Video streaming with quality adaption using collaborative active grid networks

Due to the services and demands of the end users, Distributed Computing (Grid Technology, Web Services, and Peer-to-Peer) has been developedrapidJy in thelastyears. Theconvergence of these architectures has been possible using mechanisms such as Collaborative work and Resources Sharing. Grid computing is a platform to enable flexible, secure, controlled, scalable, ubiquitous and heterogeneous services. On the other hand, Video Streaming applications demand a greater deployment over connected Internet users. The present work uses the Acti ve Grid technology as a fundamental platform to give a solution of multimediacontentrecovery. This solution takes into account the following key concepts: collaborative work, multi-source recovery and adapti ve quality. A new archi tecture is designed to deliver video content over a Grid Network. The acti ve and passi ve roles of the nodes are important to guarantee a high quality and efficiency for the video streaming system. The acti ve sender nodes are the content suppliers, while the passive sender nodes wiU perform the backup functions, based on global resource control policies. The aim of the backup node is minirnize the time to restore the systemin caseoffailures. In this way, all participant peers work in a collaborati ve manner following a mul ti -source recovery scheme. Furthermore, Video La yered Encoding is used to manage the video data in a high scalable way, di viding the video in multiple layers. This video codification scheme enables thequality adaptation according to the availability of system resources. In addition, a buffer by sender peer and by layer is needed for an effecti ve control ofthe video retrieve. The QoS will fit considering the state of each buffer and the measurement tools provide by the Acti ve Grid on the network nodes. Ke ywords: Peer -to-Peer Grid Architecture, Services for Active Grids, Streaming Media, Layered Coding, Quality Adaptation, CoUaborative Work.Peer Reviewe

Video streaming with quality adaption using collaborative active grid networks

Due to the services and demands of the end users, Distributed Computing (Grid Technology, Web Services, and Peer-to-Peer) has been developedrapidJy in thelastyears. Theconvergence of these architectures has been possible using mechanisms such as Collaborative work and Resources Sharing. Grid computing is a platform to enable flexible, secure, controlled, scalable, ubiquitous and heterogeneous services. On the other hand, Video Streaming applications demand a greater deployment over connected Internet users. The present work uses the Acti ve Grid technology as a fundamental platform to give a solution of multimediacontentrecovery. This solution takes into account the following key concepts: collaborative work, multi-source recovery and adapti ve quality. A new archi tecture is designed to deliver video content over a Grid Network. The acti ve and passi ve roles of the nodes are important to guarantee a high quality and efficiency for the video streaming system. The acti ve sender nodes are the content suppliers, while the passive sender nodes wiU perform the backup functions, based on global resource control policies. The aim of the backup node is minirnize the time to restore the systemin caseoffailures. In this way, all participant peers work in a collaborati ve manner following a mul ti -source recovery scheme. Furthermore, Video La yered Encoding is used to manage the video data in a high scalable way, di viding the video in multiple layers. This video codification scheme enables thequality adaptation according to the availability of system resources. In addition, a buffer by sender peer and by layer is needed for an effecti ve control ofthe video retrieve. The QoS will fit considering the state of each buffer and the measurement tools provide by the Acti ve Grid on the network nodes. Ke ywords: Peer -to-Peer Grid Architecture, Services for Active Grids, Streaming Media, Layered Coding, Quality Adaptation, CoUaborative Work.Peer Reviewe

Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

Geobase Information System Impacts on Space Image Formats

As Geobase Information Systems increase in number, size and complexity, the format compatability of satellite remote sensing data becomes increasingly more important. Because of the vast and continually increasing quantity of data available from remote sensing systems the utility of these data is increasingly dependent on the degree to which their formats facilitate, or hinder, their incorporation into Geobase Information Systems. To merge satellite data into a geobase system requires that they both have a compatible geographic referencing system. Greater acceptance of satellite data by the user community will be facilitated if the data are in a form which most readily corresponds to existing geobase data structures. The conference addressed a number of specific topics and made recommendations

Enhancing the efficiency of electricity utilization through home energy management systems within the smart grid framework

The concept behind smart grids is the aggregation of “intelligence” into the grid, whether through communication systems technologies that allow broadcast/data reception in real-time, or through monitoring and systems control in an autonomous way. With respect to the technological advancements, in recent years there has been a significant increment in devices and new strategies for the implementation of smart buildings/homes, due to the growing awareness of society in relation to environmental concerns and higher energy costs, so that energy efficiency improvements can provide real gains within modern society. In this perspective, the end-users are seen as active players with the ability to manage their energy resources, for example, microproduction units, domestic loads, electric vehicles and their participation in demand response events. This thesis is focused on identifying application areas where such technologies could bring benefits for their applicability, such as the case of wireless networks, considering the positive and negative points of each protocol available in the market. Moreover, this thesis provides an evaluation of dynamic prices of electricity and peak power, using as an example a system with electric vehicles and energy storage, supported by mixed-integer linear programming, within residential energy management. This thesis will also develop a power measuring prototype designed to process and determine the main electrical measurements and quantify the electrical load connected to a low voltage alternating current system. Finally, two cases studies are proposed regarding the application of model predictive control and thermal regulation for domestic applications with cooling requirements, allowing to minimize energy consumption, considering the restrictions of demand, load and acclimatization in the system

A novel backup protection scheme for hybrid AC/DC power systems

This thesis presents and demonstrates (both via simulation and hardware-based tests) a new protection scheme designed to safeguard hybrid AC/DC distribution networks against DC faults that are not cleared by the main MVDC (Medium Voltage DC) link protection. The protection scheme relies on the apparent impedance measured at the AC "side" of the MVDC link to detect faults on the DC system. It can be readily implemented on existing distance protection relays with no changes to existing measuring equipment. An overview of the literature in this area is presented and it is shown that the protection of MVDC links is only considered at a converter station level. There appears to be no consideration of protecting the MVDC system from the wider AC power system via backup - as would be the case for standard AC distribution network assets, where the failure of main protection would require a (usually remote) backup protection system to operate to clear the fault. Very little literature considers remote backup protection of MVDC links.;To address this issue, the research presented in this thesis characterises the apparent impedance as measured in the neighbouring AC system under various DC fault conditions on an adjacent MVDC link. Initial studies, based on simulations, show that a highly inductive characteristic, in terms of the calculations from the measured AC voltages and currents, is apparent on all three phases in the neighbouring AC system during DC-side pole-to-pole and pole-poleground faults. This response is confirmed via a series of experiments conducted at low voltage in a laboratory environment using scaled down electrical components. From this classification, a fast-acting backup protection methodology, which can detect pole-to-pole and pole-poleground faults within 40 ms, is proposed and trialled through simulation. The solution can be deployed on distance protection relays using a typically unused zone (e.g. zone 4).;New relays could, of course, incorporate this functionality as standard in the future. To maximise confidence and demonstrate the compatibility of the solution, the protection scheme is deployed under a real-time hardware-in-the-loop environment using a commercially available distance protection relay. Suggestions to improve the stability of the proposed solution are discussed and demonstrated. Future areas of work are identified and described. As an appendix, early stage work pertaining to the potential application and benefits of MVDC is presented for two Scottish distribution networks. The findings from this are presented as supplementary material at the end of the thesis.This thesis presents and demonstrates (both via simulation and hardware-based tests) a new protection scheme designed to safeguard hybrid AC/DC distribution networks against DC faults that are not cleared by the main MVDC (Medium Voltage DC) link protection. The protection scheme relies on the apparent impedance measured at the AC "side" of the MVDC link to detect faults on the DC system. It can be readily implemented on existing distance protection relays with no changes to existing measuring equipment. An overview of the literature in this area is presented and it is shown that the protection of MVDC links is only considered at a converter station level. There appears to be no consideration of protecting the MVDC system from the wider AC power system via backup - as would be the case for standard AC distribution network assets, where the failure of main protection would require a (usually remote) backup protection system to operate to clear the fault. Very little literature considers remote backup protection of MVDC links.;To address this issue, the research presented in this thesis characterises the apparent impedance as measured in the neighbouring AC system under various DC fault conditions on an adjacent MVDC link. Initial studies, based on simulations, show that a highly inductive characteristic, in terms of the calculations from the measured AC voltages and currents, is apparent on all three phases in the neighbouring AC system during DC-side pole-to-pole and pole-poleground faults. This response is confirmed via a series of experiments conducted at low voltage in a laboratory environment using scaled down electrical components. From this classification, a fast-acting backup protection methodology, which can detect pole-to-pole and pole-poleground faults within 40 ms, is proposed and trialled through simulation. The solution can be deployed on distance protection relays using a typically unused zone (e.g. zone 4).;New relays could, of course, incorporate this functionality as standard in the future. To maximise confidence and demonstrate the compatibility of the solution, the protection scheme is deployed under a real-time hardware-in-the-loop environment using a commercially available distance protection relay. Suggestions to improve the stability of the proposed solution are discussed and demonstrated. Future areas of work are identified and described. As an appendix, early stage work pertaining to the potential application and benefits of MVDC is presented for two Scottish distribution networks. The findings from this are presented as supplementary material at the end of the thesis

Optimal energy management for a grid-tied solar PV-battery microgrid: A reinforcement learning approach

There has been a shift towards energy sustainability in recent years, and this shift should continue. The steady growth of energy demand because of population growth, as well as heightened worries about the number of anthropogenic gases released into the atmosphere and deployment of advanced grid technologies, has spurred the penetration of renewable energy resources (RERs) at different locations and scales in the power grid. As a result, the energy system is moving away from the centralized paradigm of large, controllable power plants and toward a decentralized network based on renewables. Microgrids, either grid-connected or islanded, provide a key solution for integrating RERs, load demand flexibility, and energy storage systems within this framework. Nonetheless, renewable energy resources, such as solar and wind energy, can be extremely stochastic as they are weather dependent. These resources coupled with load demand uncertainties lead to random variations on both the generation and load sides, thus challenging optimal energy management. This thesis develops an optimal energy management system (EMS) for a grid-tied solar PV-battery microgrid. The goal of the EMS is to obtain the minimum operational costs (cost of power exchange with the utility and battery wear cost) while still considering network constraints, which ensure grid violations are avoided. A reinforcement learning (RL) approach is proposed to minimize the operational cost of the microgrid under this stochastic setting. RL is a reward-motivated optimization technique derived from how animals learn to optimize their behaviour in new environments. Unlike other conventional model-based optimization approaches, RL doesn't need an explicit model of the optimization system to get optimal solutions. The EMS is modelled as a Markov Decision Process (MDP) to achieve optimality considering the state, action, and reward function. The feasibility of two RL algorithms, namely, conventional Q-learning algorithm and deep Q network algorithm, are developed, and their efficacy in performing optimal energy management for the designed system is evaluated in this thesis. First, the energy management problem is expressed as a sequential decision-making process, after which two algorithms, trading, and non-trading algorithm, are developed. In the trading algorithm case, excess microgrid's energy can be sold back to the utility to increase revenue, while in the latter case constraining rules are embedded in the designed EMS to ensure that no excess energy is sold back to the utility. Then a Q-learning algorithm is developed to minimize the operational cost of the microgrid under unknown future information. Finally, to evaluate the performance of the proposed EMS, a comparison study between a trading case EMS model and a non-trading case is performed using a typical commercial load curve and PV generation profile over a 24- hour horizon. Numerical simulation results indicated that the algorithm learned to select an optimized energy schedule that minimizes energy cost (cost of power purchased from the utility based on the time-varying tariff and battery wear cost) in both summer and winter case studies. However, comparing the non-trading EMS to the trading EMS model operational costs, the latter one decreased cost by 4.033% in the summer season and 2.199% in the winter season. Secondly, a deep Q network (DQN) method that uses recent learning algorithm enhancements, including experience replay and target network, is developed to learn the system uncertainties, including load demand, grid prices and volatile power supply from the renewables solve the optimal energy management problem. Unlike the Q-learning method, which updates the Q-function using a lookup table (which limits its scalability and overall performance in stochastic optimization), the DQN method uses a deep neural network that approximates the Q- function via statistical regression. The performance of the proposed method is evaluated with differently fluctuating load profiles, i.e., slow, medium, and fast. Simulation results substantiated the efficacy of the proposed method as the algorithm was established to learn from experience to raise the battery state of charge and optimally shift loads from a one-time instance, thus supporting the utility grid in reducing aggregate peak load. Furthermore, the performance of the proposed DQN approach was compared to the conventional Q-learning algorithm in terms of achieving a minimum global cost. Simulation results showed that the DQN algorithm outperformed the conventional Q-learning approach, reducing system operational costs by 15%, 24%, and 26% for the slow, medium, and fast fluctuating load profiles in the studied cases

National Conference on ‘Renewable Energy, Smart Grid and Telecommunication-2023

Theme of the Conference: “The challenges and opportunities of integrating renewable energy into the grid” The National Conference on Renewable Energy, Smart Grid, and Telecommunication - 2023 is a platform for industry experts, researchers, and policymakers to come together and explore the latest advancements and challenges in the fields of renewable energy, smart grids, and telecommunication. Conference Highlights: In-depth discussions on renewable energy technologies and innovations. Smart grid integration for a sustainable future. The role of telecommunication in advancing renewable energy solutions. Networking opportunities with industry leaders and experts. Presentation of cutting-edge research papers and case studies. Conference topics: Renewable Energy Technologies and Innovations Smart Grid Development and Implementation Telecommunication for Energy Systems Energy Storage and Grid Balancing Policy, Regulation, and Market Dynamics Environmental and Social Impacts of Renewable Energy Energy Transition and Future Outlook Integration of renewable energy into the grid Microgrids and decentralized energy systems Grid cybersecurity and data analytics IoT and sensor technologies for energy monitoring Data management and analytics in energy sector Battery storage technologies and applicationshttps://www.interscience.in/conf_proc_volumes/1087/thumbnail.jp