Komponentenbasierte dynamische Modellierung von Energiesystemen und Energiemanagement-Strategien für ein intelligentes Stromnetz im Heimbereich

The motivation of this work is to present an energy cost reduction concept in a home area power network (HAPN) with intelligent generation and flexible load demands. This study endeavors to address the energy management system (EMS) and layout-design challenges faced by HAPN through a systematic design approach. The growing demand for electricity has become a significant burden on traditional power networks, prompting power engineers to seek ways to improve their efficiency. One such solution is to integrate dispersed generation sources, such as photovoltaic (PV) and storage systems, with an appropriate control mechanism at the distribution level. In recent years, there has been a significant increase in interest in the installation of PV-Battery systems, due to their potential to reduce carbon emissions and lower energy costs. This research proposes an optimal economic power dispatch strategy using Model Predictive Control (MPC) to enhance the overall performance of HAPN. A hybrid AC/DC microgrid concept is proposed to address the control choices made by the appliance scheduling and hybrid switching approaches based on a linear programming optimization framework. The suggested optimization criteria improve consumer satisfaction, minimize grid disconnections, and lower overall energy costs by deploying inexpensive clean energy generation and control. Various examples from actual case study demonstrate the use of the established EMS and design methodology.Die Motivation dieser Arbeit besteht darin, ein Konzept zur Senkung der Energiekosten in einem Heimnetzwerk (HAPN) mit intelligenter Erzeugung und exiblen Lastanforderungen vorzustellen. Im Rahmen dieser Forschungsarbeit wird ein Entwurf für ein HAPN entwickelt, indem das Energiemanagementsystem (EMS) und der Entwurf des Layouts auf der Grundlage des Systemmodells und der betrieblichen Anforderungen gelöst werden. Die steigende Nachfrage nach Elektrizität ist für traditionelle Stromnetze kostspielig und infrastrukturintensiv. Daher konzentrieren sich Energietechniker darauf, die Effizienz der derzeitigen Netze zu erhöhen. Dies kann durch die Integration verteilter Erzeugungsanlagen (z. B. Photovoltaik (PV), Speicher) mit einem geeigneten Kontrollmechanismus für das Energiemanagement auf der Verteilungsseite erreicht werden. Darüber hinaus hat das Interesse an der Installation von PV-Batterie-basierten Systemen aufgrund der Reduzierung der CO2-Emissionen und der Senkung der Energiekosten erheblich zugenommen. Es wird eine optimale wirtschaftliche Strategie für den Energieeinsatz unter Verwendung einer modellprädiktiven Steuerung (MPC) entwickelt. Es wird zudem ein hybrides AC/DC-Microgrid-Konzept vorgeschlagen, um die Steuerungsentscheidungen, die von den Ansätzen der Geräteplanung und der hybriden Umschaltung getroffen werden, auf der Grundlage eines linearen Programmierungsoptimierungsrahmens zu berücksichtigen. Die vorgeschlagenen Optimierungskriterien verbessern die Zufriedenheit der Verbraucher, minimieren Netzabschaltungen und senken die Gesamtenergiekosten durch den Einsatz von kostengünstiger und sauberer Energieerzeugung. Verschiedene Beispiele aus einer Fallstudie demonstrieren den Einsatz des entwickelten EMS und der Entwurfsmethodik

Modeling and Optimizing Energy Supply and Demand in Home Area Power Network (HAPN)

Internet of energy based smart power grids demonstrate high in-feed from renewable energy resources (RESs) and lofty out-feed to energy consumers. Uncertainties evolved by incorporating RESs and time-varying energy consumption present immense challenges to the optimal control of smart power networks. To deal with these challenges, it is important to make the system deterministic by making time-ahead prediction and scheduling of power supply and demand. The present work confers a model of a co-scheduling framework, organizing cost-efficient activation of energy supply entities (ESEs) and load demands in a home area power network (HAPN). It integrates roof-top photovoltaic (PV) panels, diesel energy generator (DE), energy storage devices (ESDs), and smart load demands (SLDs) along with grid-supplied power. The scheduling model is based on mixed-integer linear programming (MILP) framework, incorporates a “min-max” optimization algorithm that reduces the daily energy bills, maintains high comfort level for the energy consumers, and increases the self-sufficiency of the home. The proposed strategy exploits the flexibility in dynamic energy price signals and SLDs of various classes, providing day-ahead cost-optimal scheduling decisions for incorporated energy entities. A linearized component-based model is developed, considering inefficiencies, taking various power phase modes of the SLDs along with the cost of operation, maintenance, and degradation of the equipment. A case study based on numerical analysis determines the particular features of the proposed HAPN model. Simulation results demonstrate the real prospect of our implemented strategy, utilizing a cost-effective optimal blend of distinct energy entities in a smart home

On the design of a cost-efficient resource management framework for low latency applications

The ability to offer low latency communications is one of the critical design requirements for the upcoming 5G era. The current practice for achieving low latency is to overprovision network resources (e.g., bandwidth and computing resources). However, this approach is not cost-efficient, and cannot be applied in large-scale. To solve this, more cost-efficient resource management is required to dynamically and efficiently exploit network resources to guarantee low latencies. The advent of network virtualization provides novel opportunities in achieving cost-efficient low latency communications. It decouples network resources from physical machines through virtualization, and groups resources in the form of virtual machines (VMs). By doing so, network resources can be flexibly increased at any network locations through VM auto-scaling to alleviate network delays due to lack of resources. At the same time, the operational cost can be largely reduced by shutting down low-utilized VMs (e.g., energy saving). Also, network virtualization enables the emerging concept of mobile edge-computing, whereby VMs can be utilized to host low latency applications at the network edge to shorten communication latency. Despite these advantages provided by virtualization, a key challenge is the optimal resource management of different physical and virtual resources for low latency communications. This thesis addresses the challenge by deploying a novel cost-efficient resource management framework that aims to solve the cost-efficient design of 1) low latency communication infrastructures; 2) dynamic resource management for low latency applications; and 3) fault-tolerant resource management. Compared to the current practices, the proposed framework achieves 80% of deployment cost reduction for the design of low latency communication infrastructures; continuously saves up to 33% of operational cost through dynamic resource management while always achieving low latencies; and succeeds in providing fault tolerance to low latency communications with a guaranteed operational cost

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

The Four-C Framework for High Capacity Ultra-Low Latency in 5G Networks: A Review

Network latency will be a critical performance metric for the Fifth Generation (5G) networks expected to be fully rolled out in 2020 through the IMT-2020 project. The multi-user multiple-input multiple-output (MU-MIMO) technology is a key enabler for the 5G massive connectivity criterion, especially from the massive densification perspective. Naturally, it appears that 5G MU-MIMO will face a daunting task to achieve an end-to-end 1 ms ultra-low latency budget if traditional network set-ups criteria are strictly adhered to. Moreover, 5G latency will have added dimensions of scalability and flexibility compared to prior existing deployed technologies. The scalability dimension caters for meeting rapid demand as new applications evolve. While flexibility complements the scalability dimension by investigating novel non-stacked protocol architecture. The goal of this review paper is to deploy ultra-low latency reduction framework for 5G communications considering flexibility and scalability. The Four (4) C framework consisting of cost, complexity, cross-layer and computing is hereby analyzed and discussed. The Four (4) C framework discusses several emerging new technologies of software defined network (SDN), network function virtualization (NFV) and fog networking. This review paper will contribute significantly towards the future implementation of flexible and high capacity ultra-low latency 5G communications

Internet Predictions

More than a dozen leading experts give their opinions on where the Internet is headed and where it will be in the next decade in terms of technology, policy, and applications. They cover topics ranging from the Internet of Things to climate change to the digital storage of the future. A summary of the articles is available in the Web extras section