Networking Research for Smart Energy Systems

智能能源系统的网络研究

• 批准号: RGPIN-2020-05985
• 负责人: Elmallah, Ehab
• 金额: $ 1.75万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=740959
• 关键词: Networking; Research; Smart; Energy; Systems

Research on smart energy systems has been moving to the forefront worldwide. Key technological advances that empower such research include the continuing development and harnessing of energy generated from renewable energy resources, and the increasing novel use of distributed computing and communications to balance the supply and demand in the electrical power grid. This latter aspect has enabled the transformation of the traditional electrical grid into a smart cyber-physical infrastructure referred to as the smart grid. The proposed networking research investigates problems in three broad directions related to the above currently evolving vital systems. The first broad direction is on the design and analysis of terrestrial wireless sensor networks (WSNs) and underwater sensor networks (UWSNs) that utilize energy replenishment methods such as environmental energy harvesting or wireless charging to achieve long-lasting operation. Research in this direction is enabled by current advances in designing efficient solar panels, micro wind tribunes, devices that harvest kinetic energy of underwater currents, and wireless charging technologies. A common characteristic of such networks is the fluctuation of a node's energy level over time. Such fluctuations introduce uncertainty in a node's ability to sense and communicate. Consequently, many of the network design and analysis problems that have been investigated for battery operated nodes need to be revisited. We will endeavor to advance the state-of-the-art by designing new efficient, reliable, and intelligent methods for operating such networks. A core aspect in the proposed work is the development of effective methods for dealing with a node's residual energy and a node's foreseeable obtainable energy during any interval of time. The second broad direction pertains to the currently evolving organization of new electrical grids around microgrid networks that provide distributed generation of electrical power. Microgrids can cooperate to complement each other to achieve higher robustness, reliability, and profitability. The proposal addresses distributed coordination problems that arise in this context. The third broad direction considers the uncertainty in knowing many of the operational aspects that can affect the power flow and data flow in a microgrid network, and consequently affect the overall performance of the network. The proposed research in the above areas aims at developing algorithms, protocols, and performance evaluation models to cope with the problems. The methodologies will also incorporate the use of machine learning techniques to develop prediction and learning-based resource management approaches to cope with various uncertainty aspects of the problems.

智能能源系统的研究已经走到了世界的前沿。推动此类研究的关键技术进步包括对可再生能源产生的能源的持续开发和利用，以及分布式计算和通信的日益新颖的应用，以平衡电网的供需。后一个方面使传统电网转变为智能网络物理基础设施，即智能电网。提出的网络研究从三个广泛的方向调查了与上述正在发展的生命系统相关的问题。第一个广泛的方向是设计和分析地面无线传感器网络（WSNs）和水下传感器网络（UWSNs），利用能量补充方法，如环境能量收集或无线充电，以实现长期运行。目前在设计高效太阳能电池板、微型风力板、收集水下水流动能的设备和无线充电技术方面的进展使这一方向的研究成为可能。这种网络的一个共同特征是节点的能量水平随时间波动。这种波动给节点的感知和通信能力带来了不确定性。因此，需要重新审视电池供电节点的许多网络设计和分析问题。我们将努力通过设计新的高效、可靠和智能的方法来推进最先进的技术来运行这些网络。提出的工作的一个核心方面是开发有效的方法来处理节点的剩余能量和节点在任何时间间隔内的可预见可获得能量。第二个大方向涉及目前围绕提供分布式发电的微电网网络不断发展的新电网组织。微电网可以合作互补，实现更高的稳健性、可靠性和盈利能力。该提案解决了在这种情况下出现的分布式协调问题。第三个大方向考虑了在了解可能影响微电网中功率流和数据流的许多操作方面的不确定性，从而影响网络的整体性能。上述领域的研究旨在开发算法、协议和性能评估模型来应对这些问题。这些方法还将结合使用机器学习技术来开发预测和基于学习的资源管理方法，以应对问题的各种不确定性方面。