The seamless coexistence of distributed photovoltaics (PV) with the utility network may be maintained by focusing on higher energy autonomy of micro-grids.
This may be approached by seeking any ...opportunities to increase local energy consumption, especially when legal regulations are cutting-down the benefits for energy overproduction.
The microgrids combining PV with electric storage and heat pumps largely fail at satisfying local energy needs autonomously in winter periods and create excessive load of power network. Although the all-electric microgrid is a long term target, any improvements to the existing residential infrastructure with mixed-supply sources are worth revisiting as low-cost steps towards more conscious energy utilization.
The concept of using Domestic Hot Water (DHW) heating to dump locally the excess of PV-energy is affordable method to improve energy autonomy of residential microgrids with minimal interference to their existing configuration and the advantage of no additional energy demand.
The use of PV for DHW heating was studied in various configurations, but in contrast to former works, this paper presents the parametric analysis focusing on increasing the local consumption (goal A), minimizing the interference with utility grid (goal B) and optimal adjustment to net-metering accounting rules (goal C).
The case study is the residential-type micro-grid in climate of Central Europe. The study uses both simulated (energy consumption profiles) and recorded (solar irradiance) data. The simulation is based on microgrid proportions and provides the results beyond reach of single experiments and conclusions applicable to similar cases, regardless the absolute size.
•Parametric analysis of household microgrids with PV and DHW addressing energy autonomy.•Estimation of potential to increase the local utilization of PV-energy with DHWPV.•Guidelines to maximal PV-size assuring unidirectional energy transfer.•Guidelines to optimal over-sizing the PV-system with view of net-metering rules.
The article presents simple modeling and experimental verification of the power required for thermal comfort in electrically heated clothing. The clothing consists of a jumpsuit with embedded heating ...insets, controlled by a dedicated microprocessor system. The user is able to set heating power using a smartphone app. The experiments, conducted in a mobile freezing chamber, aimed at verification of the model of theoretical power (according to ISO 11079) required to maintain thermal comfort in ambient temperatures below 0 °C. Three participants were asked to adjust heating power to reach thermal comfort. The experiment revealed the required power to be only 40–60% of the theoretical one, meaning that the design of the electrically heating clothing relying solely on the theoretical models and standards would lead to oversizing of the heating system power. Further study indicated that the mean skin temperature by itself is not sufficient as an input to the algorithm for automatic maintaining of thermal comfort, even in stationary conditions.
Despite its recent growth in popularity, actively heated clothing still lacks the ability to cope with demanding user scenarios. As many of these deficiencies stem from an absence of automatic ...control, the authors propose a novel approach using a set of sensors embedded in the clothing to provide data about thermal comfort. Available sensors suffer from a lack of accuracy, as for practical reasons, they cannot be attached to the skin, whose temperature is usually used as a comfort indicator. To determine the magnitude of the problem, the authors conducted experiments, and a thermal model was proposed based on experimental findings; the output from the model was compared with the experimental reference data for three different upper body undergarments. The overall accuracy was found to be good: in most cases, the difference between the computed and reference skin temperatures did not exceed 0.5 °C. Furthermore, the model does not rely on unrealistic assumptions regarding the availability of parameters or measurement data. Our findings demonstrate that it is possible to create a thermal model that, when used for input data processing, allows undergarment temperature to be converted to skin temperature, allowing for automatic control of heating insets.
Vestibular impairments affect patients' movements and can result in difficulties with daily life activities. The main aim of this study is to answer the question whether a simple and short test such ...as rotation about a vertical axis can be an objective method of assessing balance dysfunction in patients with unilateral vestibular impairments. A 360˚ rotation test was performed using six MediPost devices. The analysis was performed in three ways: (1) the analytical approach based only on data from one sensor; (2) the analytical approach based on data from six sensors; (3) the artificial neural network (ANN) approach based on data from six sensors. For approaches 1 and 2 best results were obtained using maximum angular velocities (MAV) of rotation and rotation duration (RD), while approach 3 used 11 different features. The following sensitivities and specificities were achieved: for approach 1: MAV-80% and 60%, RD-69% and 74%; for approach 2: 61% and 85% and RD-74% and 56%; for approach 3: 88% and 84%. The ANN-based six-sensor approach revealed the best sensitivity and specificity among parameters studied, however one-sensor approach might be a simple screening test used e.g. for rehabilitation purposes.
This paper presents a fall risk assessment approach based on a fast mobility test, automatically evaluated using a low-cost, scalable system for the recording and analysis of body movement. This ...mobility test has never before been investigated as a sole source of data for fall risk assessment. It can be performed in a very limited space and needs only minimal additional equipment, yet provides large amounts of information, as the presented system can obtain much more data than traditional observation by capturing minute details regarding body movement. The readings are provided wirelessly by one to seven low-cost micro-electro-mechanical inertial measurement units attached to the subject's body segments. Combined with a body model, these allow segment rotations and translations to be computed and for body movements to be recreated in software. The subject can then be automatically classified by an artificial neural network based on selected values in the test, and those with an elevated risk of falls can be identified. Results obtained from a group of 40 subjects of various ages, both healthy volunteers and patients with vestibular system impairment, are presented to demonstrate the combined capabilities of the test and system. Labelling of subjects as fallers and non-fallers was performed using an objective and precise sensory organization test; it is an important novelty as this approach to subject labelling has never before been used in the design and evaluation of fall risk assessment systems. The findings show a true-positive ratio of 85% and true-negative ratio of 63% for classifying subjects as fallers or non-fallers using the introduced fast mobility test, which are noticeably better than those obtained for the long-established Timed Up and Go test.
The article presents the concept of detecting subjects with balance disorders by the use of machine learning techniques. The proposed solution has been developed and tested based on a group of 40 ...subjects, the group included both patients with uncompensated dysfunction in the vestibular system and healthy volunteers. Presence of dysfunction was verified prior to the study by detailed clinical examination. The data for the study were collected with the use of miniature micromachine sensors, mounted on the body at selected locations. The task performed by the subjects consisted of free gait over a distance of three meters; the task was selected to make it easy to perform in any surroundings and not requiring additional equipment. The collected data was used as an input to an artificial neural network based on a one-dimensional convolution kernel. The proposed solution allows to classify subjects into healthy and non-healthy with an accuracy of 87.5%.
Abstract This paper presents a decision support system that aims to estimate a patient׳s general condition and detect situations which pose an immediate danger to the patient׳s health or life. The ...use of this system might be especially important in places such as accident and emergency departments or admission wards, where a small medical team has to take care of many patients in various general conditions. Particular stress is laid on cardiovascular and pulmonary conditions, including those leading to sudden cardiac arrest. The proposed system is a stand-alone microprocessor-based device that works in conjunction with a standard vital signs monitor, which provides input signals such as temperature, blood pressure, pulseoxymetry, ECG, and ICG. The signals are preprocessed and analysed by a set of artificial intelligence algorithms, the core of which is based on Bayesian networks. The paper focuses on the construction and evaluation of the Bayesian network, both its structure and numerical specification.
This paper contains a discussion of striking similarities between influential philosophical concepts of the past and the approaches currently employed in selected areas of computer science. In ...particular, works of the Pythagoreans, Plato, Abelard, Ash’arites, Malebranche and Berkeley are presented and contrasted with such computer science ideas as digital computers, object-oriented programming, the modelling of an object’s actions and causality in virtual environments, and 3D graphics rendering. The intention of this paper is to provoke the computer science community to go off the beaten path in order to find inspiration for the development of new approaches in software engineering.
This paper presents a fully automatic leak detection system for slow oscillation high-pressure fluid-filled (HPFF) circuits. It also presents the concept of detecting leaks in such circuits, ...utilizing only a limited number of sensors. It will describe algorithms built upon this concept, including two different approaches to the construction of the decision module, crucial for detection capabilities. The proposed solution utilizes adaptive digital filters for modeling the circuit behavior and a Bayesian network coupled with a software leak simulator in the decision stage. These tests were performed using data obtained from a real-life circuit, including real-leak data. This paper may enable practical application of high-precision low-cost leak detection solutions for a wide range of HPFF circuits.
This paper presents a fully automatic system intended to detect leaks of dielectric fluid in underground high-pressure, fluid-filled (HPFF) cables. The system combines a number of artificial ...intelligence (AI) and data processing techniques to achieve high detection capabilities for various rates of leaks, including leaks as small as 15 l per hour. The system achieves this level of precision mainly thanks to a novel auto-tuning procedure, enabling learning of the Bayesian network – the decision-making component of the system – using simulated leaks of various rates. Significant new developments extending the capabilities of the original leak detection system described in
1 and
2 form the basis of this paper. Tests conducted on the real-life HPFF cable system in New York City are also discussed.
PDF
