Development of a Converter-Based Testing Platform and Battery Energy Storage System (BESS) Emulator for Microgrid Controller Function Evaluation

The microgrid has attracted increasing research attention in the last two decades. Due to the development of renewable energy resources and power electronics technologies, the future microgrid will trend to be smarter and more complicated. The microgrid controller performs a critical role in the microgrid operation, which will also become more and more sophisticated to support the future microgrid. Before final field deployment and test, the evaluation and testing of the controller is an indispensable step in the controller development, which requires a proper testing platform. However, existing simulation-based platforms have issues with potential numerical oscillation and may require huge computation resources for complex microgrid controllers. Meanwhile, field test-based controller evaluation is limited to the test conditions. Existing digital simulation-based platforms and field test-based platforms have limitations for microgrid controller testing. To provide a practical and flexible controller evaluation, a converter-based microgrid hardware testbed is designed and implemented considering the actual microgrid architecture and topology information. Compared with the digital simulation-based platforms, the developed microgrid testing platform can provide a more practical testing environment. Compared to the direct field test, the developed platform is more flexible to emulate different microgrids. As one of the key components, a converter-based battery energy storage system (BESS) emulator is proposed to complete the developed testing platform based on the testing requirements of microgrid controller functions. Meanwhile, the microgrid controller testing under different microgrid conditions is also considered. Two controllers for the microgrid with dynamic boundaries are tested to demonstrate the capability of the developed platform as well as the BESS emulator. Different testing cases are designed and tested to evaluate the controller performance under different microgrid conditions

Single-Image-Based Deep Learning for Segmentation of Early Esophageal Cancer Lesions

Accurate segmentation of lesions is crucial for diagnosis and treatment of early esophageal cancer (EEC). However, neither traditional nor deep learning-based methods up to today can meet the clinical requirements, with the mean Dice score - the most important metric in medical image analysis - hardly exceeding 0.75. In this paper, we present a novel deep learning approach for segmenting EEC lesions. Our approach stands out for its uniqueness, as it relies solely on a single image coming from one patient, forming the so-called "You-Only-Have-One" (YOHO) framework. On one hand, this "one-image-one-network" learning ensures complete patient privacy as it does not use any images from other patients as the training data. On the other hand, it avoids nearly all generalization-related problems since each trained network is applied only to the input image itself. In particular, we can push the training to "over-fitting" as much as possible to increase the segmentation accuracy. Our technical details include an interaction with clinical physicians to utilize their expertise, a geometry-based rendering of a single lesion image to generate the training set (the \emph{biggest} novelty), and an edge-enhanced UNet. We have evaluated YOHO over an EEC data-set created by ourselves and achieved a mean Dice score of 0.888, which represents a significant advance toward clinical applications

Modeling, Design, and Control of Power Electronic Converters for Unbalanced Load and Grounding of Microgrids

In this dissertation, the modeling, design, and control of power electronic converters are conducted for the unbalanced loads and groundings in the microgrid. First, from the system planning perspective, a detailed model for a grid-forming inverter is proposed considering the control impacts for unbalanced power flow analyses. The proposed model is applied for the unbalanced power flow analysis in the IEEE 13-bus and 34-systems. The results demonstrate that the proposed model can achieve a significant increase in the negative sequence (NS) voltage calculation accuracy. Second, a comprehensive analysis of NS current distribution among different grid-forming sources is conducted. The analysis considers different grid-forming source types and control implementations. The analysis is verified through simulation and experimental testing. A NS impedance design approach is proposed to realize the NS current distribution among different grid-forming sources (inverters and generators) in a microgrid with multiple source locations considering the topology impacts. The proposed method is demonstrated through simulation and experimental testing on a converter-based hardware testbed. To verify the proposed approach, a novel synchronous generator emulator is also proposed considering the unbalanced load impacts. Third, to deal with the potential loss of grounding in the islanded microgrid, two novel grounding schemes are proposed, which are an inverter-based grounding scheme and a controllable DER transformer-based grounding scheme. Simulation and experimental demonstration of two grounding schemes are also conducted. Then, the unbalanced load impacts on the power conditioning system (PCS) for a transformer-less asynchronous microgrid are analyzed. The PCS utilizes the modular multi-level converter (MMC) topology. Based on the analyses, the design and control solutions for the MMC are proposed and demonstrated on an actual 10 kV SiC MOSFET-based MMC up to 25 kV dc-link voltage. Moreover, the unbalanced load impacts on DER’s interfacing converter are analyzed. Based on the DER’s ripple capability, the control strategy is proposed for the dc/dc stage to eliminate or partially support the second-order frequency current from the unbalanced load. The design of the dc-link capacitors is also conducted. The dc-link capacitor design and the proposed control algorithms are verified through simulation and experimental testing

Modeling and Emulation of a Synchronous Generator Considering Unbalanced Load Conditions

Power electronics converters can be applied as emulators to mimic different grid components used for system behavior analyses and control validation. Synchronous generators (SGs) are the major sources of electric grids. Converter-based SG emulators have been developed for system stability analysis, fault analysis, and frequency support. However, existing SG emulators have not considered the impacts of load unbalance, which is a common phenomenon in distribution grids and will lead to system-level issues. In this article, a SG emulator considering an actual SG's negative sequence (NS) performance is developed for system analyses under unbalanced load conditions. With different simplifications, a SG can have different orders of electrical models. By deriving the NS performances of different SG electrical models, an appropriate SG electrical model in unbalanced load conditions is selected. Then a novel control diagram is proposed to ensure that the NS performances of the selected model can be fully realized. The derived NS models and the proposed control diagram are verified through simulation first and then validated with a converter-based hardware testbed

Risk preferences in self-other decisions: The effect of payoff allocation framing

The effect of framing is well established: Decision makers&#39; preferences are influenced by how outcomes or attributes are phrased. In the financial domain, individuals often make decisions for themselves and for others. Therefore, decisions in a two-person context with the outcome equally allocated can be framed in two ways defined as theallocation framing: (1) self-allocation frame: making a decision for oneself, with half the payoffs shared by another person; and (2) other-allocation frame: making a decision for the other person and sharing half the payoffs. The results of six studies provided consistent evidence that people are more risk seeking in the self-allocation frame than in the other-allocation frame, and the effect was only noteworthy in the gain domain-not the loss domain. Our findings on allocation framing provide a meaningful contribution to studies of self-other decision making.</p

Detection and Classification of Pole-like Landmarks for Domain-invariant 3D Point Cloud Map Matching

In 3D point cloud-based visual self-localization, pole landmarks have a great potential as landmarks for accurate and reliable localization due to their long-term stability under seasonal and weather changes. In this study, we aim to explore the use of recently developed deep learning models for pole classification in the context of pole landmark-based self-localization. Specifically, the proposed scheme consists of two main modules: pole map matching and pole class matching. In the former module, local pole map is constructed and its configuration is compared against a precomputed global pole map. An efficient RANSAC map matching is employed to achieve a good tradeoff between computational efficiency and accuracy. In the latter pole class matching module, the local and global poles paired by the RANSAC map-matching are further compared by means of pole attribute class. To this end, a predefined set of pseudo pole classes is learned via k-means clustering in a self-supervised manner. Experiments using publicly available NCLT dataset showed that the pole-like landmark classification method has an improved effect on the visual self-localization system compared with the baseline method.Comment: 4 pages, 3 figures, 1 table, draft version of a manuscript submitted to ICIVC202

Disulfiram, an aldehyde dehydrogenase inhibitor, works as a potent drug against sepsis and cancer via NETosis, pyroptosis, apoptosis, ferroptosis, and cuproptosis

Regulated cell death (RCD) is essential for maintaining cell homeostasis and preventing diseases. Besides classical apoptosis, several novel nonapoptotic forms of RCD including NETosis, pyroptosis, ferroptosis, and cuproptosis have been reported and are increasingly being implicated in various cancers and inflammation. Disulfiram (DSF), an aldehyde dehydrogenase inhibitor, has been used clinically for decades as an anti-alcoholic drug. New studies have shown that DSF possesses potent anti-inflammatory and anti-cancer effects by regulating these new types of RCD. Here, we summarize the mechanisms and discuss the potential application of DSF in the treatment of cancers and inflammatory diseases

Joint estimation of head pose and visual focus of attention.

International audienceHead pose is an important indicator of a person's visual focus of attention (VFoA). A traditional way to recognize VFoA is to consider accurate head pose or gaze estimations. However, these estimations usually degrade drastically in middle or low resolution video data. In this paper, a joint estimation of head pose and VFoA is proposed to address this issue; both head pose and VFoA are iteratively refined until convergence. This approach is evaluated in a specific scenario involving children around a table playing together with toys. Datasets are acquired and annotated by psychologists in Peking university. The experimental results demonstrate the usefulness of the join estimation process to recognize visual focus of attention in middle resolution video sequences

Microstructures and properties of wire-arc additively manufactured ultra-high strength aluminum alloy under different heat treatments

The microstructures, mechanical properties and corrosion behaviors of the ultra-high strength Al–Zn–Mg–Cu-Sc aluminum alloy fabricated by wire-arc additive manufacturing process using a self-prepared 7B55-Sc filler wire were systematically investigated under different heat treatments. The results showed that the microstructures of the as-deposited, T6, T73, and retrogression and re-aging (RRA) heat treatments were all composed of fine equiaxed grains with a size of about 6.0 μm. The grain boundary precipitates (GBPs) of the as-deposited sample were very coarse and continuously distributed along the grain boundaries, and the intragranular precipitates (IGPs) mainly consisted of a small amount of ηMg(Zn,Cu,Al)2 and η′ phases. After T6 heat treatment, the GBPs became much finer, but still continuously distributed along the grain boundaries. The IGPs mainly consisted of fine GP zones and η′ phases. After RRA heat treatment, the GBPs became coarser and discontinuously distributed along the grain boundaries. The IGPs were composed of η′ phases and ηMg(Zn,Cu,Al)2 phases. After T73 heat treatment, the GBPs became much coarser and sparsely distributed along the grain boundaries. The IGPs mainly consisted of coarser ηMg(Zn,Cu,Al)2 phases. The T6 heat-treated sample achieved the highest tensile strength of 618 MPa. While the strength of T73 heat-treated sample was sacrificed by up to 17% compared with the T6 heat-treated sample, but the corrosion resistance was the best of all heat-treated conditions. After RRA heat treatment, the strength was about 10% lower than the strength of the T6 condition, but the corrosion resistance was better than that of the T6 heat-treated sample