In power distribution systems, the goal of the voltage and reactive power control is to maintain acceptable voltage at all points along the distribution feeder under all load conditions. This should be done in the most costefficient manner. The control is usually conducted by switching devices such as shunt capacitors and transformer load tap changers in response to changing load conditions. This paper considers voltage and reactive power control models that explicitly take into account the operational costs of switching devices and the correlation between loads and voltage profiles. In addition to maintaining acceptable voltage at all points along the distribution feeder, the aim is to determine the proper settings of shunt capacitors and transformer load tap changers in order to minimize the energy loss or the total energy consumption over a selected planning horizon. A random search algorithm called approximate stochastic annealing is proposed for optimizing these models. The algorithm searches the optimal control schedule by randomly sampling from a sequence of probability distributions over the space of all possible settings of tap changers and shunt capacitors. The algorithm is shown to be globally convergent and its effectiveness is illustrated by comparing its performance with that of three other commonly used procedures on a 69-bus distribution system and a 24-bus system with distributed generation.
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