Stability of power systems coupled with market dynamics.

摘要

This Ph.D. thesis presented here spans two relatively independent topics. The first part, Chapter 2 is self-contained, and is dedicated to studies of new algorithms for power system state estimation. The second part, encompassing the remaining chapters, is dedicated to stability analysis of power system coupled with market dynamics.; The first part of this thesis presents improved Newton's methods employing efficient vectorized calculations of higher order derivatives in power system state estimation problems. The improved algorithms are proposed based on an exact Newton's method using the second order terms. By efficiently computing an exact gain matrix, combined with a special optimal multiplier method, the new algorithms show more reliable convergence compared with the existing methods of normal equations, orthogonal decomposition, and Hachtel's sparse tableau. Our methods are able to handle ill-conditioned problems, yet show minimal penalty in computational cost for well-conditioned cases. These claims are illustrated through the standard IEEE 118 and 300 bus test examples.; The second part of the thesis focuses on stability analysis of market/power systems. The work presented is motivated by an emerging problem. As the frequency of market based dispatch updates increases, there will inevitably be interaction between the dynamics of markets determining the generator dispatch commands, and the physical response of generators and network interconnections, necessitating the development of stability analysis for such coupled systems. We begin with numeric tests using different market models, with detailed machine/exciter/turbine/governor dynamics, in the New England 39 bus test system. A progression of modeling refinements are introduced, including such non-ideal effects as time delays. Electricity market parameter identification algorithms are also studied based on real time data from the PJM electricity market. Finally our power market model is augmented by optimal power flow constraints, allowing study of the so-called congestion problem. These studies show that understanding of potential modes of instability in such coupled systems is of crucial importance both in designing suitable rules for power markets, and in designing physical generator controls that are complementary to market-based dispatch.