DHP-Based Wide-Area Coordinating Control of a Power System with a Large Wind Farm and Multiple FACTS Devices

Wide-area coordinating control is becoming an important issue and a challenging problem in the power industry. This paper proposes a novel optimal wide-area monitor and wide-area coordinating neurocontroller (WACNC), based on wide-area measurements, for a power system with power system stabilizers, a large wind farm, and multiple flexible ac transmission system (FACTS) devices. The wide-area monitor is a radial basis function neural network (RBFNN) that identifies the input-output dynamics of the nonlinear power system. Its parameters are optimized through a particle swarm optimization (PSO) based method. The WACNC is designed by using the dual heuristic programming (DHP) method and RBFNNs. It operates at a global level to coordinate the actions of local power system controllers. Each local controller communicates with the WACNC, receives remote control signals from the WACNC to enhance its dynamic performance, and therefore helps improve system-wide dynamic and transient performance

Intelligent comprehensive control and monitor of proton exchange membrane fuel cell for hybrid UPS system

This paper, to improve the performance of a Proton Exchange Membrane fuel cell (PEMFC) stack, avoid the hydrogen and oxygen/air starvation of electrochemical reaction and the performance deterioration of the stack, prevent the dehydration and drying of the membrane, keep the water content in the membrane, heighten the utilization of the gases, and track the output power of a hybrid uninterruptible power supply (UPS) system with backup PEMFC and battery power sources, conducts research in the dynamic model, the on-line parameters monitoring of PEMFC, such as the resistance in the PEMFC stack using the current interrupt method and the performance improvement of the PEMFC employing an intelligent comprehensive control strategy of the operation parameters, such as operating temperature, pressures and mass flows of hydrogen and air, the output current and voltage for the PEMFC stack, the power supply switching between PEMFC and battery. The intelligent comprehensive control and monitor method is proposed and applied to the PEMFC generating system employed for the power source of UPS. The experimental results show that the proposal method can effectively monitor and control the pressures of the inlet hydrogen and the operating temperature of the stack, automatically switch the power supply between PEMFC and battery, efficaciously prevent the destroy of the stack when the load changes sharply, the hydrogen is purged and the output current is interrupted regularly, and reasonably improve the performance of the PEMFC through the water balance and thermal management, and real-time realize the tracking for the changes of the output power and the distribution of the mass flow rates of hydrogen and air. © 2009 IEEE

Automated Intelligent Monitoring and the Controlling Software System for Solar Panels

The inspection of the solar panels on a periodic basis is important to improve longevity and ensure performance of the solar system. To get the most solar potential of the photovoltaic (PV) system is possible through an intelligent monitoring & controlling system. The monitoring & controlling system has rapidly increased its popularity because of its user-friendly graphical interface for data acquisition, monitoring, controlling and measurements. In order to monitor the performance of the system especially for renewable energy source application such as solar photovoltaic (PV), data-acquisition systems had been used to collect all the data regarding the installed system. In this paper the development of a smart automated monitoring & controlling system for the solar panel is described, the core idea is based on IoT (the Internet of Things). The measurements of data are made using sensors, block management data acquisition modules, and a software system. Then, all the real-time data collection of the electrical output parameters of the PV plant such as voltage, current and generated electricity is displayed and stored in the block management. The proposed system is smart enough to make suggestions if the panel is not working properly, to display errors, to remind about maintenance of the system through email or SMS, and to rotate panels according to a sun position using the Ephemeral table that stored in the system. The advantages of the system are the performance of the solar panel system which can be monitored and analyzed

Automated Intelligent Monitoring and the Controlling Software System for Solar Panels

The inspection of the solar panels on a periodic basis is important to improve longevity and ensure performance of the solar system. To get the most solar potential of the photovoltaic (PV) system is possible through an intelligent monitoring & controlling system. The monitoring & controlling system has rapidly increased its popularity because of its user-friendly graphical interface for data acquisition, monitoring, controlling and measurements. In order to monitor the performance of the system especially for renewable energy source application such as solar photovoltaic (PV), data-acquisition systems had been used to collect all the data regarding the installed system. In this paper the development of a smart automated monitoring & controlling system for the solar panel is described, the core idea is based on IoT (the Internet of Things). The measurements of data are made using sensors, block management data acquisition modules, and a software system. Then, all the real-time data collection of the electrical output parameters of the PV plant such as voltage, current and generated electricity is displayed and stored in the block management. The proposed system is smart enough to make suggestions if the panel is not working properly, to display errors, to remind about maintenance of the system through email or SMS, and to rotate panels according to a sun position using the Ephemeral table that stored in the system. The advantages of the system are the performance of the solar panel system which can be monitored and analyzed

Smart monitoring of constructed wetlands to improve efficiency and water quality

The Smart monitoring of constructed wetlands to improve efficiency and water quality (SmarterCW) project aims to monitor biological wastewater treatment processes by gathering continuous data from remote water and environmental sensors. The acquired data can be processed and analysed through data science tools to better understand the complex and coupled phenomena underneath wastewater treatment, as well as, to monitor and optimize the system performance. The results will improve the efficiency and control of nature-based wastewater treatment technologies. The methodology comprises the following tasks and activities: Implementation of a set of electrochemical sensors in the input and output flow streams of pilot-scale constructed wetlands; Acquisition of water quality parameters such as pH, electrical conductivity, temperature, and ionic compounds; Acquisition of environmental parameters, such as temperature and humidity; Application of data analysis tools to design and optimize conceptual models to correlate pollutants removal with operative parameters in green technologies for wastewater treatment. This methodology was applied to a patent-protected pilot-scale modular constructed wetland in which filling media consists of a mixture of solid waste. The system is complemented by a high-level IoT communication layer structure to support remote real-time water and environmental monitoring, system performance, and data dissemination. The project contributes to: Water and Environment through the efficient management and use of water resources and waste reduction, management, treatment, and valorisation; Materials and raw-materials through efficient, secure, and sustainable use of resources; and Environmental Education promoting environmental awareness and best environmental practices through the dissemination of scientific data and results using Information and Communication Technologies (ICT) tools and IoT platforms. The project also contributes to giving response to Societal Challenges, such as Environment protection, sustainable management of natural resources, water, biodiversity, and ecosystems; Enabling the transition to a green society and economy through eco-innovation.info:eu-repo/semantics/submittedVersio

Parallel-connected solar arrays

The purpose of this thesis is to investigate the advantages of having various series-parallel configurations of solar arrays and make a comparison between them. The objective is to determine the best PV system configuration and thus improve the overall efficiency of a solar array. The primary focus of this thesis is to study the parallel connection of PV panels for achieving maximum efficiency while extracting maximum energy from the solar radiation. A comparison between a series connected and a parallel connected solar PV array justifies the need for installing a parallel configured solar PV array to achieve optimum performance. The DC-DC converter plays an important role in delivering maximum power to the load. A solar sensor array was used to monitor the solar radiation under various climatic conditions. Data saved using these sensors was then analyzed using software developed with MATLAB\u27s Graphical User Interface (GUI) platform. The PV-cell equations cannot be solved with the ordinary numerical method due to both the complexity and their non-linearity. These calculation were simplified through using the Newton-Raphson (NR) method along with other numerical approximation approaches. The software package is capable of displaying a number of curves including the I-V characteristic, the output power, and the output energy of the PV-panels for different configurations. Various scenarios were simulated and compared under different climatic conditions. The proposed method for parallel configured PV panel was found to be an alternative to existing methods --Abstract, page iii

Environmental Audit improvements in industrial systems through FRAM

Environmental risk management requires specific methodologies to focus audit activities on the most critical elements of production systems. Limited resources require a clear motivation to put attention on specific technological, human, organizational components, and often should address the monitor of interactions among these elements. Recent research in environmental risk looks at methods to deal with complexity as interesting tools to reduce real impacts on pollution and consumption. In this paper, we provide evidence of the advantage in using the Functional Resonance Analysis Method (FRAM), not only to identify the criticalities of a complex production system but to provide a methodology to continuously improve the audit activities in parallel with the introduction of technique to reduce environmental risk. The case study presents the evolution of environmental audit in a sinter plant, proving the need for a review of the criticality list and the successful application of FRAM to refocus the control activities

Real-Time High Jump Wearable Device with ESP8266 for High-Performance and Low-Injury

In the world of sports, the injury is unavoidable, however, the performance is the first priority. The percentage of the athletes to get injured is very high due to the fallibility of athlete jumping themselves. Therefore, this study presents the design and implementation of high-performance and low-injury real-time high jump wearable device by using ESP8266 microcontroller. The proposed wearable device is built because of there is no device to monitor this sport during training. There are three (3) parts have been integrated to build this wearable device – input, process and output. The input consists of global positioning system (GPS) sensor that attached to the waist and force sensing resistor (FSR) sensor was placed at the bottom of the ankle as a wireless input for data captured. These data were then being processed by ESP8266 microcontroller hardware device with an embedded wireless fidelity (Wi-Fi) module on the same chip that has been programmed and results obtained were displayed via the mobile app. Graphical user interface (GUI) of the wearable device has been designed using C language code using OpenHAB software and data from the wearable device were also available in log formats. The outcomes obtained have shown encouraging results since all data can be visualised and monitored in real-time, history of the training can be retrieved and the benchmark data acts as a guide to the other athlete to improve the performance

Intelligent optical performance monitor using multi-task learning based artificial neural network

An intelligent optical performance monitor using multi-task learning based artificial neural network (MTL-ANN) is designed for simultaneous OSNR monitoring and modulation format identification (MFI). Signals' amplitude histograms (AHs) after constant module algorithm are selected as the input features for MTL-ANN. The experimental results of 20-Gbaud NRZ-OOK, PAM4 and PAM8 signals demonstrate that MTL-ANN could achieve OSNR monitoring and MFI simultaneously with higher accuracy and stability compared with single-task learning based ANNs (STL-ANNs). The results show an MFI accuracy of 100% and OSNR monitoring root-mean-square error of 0.63 dB for the three modulation formats under consideration. Furthermore, the number of neuron needed for the single MTL-ANN is almost the half of STL-ANN, which enables reduced-complexity optical performance monitoring devices for real-time performance monitoring

Security Analysis of an Untrusted Source for Quantum Key Distribution: Passive Approach

We present a passive approach to the security analysis of quantum key distribution (QKD) with an untrusted source. A complete proof of its unconditional security is also presented. This scheme has significant advantages in real-life implementations as it does not require fast optical switching or a quantum random number generator. The essential idea is to use a beam splitter to split each input pulse. We show that we can characterize the source using a cross-estimate technique without active routing of each pulse. We have derived analytical expressions for the passive estimation scheme. Moreover, using simulations, we have considered four real-life imperfections: Additional loss introduced by the "plug & play" structure, inefficiency of the intensity monitor, noise of the intensity monitor, and statistical fluctuation introduced by finite data size. Our simulation results show that the passive estimate of an untrusted source remains useful in practice, despite these four imperfections. Also, we have performed preliminary experiments, confirming the utility of our proposal in real-life applications. Our proposal makes it possible to implement the "plug & play" QKD with the security guaranteed, while keeping the implementation practical.Comment: 35 pages, 19 figures. Published Versio