Interior point methods for power flow optimization with security constraints

This paper deals with power flow optimization with security constraints, focusing on the problem of short-term hydroelectric scheduling, called predispatch. Since the energy demand varies throughout the day, the generation must satisfy daily targets, established by long-term scheduling models. This study considers that the hydroelectric plants and transmission systems must provide an optimal flow of energy under security constraints that allow meeting energy demands for normal operating conditions and when disturbances happen. Algebraic techniques are used to exploit the sparse structure of the problem, targeting the design of an interior point algorithm, efficient in terms of robustness and computational time. Case studies compare the proposed approach with a general purpose optimization solver for quadratic problems and an algorithm for the predispatch problem that does not consider security constraints. The results show the benefits of using the method proposed in the paper, obtaining optimal power flow that is suitable to consider contingencies, with numerical stability and appropriate computational time.

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