Analysis of Various Energy Storage Systems for Variable Speed Wind Turbines

During the high penetration of wind power, wind turbines can affect power quality directly due to an unstable and intermittency source. Voltage fluctuations, harmonics, and voltage drops might be factors in this environment. Energy storage systems (ESSs) with variable speed wind turbines (VSWTs) as a permanent magnetic synchronous generator (PMSG) and a doubly fed induction generator (DFIG) could be a solution to improve the power quality from the “variability” of wind power. This chapter investigates the proposed system, which comprises a hybrid ESS for the VSWT. It analyzes the ability of various ESSs (B, SC, and EDLC) based on VSWTs with various ESSs for power quality in terms of average THD (%) specified in reference to IEEE std-519-1992 and IEC 61400-21-Ed.2.0. In addition, this chapter investigates the DFIG with hybrid energy storage systems (Li ion battery and super capacitor ESS) for the economic evaluation in terms of payback time. The simulation results have been verified by a power system computer-aided design/electromagnetic transients direct current (PSCAD/EMTDC) to demonstrate the system performance under different scenarios

Caveat (IoT) Emptor: Towards Transparency of IoT Device Presence (Full Version)

As many types of IoT devices worm their way into numerous settings and many aspects of our daily lives, awareness of their presence and functionality becomes a source of major concern. Hidden IoT devices can snoop (via sensing) on nearby unsuspecting users, and impact the environment where unaware users are present, via actuation. This prompts, respectively, privacy and security/safety issues. The dangers of hidden IoT devices have been recognized and prior research suggested some means of mitigation, mostly based on traffic analysis or using specialized hardware to uncover devices. While such approaches are partially effective, there is currently no comprehensive approach to IoT device transparency. Prompted in part by recent privacy regulations (GDPR and CCPA), this paper motivates and constructs a privacy-agile Root-of-Trust architecture for IoT devices, called PAISA: Privacy-Agile IoT Sensing and Actuation. It guarantees timely and secure announcements about IoT devices' presence and their capabilities. PAISA has two components: one on the IoT device that guarantees periodic announcements of its presence even if all device software is compromised, and the other that runs on the user device, which captures and processes announcements. Notably, PAISA requires no hardware modifications; it uses a popular off-the-shelf Trusted Execution Environment (TEE) -- ARM TrustZone. This work also comprises a fully functional (open-sourced) prototype implementation of PAISA, which includes: an IoT device that makes announcements via IEEE 802.11 WiFi beacons and an Android smartphone-based app that captures and processes announcements. Both security and performance of PAISA design and prototype are discussed.Comment: 17 pages, 11 figures. To appear at ACM CCS 202

Comprehensive bias correction of regional climate model boundary conditions for simulation of hydrologic extremes.

High-impact extreme weather and climate events result that threaten society and ecosystems worldwide, from multiple interactions of atmospheric variables linked in dynamic ways. Ongoing global warming necessitates new ways of assessing how extreme events may change in the future. While global climate models (GCMs) have been utilised to assess the simulation of extreme events, the coarse spatial and temporal scales limit their effectiveness at regional or hydrological catchment scales. Regional climate models (RCMs) that use GCM datasets as input boundary conditions are commonly used to improve model predictability for extreme events. Although analyses of extreme events at the regional scale have evolved, systematic bias still exists and is passed onto the RCM simulation through biased boundary conditions simulated using coarser scale GCMs. Despite using various bias correction alternatives to address biases, these approaches often assume that inter-variable bias is not of key importance and that diurnal patterns are properly simulated by the GCM. However, such assumptions can result in substantial anomalies in the simulation of extreme events. Thus, this thesis investigates the impact that several bias correction alternatives can have on RCM boundary conditions with a focus on (1) Precipitation extremes; (2) Spatial, temporal, and multivariate aspects; (3) Multivariate relationships for extreme events; (4) Compound events; (5) Diurnal precipitation cycle; and develops a (6) Software tool for bias correction. The univariate techniques show improvement in precipitation extremes, but the discrepancies in inter-variable relationships are not adequately reduced through RCM boundaries. To address this issue, this study corrects the cross-dependence attributes of these fields, leading to substantial improvements in the statistics used. This study also shows that multivariate bias correction broadly represents the frequency of compound events better. The method is further developed to provide sub-daily corrections that are shown to improve the diurnal cycle of precipitation. Finally, a Python package has been developed as a software tool that simplifies the correction of systematic bias in RCM input boundary conditions. In conclusion, the work in this thesis demonstrates a significant improvement in the regional climate model simulation capacity, thereby enhancing water security and enabling more accurate forecasting of drought and flood events under climate change

Influence of multimodal integration on spatial perception

To design affective spaces that promote stabilized living experience and user well-being, it is necessary to consider and be aware of how multiple perceptual information interact and influence the way we perceive space i.e. multimodal perception. This study aims to gain an understanding of how sensory cues influence the emotional evaluation of the spatial design. We analyzed how the change in levels of spatial elements was emotionally perceived in the presence and absence of scent and color. The results from the study presented that both scent and color significantly affected the emotional response to change in levels of spatial elements in different ways. The findings suggest that (1) in the absence of both color and scent, the spatial elements interacted to affect the participants’ moods related to being confused and feeling strained and tensed, (2) in the presence of a cool color (purple) and relaxing scent (lavender), spatial elements interacted to affect the participants’ mood related to feeling strained and tensed, (3) in the presence of a warm color (orange) and stimulating scent (orange), spatial elements interacted to affect the participants’ mood related to being unhappy. The findings of the study are worthy as they provide an insight into the influence of multimodality in spatial perception. They will help establish guidelines for incorporating perceptual information in spatial designs that provide stabilized living experience and enhanced individual well-being

Online trajectory replan for gliding vehicle considering terminal velocity constraint

Controlling the terminal velocity can improve the effectiveness of guided missiles. In particular, a ballistic missile propelled by solid rocket motors can successfully accomplish its mission when it hits the target at an appropriate speed. In this study, a method for modifying the trajectory of gliding vehicle, i.e., gliding ballistic missiles is proposed to meet the terminal velocity constraint by reflecting the effects of the environment during a flight. The proposed framework consisting of trajectory generation and dynamic propagation compensates for errors due to uncertainties in real time. The trajectory generation step provides various trajectories that satisfy the given constraints based on information about the current state. The dynamic propagation step efficiently predicts the terminal velocity for each of the generated trajectories and finds the trajectory with the lowest terminal speed error. A numerical simulation is performed considering various conditions to demonstrate the performance of the proposed method

Third-order exceptional point in an ion-cavity system

We investigate a scheme for observing the third-order exceptional point (EP3) in an ion-cavity setting. In the lambda-type level configuration, the ion is driven by a pump field, and the resonator is probed with another weak laser field. We exploit the highly asymmetric branching ratio of an ion's excited state to satisfy the weak-excitation limit, which allows us to construct the non-Hermitian Hamiltonian $(H_{\textrm{nH}})$. Via fitting the cavity-transmission spectrum, the eigenvalues of $H_{\textrm{nH}}$ are obtained. The EP3 appears at a point where the Rabi frequency of the pump laser and the atom-cavity coupling constant balance the loss rates of the system. Feasible experimental parameters are provided.Comment: 9 pages, 6 figure

Ion trap with gold-plated alumina: substrate and surface characterization

We describe a complete development process of a segmented-blade linear ion trap. Alumina substrate is characterized with an X-ray diffraction and loss-tangent measurement. The blade is laser-micromachined and polished, followed by the sputtering and gold electroplating. Surface roughness is examined at each step of the fabrication via both electron and optical microscopies. On the gold-plated facet, we obtain a height deviation of tens of nanometers in the vicinity of the ion position. Trapping of laser-cooled $^{174}$Yb$^{+}$ ions is demonstrated.Comment: 7 pages, 6 figure