Reliability Evaluation for Optimally Operated, Large, Electric Power Systems

This paper presents a combined optimization/reliability technique to evaluate the reliability of large power systems. It uses Monte Carlo simulation for the individual operation/failure random performance of elements of a power network. This simulation overcomes the difficulty in constructing the many possible states for large power systems of complex topology. A simplified power-flow representation of the power network is used and a network reduction is implemented to reduce the size of the power-flow problem, such that only the effective part of the network (for a given contingency) is retained. The control parameters are optimized in order to simulate practical contingency situations in which suitable controls are invoked to preserve, as much as possible, the continuity of supply. The optimization problem is solved by linear programming in which the generator powers are manipulated as optimization variables to maximize the load power supplied and subject to the power flow equations as well as upper and lower bounds on the optimization variables. The outputs of the performance simulation and the optimization problem are subsequently used to compute the system reliability indices. The paper describes the computerized algorithm as well as numerical results for the IEEE 118-bus power system to demonstrate the applicability of the algorithm to actual systems.