Stochastic meter placement algorithm for active distribution networks suitable for parallel processing

Present distribution networks need significant enhancements in sensor and measurement instrumentation to accommodate the future requirements of distributed generators and active operation. Additional sensor data can allow distribution state estimation to generate useful information on the operating state. A major challenge arises as the investment in new meters has to be economical while achieving sufficiently trustworthy estimation. In this paper, we propose a stochastic meter placement algorithm that enhances the accuracy, as well as improving the numerical robustness of the distribution state estimation tool. The proposed algorithm supports parallel computation which can effectively reduce the computation time.