Online decentralized tracking for nonlinear time-varying optimal power flow of coupled transmission-distribution grids

The coordinated alternating current optimal power flow (ACOPF) for coupled transmission-distribution grids has become crucial to handle problems related to high penetration of renewable energy sources (RESs). However, obtaining all system details and solving ACOPF centrally is not feasible because of privacy concerns. Intermittent RESs and uncontrollable loads can swiftly change the operating condition of the power grid. Existing decentralized optimization methods can seldom track the optimal solutions of time-varying ACOPFs. Here, we propose an online decentralized optimization method to track the time-varying ACOPF of coupled transmission-distribution grids. First, the time-varying ACOPF problem is converted to a dynamic system based on Karush-Kuhn-Tucker conditions from the control perspective. Second, a prediction term denoted by the partial derivative with respect to time is developed to improve the tracking accuracy of the dynamic system. Third, a decentralized implementation for solving the dynamic system is designed based on only a few information exchanges with respect to boundary variables. Moreover, the proposed algorithm can be used to directly address nonlinear power flow equations without relying on convex relaxations or linearization techniques. Numerical test results reveal the effectiveness and fast-tracking performance of the proposed algorithm.Comment: 18 pages with 15 figure

Imaging spontaneous MMTVneu transgenic murine mammary tumors: targeting metabolic activity versus genetic products.

INTRODUCTION: Despite the great strides made in imaging breast cancer (BC) in humans, the current imaging modalities miss up to 30% of BC, do not distinguish malignant lesions from benign ones, and require histologic examinations for which invasive biopsy must be performed. Annually in the United States, approximately 5.6 million biopsies find benign lesions. More than 50% of human BCs overexpress cyclin D1, and all BCs exhibit VPAC1 oncogene products. Together, these gene products may provide an excellent biomarker for the early and accurate detection of BC. We have evaluated 4 biologically active peptide analogs that have high affinity for VPAC1. The transgenic MMTVneu mice spontaneously develop BC and metastatic lesions that overexpress cyclin D1 and VPAC1 biomarkers. The MMTVneu mouse, therefore, provides an excellent animal model that mimics the pathogenesis of human BC. The objective of this investigation was to determine the ability of 1 of the peptide analogs, (64)Cu-TP3805, to detect BC in MMTVneu mice using (18)F-FDG as a gold standard. METHODS: The transgenic MMTVneu mouse colony was maintained. Offspring were screened for transgenic status by reverse transcriptase polymerase chain reaction (RT-PCR). Nine mice with visible, palpable, or unknown metastatic lesions were entered into the protocol. (18)F-FDG (6,475 +/- 1,628 kBq [175 +/- 44 microCi]) PET served as a control, followed by a CT scan and 24-48 h later by PET with (64)Cu-TP3805 (4,588 +/- 962 kBq [124 +/- 26 microCi]). RT-PCR on excised tumors determined VPAC1 expression, and histology ascertained the pathology. RESULTS: Ten tumors were detected by PET. Four tumors were detected both by (18)F-FDG and by (64)Cu-TP3805. Additionally, 4 tumors were imaged with (64)Cu-TP3805 only. These 8 tumors overexpressed VPAC1 receptors and were malignant by histology. The 2 remaining tumors were visualized with (18)F-FDG only. These tumors did not express the VPAC1 oncogene product and had benign histology. The standard uptake value ranged from 3.1 to 18.3 for (64)Cu-TP3805 and 0.9 to 1.4 for (18)F-FDG. CONCLUSION: (64)Cu-TP3805 identified all malignant lesions unequivocally that overexpressed the VPAC1 oncogene surface product. The 2 benign tumors that did not express the VPAC1 receptor were not imaged. (64)Cu-TP3805 promises to have the potential for the early and accurate imaging of primary and metastatic BC