Automatic Controller for Teleoperated Switching between Multiple Energy Sources in a Residential Building Nanogrid

Erratic power supply from the utility grid has grave effect of the development of several countries. In a bid to overcome this challenge, many residential buildings have become electrically self-sustaining by the integration of various backup power supply source. Yet the act of transition from one source to another has remained a manual task that tends to discourage users from going through the rigour. Internal combustion engine AC generators and batteries have been found to be the most common backup options. An automatic transition system that gives user the flexibility of monitoring and controlling resources remotely from a mobile phone application is thus presented in this paper. The microcontroller-based system monitors the status of the energy resources and protects the building against undervoltage or overvoltage conditions. Based on the state of charge of the battery and the fuel level in the generator, the system activates the appropriate alternative backup source in the event of an outage form the grid supply. This system affords users a new level of comfort and reliability of power supply, as in the automatic mode, the users are guaranteed power supply with minimal downtime, except when all resources are unavailable. Keywords: Automatic Transfer Switch, Nanogrids, Remote Monitoring and Control DOI: 10.7176/ISDE/11-5-03 Publication date:September 30th 2020

OSEM : occupant-specific energy monitoring.

Electricity has become prevalent in modern day lives. Almost all the comforts people enjoy today, like home heating and cooling, indoor and outdoor lighting, computers, home and office appliances, depend on electricity. Moreover, the demand for electricity is increasing across the globe. The increasing demand for electricity and the increased awareness about carbon footprints have raised interest in the implementation of energy efficiency measures. A feasible remedy to conserve energy is to provide energy consumption feedback. This approach has suggested the possibility of considerable reduction in the energy consumption, which is in the range of 3.8% to 12%. Currently, research is on-going to monitor energy consumption of individual appliances. However, various approaches studied so far are limited to group-level feedback. The limitation of this approach is that the occupant of a house/building is unaware of his/her energy consumption pattern and has no information regarding how his/her energy-related behavior is affecting the overall energy consumption of a house/building. Energy consumption of a house/building largely depends on the energy-related behavior of individual occupants. Therefore, research in the area of individualized energy-usage feedback is essential. The OSEM (Occupant-Specific Energy Monitoring) system presented in this work is capable of monitoring individualized energy usage. OSEM system uses the electromagnetic field (EMF) radiated by appliances as a signature for appliance identification. An EMF sensor was designed and fabricated to collect the EMF radiated by appliances. OSEM uses proximity sensing to confirm the energy-related activity. Once confirmed, this activity is attributed to the occupant who initiated it. Bluetooth Low Energy technology was used for proximity sensing. This OSEM system would provide a detailed energy consumption report of individual occupants, which would help the occupants understand their energy consumption patterns and in turn encourage them to undertake energy conservation measures

Contribuitions and developments on nonintrusive load monitoring

Energy efficiency is a key subject in our present world agenda, not only because of greenhouse gas emissions, which contribute to global warming, but also because of possible supply interruptions. In Brazil, energy wastage in the residential market is estimated to be around 15%. Previous studies have indicated that the most savings were achieved with specific appliance, electricity consumption feedback, which caused behavioral changes and encouraged consumers to pursue energy conservation. Nonintrusive Load Monitoring (NILM) is a relatively new term. It aims to disaggregate global consumption at an appliance level, using only a single point of measurement. Various methods have been suggested to infer when appliances are turned on and off, using the analysis of current and voltage aggregated waveforms. Within this context, we aim to provide a methodology for NILM to determine which sets of electrical features and feature extraction rates, obtained from aggregated household data, are essential to preserve equivalent levels of accuracy; thus reducing the amount of data that needs to be transferred to, and stored on, cloud servers. As an addendum to this thesis, a Brazilian appliance dataset, sampled from real appliances, was developed for future NILM developments and research. Beyond that, a low-cost NILM smart meter was developed to encourage consumers to change their habits to more sustainable methods.Eficiência energética é um assunto essencial na agenda mundial. No Brasil, o desperdício de energia no setor residencial é estimado em 15%. Estudos indicaram que maiores ganhos em eficiência são conseguidos quando o usuário recebe as informações de consumo detalhadas por cada aparelho, provocando mudanças comportamentais e incentivando os consumidores na conservação de energia. Monitoramento não intrusivo de cargas (NILM da sigla em inglês) é um termo relativamente novo. A sua finalidade é inferir o consumo de um ambiente até observar os consumos individualizados de cada equipamento utilizando-se de apenas um único ponto de medição. Métodos sofisticados têm sido propostos para inferir quando os aparelhos são ligados e desligados em um ambiente. Dentro deste contexto, este trabalho apresenta uma metodologia para a definição de um conjunto mínimo de características elétricas e sua taxa de extração que reduz a quantidade de dados a serem transmitidos e armazenados em servidores de processamento de dados, preservando níveis equivalentes de acurácia. São utilizadas diferentes técnicas de aprendizado de máquina visando à caracterização e solução do problema. Como adendo ao trabalho, apresenta-se um banco de dados de eletrodomésticos brasileiros, com amostras de equipamentos nacionais para desenvolvimentos futuros em NILM, além de um medidor inteligente de baixo custo para desagregação de cargas, visando tornar o consumo de energia mais sustentável

Physiological sensor.

For the purpose of medical diagnosis and research, various physiological signals, such as Photoplethysmograph (PPG), Galvanic Skin Response (GSR) and Skin Temperature (SKT), are measured by different types of medical sensor equipment. However, the sensors are intrusive and the patients must endure some discomfort when encountering these types of medical sensor equipment. These bio sensors also fail to be implemented outside of lab or clinical settings. Recently the development in sensor technology and wireless communication technology have significantly improved the integration of wearable systems, so that we could find new ways to minimize the wearable circuits module, design layers of fabric for wearable system. This thesis documents the successful development of a novel, unobtrusive, low-cost, wrist-worn integrated sensors (PPG, GSR, SKT) system using wireless wearable technology capable of measuring real-time data collection, and monitoring which is important when dealing with treatment and management of many chronic illnesses, neurological disorders, and mental health issues. Examples can include: epileptic seizures, autism spectrum disorder (ASD), depression, drug addiction, and anxiety disorders

Monitoring System for Laboratory Mice Transportation: A Novel Concept for the Measurement of Physiological and Environmental Parameters

Laboratory mice are used in biomedical research as “models” for studying human disease. These mice may be subject to significant levels of stress during transportation that can cause alterations that could negatively affect the results of the performed investigation. Here, we present the design and realization of a prototypical transportation container for laboratory mice, which may contribute to improved laboratory animal welfare. This prototype incorporates electric potential integrated circuit (EPIC) sensors, which have been shown to allow the recording of physiological parameters (heart rate and breathing rate) and other sensors for recording environmental parameters during mouse transportation. This allows for the estimation of the stress levels suffered by mice. First experimental results for capturing physiological and environmental parameters are shown and discussed

A Non Intrusive Low Cost Kit for Electric Power Measuring and Energy Disaggregation

This article presents a kit to collect data of electric loads of single and three phases main power supply of a house and perform the energy disaggregation. To collect the data, we use sensors based on open magnetic core to measure the electromagnetic field induced by the current in the electric conducting wire in a non intrusive way. In particular, each sensor from the three-phase device wraps/encloses each phase without alignment. In order to calibrate the three-phase device, we present a method to calculate the neutral RMS without complex numbers using (Analysis of Variance) ANOVA and post hoc Tukey’s multiple comparison test to assert the differences of measures among phases. We managed to validate the method using a measure reference. Additionally, to perform the energy disaggregation, we use the NILMTK tool. This toll was used, initially, to compare disaggregation algorithms on many public datasets. We use in our system two disaggregation algorithms Combinatorial Optimization and Factorial Hidden Markov Model algorithms. The results show that is possible to collect and perform energy disaggregation through our embedded system

A Non Intrusive Low Cost Kit for Electric Power Measuring and Energy Disaggregation

This article presents a kit to collect data of electric loads of single and three phases main power supply of a house and perform the energy disaggregation. To collect the data, we use sensors based on open magnetic core to measure the electromagnetic field induced by the current in the electric conducting wire in a non intrusive way. In particular, each sensor from the three-phase device wraps/encloses each phase without alignment. In order to calibrate the three-phase device, we present a method to calculate the neutral RMS without complex numbers using (Analysis of Variance) ANOVA and post hoc Tukey’s multiple comparison test to assert the differences of measures among phases. We managed to validate the method using a measure reference. Additionally, to perform the energy disaggregation, we use the NILMTK tool. This toll was used, initially, to compare disaggregation algorithms on many public datasets. We use in our system two disaggregation algorithms Combinatorial Optimization and Factorial Hidden Markov Model algorithms. The results show that is possible to collect and perform energy disaggregation through our embedded system

Development of Electrostatic and Piezoelectric Sensor Arrays for Determining the Velocity and Concentration Profiles and Size Distribution of Pneumatically Conveyed Bulk Solids

One way countries around the world are increasing the proportion of renewable fuels for electricity generation is to convert coal fired power stations to co-fired (biomass/coal fired) or converting coal fired power stations to burn only biomass fuels. This however has led to measurement challenges monitoring the complex multi-phase flow of the pulverised fuels entering the furnace due to the complex shape of biomass particles. To meet these measurement challenges a novel electrostatic sensor array and piezoelectric sensor array have been developed. The electrostatic sensor array consists of an array of electrostatic electrode pairs that span the diameter of the pipe. Consequently the electrostatic sensor array is capable of determining the particle velocity and concentration profiles as well as detecting specific flow regimes such as roping. The piezoelectric impact sensor array consists of an array of piezoelectric individual impact sensors that span the diameter of the pipe. The piezoelectric sensor array is capable of determining the particle concentration and size distribution profiles. Experimentation has been carried out on laboratory scale pneumatic conveying systems using a variety of materials such as coal, biomass, coal/biomass blends and plastic shot. Experiments using the electrostatic sensor array have shown that it is indeed capable of determining the particle velocity and concentration profiles in both dilute developed and undeveloped flows. Analysis of the standard deviation of the velocity profiles as well as the correlation coefficient profiles have indicated that parts of the pipe cross section have a more stable flow compared to others. Data obtained through on-line and off-line experimentation using the piezoelectric sensor array has shown that through selective frequency filtering of the impact signal particle size can be determined assuming the particle velocity and the mechanical properties of the conveyed pulverised materials are known. By using a threshold voltage to determine when an impact has occurred on each element of the piezoelectric sensor array the particle concentration profile has been determined. The concentration profiles measured by the piezoelectric sensor array were verified using the electrostatic sensor array