Routing Protocols for Wireless Sensor Networks (WSNs)

Wireless sensor networks (WSNs) are achieving importance with the passage of time. Out of massive usage of wireless sensor networks, few applications demand quick data transfer including minimum possible interruption. Several applications give importance to throughput and they have not much to do with delay. It all rest on the applications desires that which parameter is more favourite. The knowledge of network structure and routing protocol is very important and it should be appropriate for the requirement of the usage. In the end a performance analysis of different routing protocols is made using a WLAN and a ZigBee based Wireless Sensor Network

Case study of non-linear PV inverter devices attached to the LV distribution network

Every year, more and more solar power plants are connected to the grid, producing electricity in an environmentally sustainable manner. The increasing number of photovoltaic (PV) installations and their integration into the low voltage (LV) distribution network (DN) is having an impact in terms of power quality (PQ). For example, the voltage in the DN can sustain high distortion values. The impact of a PV installation on the LV network is analysed in this research. The field measurements were carried out over a 3-week period at a solar power plant with a total output power of 160 kW in an Estonian rural municipality. The measurement results provide the opportunity to look more closely at the effect of the solar power plant on the supply voltage of the LV DN. Parameters such as voltage variation within a one-minute period, the asymmetry of the voltages and the total harmonic distortion of the voltages are discussed here

An overview of measurement standards for power quality

Received: December 7th, 2020 ; Accepted: April 7th, 2021 ; Published: May 13th, 2021 ; Correspondence: [email protected] Quality (PQ) is a vital aspect of electrical power systems, which cannot be neglected anymore, as an ample PQ guarantees the essential compatibility between consumer equipment and the electricity network. The analysis of electrical parameters related to distributing electricity is recognized as a complex engineering problem. It remains a critical task to maintain and improve PQ in modern evolving networks as the overall system performance highly depends on it. Future smart grids will also require a further increase in PQ levels in terms of observability, affordability, data exchange, flexibility, and net metering, thus making the network much more complex as it will be featuring a large amount of variable renewable-based distributed generation. This will further require the need for the introduction of novel, efficient and intelligent monitoring, control, and communication systems with various demand manageable resources. In this paper, a review and comparisons have been made for different IEEE and IEC measurement standards that are used for PQ with a specific focus on harmonic distortion as it is one of the most important parameters in PQ and some guidelines have been suggested for future electricity networks

Iatrogenic trauma following percutaneous and minimally invasive surgical interventions

Technological progress has changed the landscape of surgical practice. Minimally invasive surgery (MIS) and percutaneous interventions (PC) are constantly replacing open procedures. This reduces hospital stay and allows quicker recovery. The application of MIS should follow the good medical practice dictum by Hippocrates i.e. First do no harm . To remain abreast with new procedures, the medical personnel are required to update and enhance their knowledge and skill. To ensure safety, the innovations are rigorously tested and tried. The learning curve of MIS is shortened by simulator training and proctorship. Credentialing processes are in place to enhance safe delivery of care. Despite of all these measures MIS and PCI are associated with adverse effects. The purpose of this article is to overview the iatrogenic trauma associated with MIS and PCI in major surgical subspecialties

A Cost-Effective Electric Vehicle Intelligent Charge Scheduling Method for Commercial Smart Parking Lots Using a Simplified Convex Relaxation Technique

Deployment of efficient and cost-effective parking lots is a known bottleneck for the electric vehicles (EVs) sector. A comprehensive solution incorporating the requirements of all key stakeholders is required. Taking up the challenge, we propose a real-time EV smart parking lot model to attain the following objectives: (a) maximize the smart parking lot revenue by accommodating maximum number of EVs and (b) minimize the cost of power consumption by participating in a demand response (DR) program offered by the utility since it is a tool to answer and handle the electric power usage requirements for charging the EV in the smart parking lot. With a view to achieving these objectives, a linear programming-based binary/cyclic (0/1) optimization technique is developed for the EV charge scheduling process. It is difficult to solve the problems of binary optimization in real-time given that the complexity of the problem increases with the increase in number of EV. We deploy a simplified convex relaxation technique integrated with the linear programming solution to overcome this problem. The algorithm achieves: minimum power consumption cost of the EV smart parking lot; efficient utilization of available power; maximization of the number of the EV to be charged; and minimum impact on the EV battery lifecycle. DR participation provide benefits by offering time-based and incentive-based hourly intelligent charging schedules for the EV. A thorough comparison is drawn with existing variable charging rate-based techniques in order to demonstrate the comparative validity of our proposed technique. The simulation results show that even under no DR event, the proposed scheme results in 2.9% decrease in overall power consumption cost for a 500 EV scenario when compared to variable charging rate method. Moreover, in similar conditions, such as no DR event and for 500 EV arrived per day, there is a 2.8% increase in number of EV charged per day, 3.2% improvement in the average state-of-charge (SoC) of the EV, 12.47% reduction in the average time intervals required to achieve final SoC

Radio Resource Management in WiMAX

Today, different types of cellular networks are actively working on the radio links. For instance, the Global System for Mobile Communication (GSM) is being used in nearly two hundred countries and currently it has around two and half billion users all over the world. Universal Mobile Telecommunication System (UMTS) is currently deployed in many countries and it is providing increased data rates, coverage and mobility as compared to GSM. Wireless Local Area Networks (WLAN) are very famous when we have a small area and none real time services. Worldwide Interoperability for Microwave Access (WiMAX) is a new technology and it is in deployment phase. In all these cellular technologies, we have very limited recourses and we have to make best use of them by proper management. Radio Resource Management (RRM) is a control mechanism for the overall system which is being used to manage radio resources in the air interface inside a cellular network. The main objective is to utilize the available spectral resources as efficiently as possible. Our aim is to use them in the best possible way to maximize the performance and spectral efficiency in such a way that we have maximum number of users in our network and Quality of Service (QoS) is up to the mark. In a cellular communication system, a service area or a geographical region is divided into a number of cells and each cell is served by an infrastructure element called the base station which works through a radio interface. The frequency license fees, real estate, distribution network and maintenance are the issues which dominates the cost for deploying a cellular network. Management of radio related resources is a critical design component in cellular communications. In RRM, we control parameters like Radio Frequency (RF) planning, link budgeting, modulation schemes, channel access schemes etc. RF planning includes cell planning, coverage of the network and capacity of the network. Our main focus in this thesis will be on cell planning and link budgeting and we will discuss them in context of a WiMAX network

Forecasting of Energy Consumption and Production Using Recurrent Neural Networks

Energy forecasting for both consumption and production is a challenging task as it involves many variable factors. It is necessary to calculate the actual production of energy and its consumption as it is very beneficial in maintaining demand and supply. The reliability and smooth functioning of any electrical system are dependent on this management. In this article, the Recurrent Neural Network (RNN) based algorithm is used for energy forecasting. The algorithm is used for making three days ahead prediction of energy for both generation and consumption in Estonia. A comparison is also made between our proposed algorithm and the forecasting algorithm used by Estonian energy regulatory authority. The results of both algorithms indicate that our proposed algorithm has lower Root Mean Square Error (RMSE) and is giving better forecasting

Fetch Effect on Flux-Variance Estimations of Sensible and Latent Heat Fluxes of Camellia Sinensis

Precise estimation of surface-atmosphere exchange is a major challenge in micrometeorology. Previous literature presented the eddy covariance (EC) as the most reliable method for the measurements of such fluxes. Nevertheless, the EC technique is quite expensive and complex, hence other simpler methods are sought. One of these methods is Flux-Variance (FV). The FV method estimates sensible heat flux (H) using high frequency (~10Hz) air temperature measurements by a fine wire thermocouple. Additional measurements of net radiation (Rn) and soil heat flux (G) allow the derivation of latent heat flux (LE) as the residual of the energy balance equation. In this study, the Flux Variance method was investigated, and the results were compared against eddy covariance measurements. The specific goal of the present study was to assess the performance of the FV method for the estimation of surface fluxes along a variable fetch. Experiment was carried out in a tea garden; an EC system measured latent and sensible heat fluxes and five fine-wire thermocouples were installed towards the wind dominant direction at different distances (fetch) of TC1 = 170 m, TC2 = 165 m, TC3 = 160 m, TC4 = 155 m and TC5 = 150 m from the field edge. Footprint analysis was employed to examine the effect of temperature measurement position on the ratio between 90% footprint and measurement height. Results showed a good agreement between FV and EC measurements of sensible heat flux, with all regression coefficients (R2) larger than 0.6; the sensor at 170 m (TC1), nearest to the EC system, had highest R2 = 0.86 and lowest root mean square error (RMSE = 25 Wm−2). The estimation of LE at TC1 was also in best agreement with eddy covariance, with the highest R2 = 0.90. The FV similarity constant varied along the fetch within the range 2.2–2.4