Modeling smart grid of prosumers with photovoltaic systems

Запропоновано модель вузла смарт-мережі для споживача-просьюмера в межах котеджного селища. Модель включає в себе типові добові графіки навантаження будинку та генерації дахової фотоелектричної системи, модель акумуляторної системи зберігання енергії та контролера вузла смарт-мережі. Розроблено алгоритми керування роботою вузла смарт-мережі, який передбачає різні режими роботи для літа та зими. В залежності від години доби, стану заряду акумулятора, генерації фотоелектричної системи та навантаження будинку контролер керує балансуючим споживанням або віддачою енергії до мережі, заряджанням або розряджанням акумулятора, купівлею або продажом енергії просьюмером до енергосистеми. Метою керування влітку є повне використання енергії, виробленої власною фотоелектричною системою, для власного споживання та продажу надлишків в енергосистему в години пікового навантаження. Метою керування взимку є зниження витрат споживача за рахунок перенесення навантаження на нічні години та збільшення доходів від перепродажу накопиченої енергії до енергосистеми в пікові години. За результатами моделювання на прикладі котеджного селища в харківській області визначено мінімальну ємність акумуляторної системи, якої достатньо для забезпечення автономності споживача-просьюмера влітку та отримання доходу від перепродажу енергії взимку. Показано, що запропоновані алгоритми керування роботою вузла смарт-мережі дозволяють споживачу-просьюмеру ефективно використовувати власну фотоелектричну систему та надавати системні послуги об’єднаній енергосистемі.The smart-grid node model for prosumer within a cottage community has been proposed. The model includes a typical cottage load daily profiles and a roof photovoltaic system generation daily profiles, an energy storage system model and a smart grid node controller. The control algorithms for the smart grid node operation, providing different operation modes for summer and winter are developed. Depending on the time of day, the battery state of charge, the photovoltaic system generation and the cottage load, the controller controls the balancing power consumption or output to the grid, the battery charge or discharge, the energy buy or sale by prosumer. The control goal in summer is to fully use the energy produced by own photovoltaic system for own needs and to sale of surplus energy to the grid during peak hours. The control goal in winter is to reduce consumer costs by shifting the load overnight and increasing revenues from the resale of stored energy to the grid during peak hours. The minimum battery capacity of the energy storage system, sufficient to ensure the consumer autonomy in the summer and generate income from the energy resale in the winter, was estimated based on the simulation results for the case of a cottage community in the Kharkiv region. It is shown that the proposed algorithms for control of a smart grid node allow the prosumer to effectively use their own photovoltaic system and provide system services to the energy system

Are Formal Contracts a useful Digital Twin of Software Systems?

Digital Twins are a trend topic in the industry today to either manage runtime information or forecast properties of devices and products. The techniques for Digitial Twins are already employed in several disciplines of formal methods, in particular, formal verification, runtime verification and specification inference. In this paper, we connect the Digital Twin concept and existing research areas in the field of formal methods. We sketch how digital twins for software-centric systems can be forged from existing formal methods

Applications of ontology in the Internet of Things: a systematic analysis

Ontology has been increasingly implemented to facilitate the Internet of Things (IoT) activities, such as tracking and information discovery, storage, information exchange, and object addressing. However, a complete understanding of using ontology in the IoT mechanism remains lacking. The main goal of this research is to recognize the use of ontology in the IoT process and investigate the services of ontology in IoT activities. A systematic literature review (SLR) is conducted using predefined protocols to analyze the literature about the usage of ontologies in IoT. The following conclusions are obtained from the SLR. (1) Primary studies (i.e., selected 115 articles) have addressed the need to use ontologies in IoT for industries and the academe, especially to minimize interoperability and integration of IoT devices. (2) About 31.30% of extant literature discussed ontology development concerning the IoT interoperability issue, while IoT privacy and integration issues are partially discussed in the literature. (3) IoT styles of modeling ontologies are diverse, whereas 35.65% of total studies adopted the OWL style. (4) The 32 articles (i.e., 27.83% of the total studies) reused IoT ontologies to handle diverse IoT methodologies. (5) A total of 45 IoT ontologies are well acknowledged, but the IoT community has widely utilized none. An in-depth analysis of different IoT ontologies suggests that the existing ontologies are beneficial in designing new IoT ontology or achieving three main requirements of the IoT field: interoperability, integration, and privacy. This SLR is finalized by identifying numerous validity threats and future directions

An adaptive neuro-fuzzy propagation model for LoRaWAN

This article proposes an adaptive-network-based fuzzy inference system (ANFIS) model for accurate estimation of signal propagation using LoRaWAN. By using ANFIS, the basic knowledge of propagation is embedded into the proposed model. This reduces the training complexity of artificial neural network (ANN)-based models. Therefore, the size of the training dataset is reduced by 70% compared to an ANN model. The proposed model consists of an efficient clustering method to identify the optimum number of the fuzzy nodes to avoid overfitting, and a hybrid training algorithm to train and optimize the ANFIS parameters. Finally, the proposed model is benchmarked with extensive practical data, where superior accuracy is achieved compared to deterministic models, and better generalization is attained compared to ANN models. The proposed model outperforms the nondeterministic models in terms of accuracy, has the flexibility to account for new modeling parameters, is easier to use as it does not require a model for propagation environment, is resistant to data collection inaccuracies and uncertain environmental information, has excellent generalization capability, and features a knowledge-based implementation that alleviates the training process. This work will facilitate network planning and propagation prediction in complex scenarios

A neural network propagation model for LoRaWAN and critical analysis with real-world measurements

Among the many technologies competing for the Internet of Things (IoT), one of the most promising and fast-growing technologies in this landscape is the Low-Power Wide-Area Network (LPWAN). Coverage of LoRa, one of the main IoT LPWAN technologies, has previously been studied for outdoor environments. However, this article focuses on end-to-end propagation in an outdoor–indoor scenario. This article will investigate how the reported and documented outdoor metrics are interpreted for an indoor environment. Furthermore, to facilitate network planning and coverage prediction, a novel hybrid propagation estimation method has been developed and examined. This hybrid model is comprised of an artificial neural network (ANN) and an optimized Multi-Wall Model (MWM). Subsequently, real-world measurements were collected and compared against different propagation models. For benchmarking, log-distance and COST231 models were used due to their simplicity. It was observed and concluded that: (a) the propagation of the LoRa Wide-Area Network (LoRaWAN) is limited to a much shorter range in this investigated environment compared with outdoor reports; (b) log-distance and COST231 models do not yield an accurate estimate of propagation characteristics for outdoor–indoor scenarios; (c) this lack of accuracy can be addressed by adjusting the COST231 model, to account for the outdoor propagation; (d) a feedforward neural network combined with a COST231 model improves the accuracy of the predictions. This work demonstrates practical results and provides an insight into the LoRaWAN’s propagation in similar scenarios. This could facilitate network planning for outdoor–indoor environments

New Perspectives in Manufacturing: An Assessment for an Advanced Reconfigurable Machining System

Traditionally manufacturing cycle involves several production processes that are carried out according to the required technologies tacking into account the constraint due to the production capacity provided by machine tools and the customers' orders time schedule In this paper, a new modular, reconfigurable and scalable machining centre is presented. The resulting system is characterized by the possibility of modifying the machining capacity as well as exchanging the role between workpieces and machining/operating resources. This augmented flexibility creates new opportunities for efficient manufacturing; however, the increased system complexity demands a new approach for the jobs scheduling and machining control. An architecture based on agents modelling is proposed and discussed

A Strategic Roadmap for the Manufacturing Industry to Implement Industry 4.0

Industry 4.0 (also referred to as digitization of manufacturing) is characterized by cyber physical systems, automation, and data exchange. It is no longer a future trend and is being employed worldwide by manufacturing organizations, to gain benefits of improved performance, reduced inefficiencies, and lower costs, while improving flexibility. However, the implementation of Industry 4.0 enabling technologies is a difficult task and becomes even more challenging without any standardized approach. The barriers include, but are not limited to, lack of knowledge, inability to realistically quantify the return on investment, and lack of a skilled workforce. This study presents a systematic and content-centric literature review of Industry 4.0 enabling technologies, to highlight their impact on the manufacturing industry. It also provides a strategic roadmap for the implementation of Industry 4.0, based on lean six sigma approaches. The basis of the roadmap is the design for six sigma approach for the development of a new process chain, followed by a continuous improvement plan. The reason for choosing lean six sigma is to provide manufacturers with a sense of familiarity, as they have been employing these principles for removing waste and reducing variability. Major reasons for the rejection of Industry 4.0 implementation methodologies by manufactures are fear of the unknown and resistance to change, whereas the use of lean six sigma can mitigate them. The strategic roadmap presented in this paper can offer a holistic view of phases that manufacturers should undertake and the challenges they might face in their journey toward Industry 4.0 transition

Prosumer communities and relationships in smart grids: A literature review, evolution and future directions

Smart grids are robust, self-healing networks that allow bidirectional propagation of energy and information within the utility grid. This introduces a new type of energy user who consumes, produces, stores and shares energy with other grid users. Such a user is called a "prosumer." Prosumers' participation in the smart grid is critical for the sustainability and long-term efficiency of the energy sharing process. Thus, prosumer management has attracted increasing attention among researchers in recent years. This paper systematically examines the literature on prosumer community based smart grid by reviewing relevant literature published from 2009 to 2018 in reputed energy and technology journals. We specifically focus on two dimensions namely prosumer community groups and prosumer relationships. Based on the evaluated literature, we present eight propositions and thoroughly describe several future research directions

Islanding of distribution networks : challenges and potential solutions

The concept of generating electricity from renewable sources has been developed to solve the problems raised by environmental pollution and diminishing fossil fuel resources. Integration of clean renewable generation into existing electrical systems has been proven to benefit both power system operators and customers. However, a number of technical and economic challenges still exist with regards to effective integration and optimal utilization of such sources. One of the issues much debated recently is the provision for islanded operation in distribution networks utilizing the locally available generation. There are many obstacles and challenges concerning technical, economic and regulatory aspects of islanded operation which attract a significant amount of research worldwide. This review paper covers the state-of-the-art in research on islanded systems, specifically concerning: generation control, islanding detection, protection, and other functions such as power-sharing and black start capability

Wearable Bluetooth Triage Healthcare Monitoring System.

Triage is the first interaction between a patient and a nurse/paramedic. This assessment, usually performed at Emergency departments, is a highly dynamic process and there are international grading systems that according to the patient condition initiate the patient journey. Triage requires an initial rapid assessment followed by routine checks of the patients' vitals, including respiratory rate, temperature, and pulse rate. Ideally, these checks should be performed continuously and remotely to reduce the workload on triage nurses; optimizing tools and monitoring systems can be introduced and include a wearable patient monitoring system that is not at the expense of the patient's comfort and can be remotely monitored through wireless connectivity. In this study, we assessed the suitability of a small ceramic piezoelectric disk submerged in a skin-safe silicone dome that enhances contact with skin, to detect wirelessly both respiration and cardiac events at several positions on the human body. For the purposes of this evaluation, we fitted the sensor with a respiratory belt as well as a single lead ECG, all acquired simultaneously. To complete Triage parameter collection, we also included a medical-grade contact thermometer. Performances of cardiac and respiratory events detection were assessed. The instantaneous heart and respiratory rates provided by the proposed sensor, the ECG and the respiratory belt were compared via statistical analyses. In all considered sensor positions, very high performances were achieved for the detection of both cardiac and respiratory events, except for the wrist, which provided lower performances for respiratory rates. These promising yet preliminary results suggest the proposed wireless sensor could be used as a wearable, hands-free monitoring device for triage assessment within emergency departments. Further tests are foreseen to assess sensor performances in real operating environments