arresters in transient analysis. These tools use simulation programs data as inputs and may require that complex functions be solved with numerical methods. These functions are part of control system in computer simulator. Moreover, the simulation evolves in a broader context of the development of digital controller, distributed and parallel high performance computing and rapid evolutions in computer (multiprocessor) technology. In such context, a continuing improvement of the control equations solver is welcomed.;Control systems are modelled using ax=b simultaneous system of equations. These equations are sometimes non-linear with feedback loops and thus require iterative Newton methods, including the formation of a Jacobian matrix and ordering as well as processing by graph theory tools. The proposed approach is based on the formulation of a reduced rank Jacobian matrix. The dimension is reduced up to the count of feedback loops. With this new approach, gains in computation speed are expected without compromising its accuracy when compared to classical full rank Jacobian matrix representation.;A directed graph representation is adopted and a proper approach for detecting and removing cycles within the graph is introduced. A condition of all zero eigenvalues of adjacency matrix of the graph is adopted. The transformation of the graph of controls with no cycle permits a formulation of control equations for only feedback points. This yields a general feedback interconnection (GFBI) representation of control, which is the main contribution of this thesis.;Methods for solving (non-linear) equations of control systems were deployed into the new GFBI approach. Five variants of the new approach were illustrated including firstly, a basic Newton method (1), a more robust one, the Dogleg method (2) and a fixed-point iterations method (3). I.;The presented approach is implemented in Electromagnetic Transient program EMTP-RV and tested on practical systems of various types and levels of complexity: the PLL, an asynchronous machine with 87 blocks reduced to 23 feedback equations by GFBI, and 12 wind power plants integrated to the IEEE-39 buses system.;Further analysis, which opens up avenues for future research includes comparison of the proposed approach against existing ones. With respect to the sole representation, it is shown that the proposed approach is equivalent to full classic representation of system of equations through a proper substitution process which complies with topological sequence and by skipping feedback variable identified by GFBI. Moreover, a second comparison with state space based approach, such as that in MATLAB/Simulink, shows that output evaluation step in state-space approach with algebraic constraints is similar to the GFBI. The algebraic constraints are similar to feedback variables. A difference may arise, however, when the number of algebraic constraints is not the optimal number of cuts for the GFBI method: for the PLL, for example, MATLAB/Simulink generated 3 constraints while the GFBI generated only 2. The GFBI method may offer some advantages in this case.;A last analysis axis prompted further work in initialization. It is shown that GFBI method may modifies the convergence properties of iterations of the Newton method. The Newton- Kantorovich theorem, using bounds on the norms of the Jacobian, has been applied to the proposed GFBI and classic full representation of control equations. The expressions of the Jacobian norms have been established for generic cases using Coates graph. It appears from the analysis of a simple case, for the same initial conditions, the behaviour of the Newton- Kantorovich theorem differs in both cases. These differences may also be more pronounced in the non-linear case. Further work would be useful to investigate this aspect and, eventually, pave the way to new initialization approaches.;Despite these limitations, not to mention areas for improvement in further work, one notes the contribution of this thesis to improve the gain of time on simulation for the solution of control systems. (Abstract shortened by UMI.).