Trajectory optimization for voltage control via receding horizon control and mixed-integer programming

Voltage instability can be mitigated or avoided by coordination of appropriate control resources. In addition, to meet the power quality requirements, it is desirable to find the whole minimal-cost trajectory using available controls without violating any constraints. This is the trajectory optimization problem and intrinsically hard to solve in power systems because of the interactions between continuous dynamics and discrete or continuous controls. The hard constraints also add to the complexities. In this paper, the trajectory optimization problem is formulated as a mixed-integer quadratic programming (MIQP) problem which can reduce the computation burden. Due to the open-loop characteristics, this formulation will be subject to uncertainty and the system may not evolve as expected. However, the proposed framework embeds the MIQP formulations into receding horizon control (RHC) to compensate for uncertainties such as model error, disturbances, and noise. As a result, reasonable computation speed and improved accuracy are obtained.

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