Least Median Of Squares Estimation In Power Systems

Static state estimators currently in use in power systems are prone to masking by multiple bad data. This is mainly because the power system regression model contains many leverage points; typically they have a cluster pattern. As reported recently in the statistical literature, only high breakdown point estimators are robust enough to cope with gross errors corrupting such a model. This paper deals with one such estimator, the least median of squares estimator, developed by Rousseeuw in 1984. The robustness of this method is assessed while applying it to power systems. Resampling methods are developed, and simulation results for IEEE test systems discussed. © 1991 IEEE.

Flexible Sensor for Wearable Vital Sign Monitoring System

In modern society, the body health is a very important issue to everyone. With the development of the science and technology, the new and developed body health monitoring device and technology will play the key role in the daily medical activities. This paper focus on making progress in the design of the wearable vital sign system. A vital sign monitoring system has been proposed and designed. The whole detection system is composed of signal collecting subsystem, signal processing subsystem, short-range wireless communication subsystem and user interface subsystem. The signal collecting subsystem is composed of light source and photo diode, after emiting light of two different wavelength, the photo diode collects the light signal reflected by human body tissue. The signal processing subsystem is based on the analog front end AFE4490 and peripheral circuits, the collected analog signal would be filtered and converted into digital signal in this stage. After a series of processing, the signal would be transmitted to the short-range wireless communication subsystem through SPI, this subsystem is mainly based on Bluetooth 4.0 protocol and ultra-low power System on Chip(SoC) nRF51822. Finally, the signal would be transmitted to the user end. After proposing and building the system, this paper focus on the research of the key component in the system, that is, the photo detector. Based on the study of the perovskite materials, a low temperature processed photo detector has been proposed, designed and researched. The device is made up of light absorbing layer, electron transporting and hole blocking layer, hole transporting and electron blocking layer, conductive substrate layer and metal electrode layer. The light absorbing layer is the important part of whole device, and it is fabricated by perovskite materials. After accepting the light, the electron-hole pair would be produced in this layer, and due to the energy level difference, the electron and hole produced would be transmitted to metal electrode and conductive substrate electrode through electron transporting layer and hole transporting layer respectively. In this way the response current would be produced. Based on this structure, the specific fabrication procedure including substrate cleaning; PEDOT:PSS layer preparation; pervoskite layer preparation; PCBM layer preparation; C60, BCP, and Ag electrode layer preparation. After the device fabrication, a series of morphological characterization and performance testing has been done. The testing procedure including film-forming quality inspection, response current and light wavelength analysis, linearity and response time and other optical and electrical properties testing. The testing result shows that the membrane has been fabricated uniformly; the device can produce obvious response current to the incident light with the wavelength from 350nm to 800nm, and the response current could be changed along with the light wavelength. When the light wavelength keeps constant, there exists a good linear relationship between the intensity of the response current and the power of the incident light, based on which the device could be used as the photo detector to collect the light information. During the changing period of the light signal, the response time of the device is several microseconds, which is acceptable working as a photo detector in our system. The testing results show that the device has good electronic and optical properties, and the fabrication procedure is also repeatable, the properties of the devices has good uniformity, which illustrates the fabrication method and procedure could be used to build the photo detector in our wearable system. Based on a series of testing results, the paper has drawn the conclusion that the photo detector fabricated could be integrated on the flexible substrate and is also suitable for the monitoring system proposed, thus made some progress on the research of the wearable monitoring system and device. Finally, some future prospect in system design aspect and device design and fabrication aspect are proposed.

Dynamic-Data Driven Real-Time Identification for Electric Power Systems

Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.

Strategic Optimization Techniques For FRTU Deployment and Chip Physical Design

Combinatorial optimization is a complex engineering subject. Although formulation often depends on the nature of problems that differs from their setup, design, constraints, and implications, establishing a unifying framework is essential. This dissertation investigates the unique features of three important optimization problems that can span from small-scale design automation to large-scale power system planning: (1) Feeder remote terminal unit (FRTU) planning strategy by considering the cybersecurity of secondary distribution network in electrical distribution grid, (2) physical-level synthesis for microfluidic lab-on-a-chip, and (3) discrete gate sizing in very-large-scale integration (VLSI) circuit. First, an optimization technique by cross entropy is proposed to handle FRTU deployment in primary network considering cybersecurity of secondary distribution network. While it is constrained by monetary budget on the number of deployed FRTUs, the proposed algorithm identi?es pivotal locations of a distribution feeder to install the FRTUs in different time horizons. Then, multi-scale optimization techniques are proposed for digital micro?uidic lab-on-a-chip physical level synthesis. The proposed techniques handle the variation-aware lab-on-a-chip placement and routing co-design while satisfying all constraints, and considering contamination and defect. Last, the first fully polynomial time approximation scheme (FPTAS) is proposed for the delay driven discrete gate sizing problem, which explores the theoretical view since the existing works are heuristics with no performance guarantee. The intellectual contribution of the proposed methods establishes a novel paradigm bridging the gaps between professional communities.

Development and Verification of Control and Protection Strategies in Hybrid AC/DC Power Systems for Smart Grid Applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Simulation of Malfunctions in a Wind System Powered by a DFIG

The paper is about the simulation of malfunctions in an onshore wind energy conversion system powered by a doubly fed induction generator with a two-level power converter, handling only the slip power. These malfunctions are analysed in order to be able to investigate the impact in the wind power system behaviour by comparison before, during and after the malfunctions. The malfunctions considered in the simulation includes are localized in the DC-link of the converter and in the phase change in rectifier.

Short-Term Trading for a Wind-PV Power Producer in an Electricity Market

This paper deals with the problem of coordinated trading of wind and photovoltaic systems in order to find the optimal bid to submit in a pool-based electricity market. The coordination of wind and photovoltaic systems presents uncertainties not only due to electricity market prices, but also with wind and photovoltaic power forecast. Electricity markets are characterized by financial penalties in case of deficit or excess of generation. So, the aim o this work is to reduce these financial penalties and maximize the expected profit of the power producer. The problem is formulated as a stochastic linear programming problem. The proposed approach is validated with real data of pool-based electricity market of Iberian Peninsula.

Vanadium Redox Flow Battery Storage System Linked to the Electric Grid

This paper focuses on technology state of the art for the charge/discharge of electric energy storage supported by vanadium redox flow battery linked to the electric grid. Properties of vanadium, the main configuration and the reaction of charge/discharge of a vanadium redox flow battery are addressed. The vanadium redox flow battery has the highest cell voltage among the other redox flow battery, implying higher power and energy density which favours application at power plants. This electric energy storage is viewed as a promising contribution to be integrated in power system due to a reasonably bulky size and to successful applications currently allowing storage of energy at power plants or at electrical grids. For instances, allowing storage of energy as an economic improvement providing spin reserve to avoid penalty for imbalances between the energy delivered and energy contracted at closing of electricity market or as an economic improvement to diminish the cost of electricity usage of a consumer. The vanadium redox flow battery has the advantages of scalability customized to meet requirements for power and energy capacity and of excellent combination of energy efficiency, capital cost and life cycle costs compared with other technology.

Distributed and synchronized measurements for the wide-area observation of electric power systems in distorted and low-inertia conditions

With the aim of heading towards a more sustainable future, there has been a noticeable increase in the installation of Renewable Energy Sources (RES) in power systems in the latest years. Besides the evident environmental benefits, RES pose several technological challenges in terms of scheduling, operation, and control of transmission and distribution power networks. Therefore, it raised the necessity of developing smart grids, relying on suitable distributed measurement infrastructure, for instance, based on Phasor Measurement Units (PMUs). Not only are such devices able to estimate a phasor, but they can also provide time information which is essential for real-time monitoring. This Thesis falls within this context by analyzing the uncertainty requirements of PMUs in distribution and transmission applications. Concerning the latter, the reliability of PMU measurements during severe power system events is examined, whereas for the first, typical configurations of distribution networks are studied for the development of target uncertainties. The second part of the Thesis, instead, is dedicated to the application of PMUs in low-inertia power grids. The replacement of traditional synchronous machines with inertia-less RES is progressively reducing the overall system inertia, resulting in faster and more severe events. In this scenario, PMUs may play a vital role in spite of the fact that no standard requirements nor target uncertainties are yet available. This Thesis deeply investigates PMU-based applications, by proposing a new inertia index relying only on local measurements and evaluating their reliability in low-inertia scenarios. It also develops possible uncertainty intervals based on the electrical instrumentation currently used in power systems and assesses the interoperability with other devices before and after contingency events.

Design of a wearable platform for PPG analysis with multicore low-power processor

Photoplethysmography (PPG) sensors allow for noninvasive and comfortable heart-rate (HR) monitoring, suitable for compact wearable devices. However, PPG signals collected from such devices often suffer from corruption caused by motion artifacts. This is typically addressed by combining the PPG signal with acceleration measurements from an inertial sensor. Recently, different energy-efficient deep learning approaches for heart rate estimation have been proposed. To test these new solutions, in this work, we developed a highly wearable platform (42mm x 48 mm x 1.2mm) for PPG signal acquisition and processing, based on GAP9, a parallel ultra low power system-on-chip featuring nine cores RISC-V compute cluster with neural network accelerator and 1 core RISC-V controller. The hardware platform also integrates a commercial complete Optical Biosensing Module and an ARM-Cortex M4 microcontroller unit (MCU) with Bluetooth low-energy connectivity. To demonstrate the capabilities of the system, a deep learning-based approach for PPG-based HR estimation has been deployed. Thanks to the reduced power consumption of the digital computational platform, the total power budget is just 2.67 mW providing up to 5 days of operation (105 mAh battery).

Acquisition of Vibration Signals for Predictive Maintenance: a Practical Case

As predictive maintenance becomes more and more relevant in industrial environment, the possible range of applications for this maintenance strategy grows. The progresses in components technology and their reduction in price, together with the late years' advances in machine learning and in computational power, are making the implementation of predictive maintenance possible in plants where it would have previously been unreasonably costly. This is leading major pharmaceutical industries to explore the possibility of the application of condition monitoring systems on progressively less and less critical equipment. The focus of this thesis is on the implementation of a system to gather vibrational data from the motors installed in a pre-existing machine using off-the-shelf components. The final goal for the system is to provide the necessary vibration data, in the form of frequency spectra, to a machine learning system developed by IMA Digital, which will be leveraging such data to predict possible upcoming faults and to give the final client all the information necessary to plan maintenance activity according to the estimated machine condition.

Low Power instrument Transformer: technologies and applications

Instrument transformers serve an important role in the protection and isolation of AC electrical systems for measurements of different electrical parameters like voltage, current, power factor, frequency, and energy. As suggested by name these transformers are used in connection with suitable measuring instruments like an ammeter, wattmeter, voltmeter, and energy meters. We have seen how higher voltages and currents are transformed into lower magnitudes to provide isolation between power networks, relays, and other instruments. Reducing transient, suppressing electrical noises in sensitive devices, standardization of instruments and relays up to a few volts and current. Transformer performance directly affects the accuracy of power system measurements and the reliability of relay protection. We classified transformers in terms of purpose, insulating medium, Voltage ranges, temperature ranges, humidity or environmental effect, indoor and outdoor use, performance, Features, specification, efficiency, cost analysis, application, benefits, and limitations which enabled us to comprehend their correct use and selection criteria based on our desired requirements. We also discussed modern Low power instrument transformer products that are recently launched or offered by renowned companies like Schneider Electric, Siemens, ABB, ZIV, G&W etc. These new products are innovations and problem solvers in the domain of measurement, protection, digital communication, advance, and commercial energy metering. Since there is always some space for improvements to explore new advantages of Low power instrument transformers in the domain of their wide linearity, high-frequency range, miniaturization, structural and technological modification, integration, smart frequency modeling, and output prediction of low-power voltage transformers.

Design and Implementation of Single phase 230V to Three Phase Inverter Based on the Embedded System STM-32 Applied to motor control

In the field of Power Electronics, several types of motor control systems have been developed using STM microcontroller and power boards. In both industrial power applications and domestic appliances, power electronic inverters are widely used. Inverters are used to control the torque, speed, and position of the rotor in AC motor drives. An inverter delivers constant-voltage and constant-frequency power in uninterruptible power sources. Because inverter power supplies have a high-power consumption and low transfer efficiency rate, a three-phase sine wave AC power supply was created using the embedded system STM32, which has low power consumption and efficient speed. It has the capacity of output frequency of 50 Hz and the RMS of line voltage. STM32 embedded based Inverter is a power supply that integrates, reduced, and optimized the power electronics application that require hardware system, software, and application solution, including power architecture, techniques, and tools, approaches capable of performance on devices and equipment. Power inverters are currently used and implemented in green energy power system with low energy system such as sensors or microcontroller to perform the operating function of motors and pumps. STM based power inverter is efficient, less cost and reliable. My thesis work was based on STM motor drives and control system which can be implemented in a gas analyser for operating the pumps and motors. It has been widely applied in various engineering sectors due to its ability to respond to adverse structural changes and improved structural reliability. The present research was designed to use STM Inverter board on low power MCU such as NUCLEO with some practical examples such as Blinking LED, and PWM. Then we have implemented a three phase Inverter model with Steval-IPM08B board, which converter single phase 230V AC input to three phase 380 V AC output, the output will be useful for operating the induction motor.

Graph-based User Scheduling for MIMO LEO-based Satellite Communication Systems

The study of the user scheduling problem in a Low Earth Orbit (LEO) Multi-User MIMO system is the objective of this thesis. With the application of cutting-edge digital beamforming algorithms, a LEO satellite with an antenna array and a large number of antenna elements can provide service to many user terminals (UTs) in full frequency reuse (FFR) schemes. Since the number of UTs on-ground are many more than the transmit antennas on the satellite, user scheduling is necessary. Scheduling can be accomplished by grouping users into different clusters: users within the same cluster are multiplexed and served together via Space Division Multiple Access (SDMA), i.e., digital beamforming or Multi-User MIMO techniques; the different clusters of users are then served on different time slots via Time Division Multiple Access (TDMA). The design of an optimal user grouping strategy is known to be an NP-complete problem which can be solved only through exhaustive search. In this thesis, we provide a graph-based user scheduling and feed space beamforming architecture for the downlink with the aim of reducing user inter-beam interference. The main idea is based on clustering users whose pairwise great-circle distance is as large as possible. First, we create a graph where the users represent the vertices, whereas an edge in the graph between 2 users exists if their great-circle distance is above a certain threshold. In the second step, we develop a low complex greedy user clustering technique and we iteratively search for the maximum clique in the graph, i.e., the largest fully connected subgraph in the graph. Finally, by using the 3 aforementioned power normalization techniques, a Minimum Mean Square Error (MMSE) beamforming matrix is deployed on a cluster basis. The suggested scheduling system is compared with a position-based scheduler, which generates a beam lattice on the ground and randomly selects one user per beam to form a cluster.

Collision probabilities in the rarefaction fan of asymmetric exclusion processes

We consider the one-dimensional asymmetric simple exclusion process (ASEP) in which particles jump to the right at rate p is an element of (1/2, 1.] and to the left at rate 1 - p, interacting by exclusion. In the initial state there is a finite region such that to the left of this region all sites are occupied and to the right of it all sites are empty. Under this initial state, the hydrodynamical limit of the process converges to the rarefaction fan of the associated Burgers equation. In particular suppose that the initial state has first-class particles to the left of the origin, second-class particles at sites 0 and I, and holes to the right of site I. We show that the probability that the two second-class particles eventually collide is (1 + p)/(3p), where a collision occurs when one of the particles attempts to jump over the other. This also corresponds to the probability that two ASEP processes. started from appropriate initial states and coupled using the so-called ""basic coupling,"" eventually reach the same state. We give various other results about the behaviour of second-class particles in the ASEP. In the totally asymmetric case (p = 1) we explain a further representation in terms of a multi-type particle system, and also use the collision result to derive the probability of coexistence of both clusters in a two-type version of the corner growth model.