Abstract-Identification of a low-level point radiation source amidst background radiation is achieved by a network of radiation sensors using a two-step approach. Based on measurements from three sensors, the geometric difference triangulation method is used to estimate the location and strength of the source. Then a sequential probability ratio test based on current measurements and estimated parameters is employed to finally decide: (i) presence of a source with the estimated parameters, or (ii) absence of the source, or (iii) insufficiency of measurements to make a decision. This method achieves the specified levels of false alarm and missed detection probabilities, while ensuring close to minimal number of measurements to reach a decision. This method minimizes the ghost-source problem of the current estimation methods and achieves lower false alarm rate compared to current detection methods. This method is tested and demonstrated using: (a) simulations, and (b) a test-bed that utilizes the scaling properties of point radiation sources to emulate high intensity ones that cannot be easily and safely handled in experimentation.
This paper studies the generation and transmission expansion co-optimization problem with a high wind power penetration rate in large-scale power grids. In this paper, generation and transmission expansion co-optimization is modeled as a mixed-integer programming (MIP) problem. A scenario creation method is proposed to capture the variation and correlation of both load and wind power across regions for largescale power grids. Obtained scenarios that represent load and wind uncertainties can be easily introduced into the MIP problem and then solved to obtain the co-optimized generation and transmission expansion plan. Simulation results show that the proposed planning model and the scenario creation method can improve the expansion result significantly through modeling more detailed information of wind and load variation among regions in the US EI system. The improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare in large-scale power grids.
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