Hardware and software for power system and market studies using AI and bigdata techniques
使用人工智能和大数据技术进行电力系统和市场研究的硬件和软件
基本信息
- 批准号:RTI-2021-00192
- 负责人:
- 金额:$ 7.46万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Research Tools and Instruments
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Large interconnected electric power systems are strategic for the economic and social well-being of Canadians, since society depends more than ever on electricity, due to the fact that most of our energy demand, in particular thermal and transportation, are being electrified at a very rapid rate, driven by climate change and the associated integration of ever more present and cheaper Renewable Energy Sources (RES) such as wind and solar generation. These large and complex grids, which are considered the most complex systems invented by humanity, have traditionally been studied and researched through software simulations, rather than hardware-based studies. In this context, our research group at Waterloo has focused on power systems research that is primarily based on computer modeling and simulation of mathematical models of large and small power grids with RES for stability, control, operation, economics, planning, and electricity market studies. For over the past two decades, our research group has developed some of the most relevant mathematical models for computer simulations and studies in the power grid technical literature, as attested by multiple awards and recognitions, which has been widely referred to and used by researchers and utilities around the world.
Our research has been accomplished with the help of 4 servers and various software packages, on which our group is fully dependent. All this hardware and software tools, which have been developed, purchased, maintained, and updated with NSERC, OCE, research contracts, and Waterloo funds, have served us well, allowing us to also establish collaborations with other colleagues at Waterloo and other Canadian universities, as well as with researchers from overseas institutions. However, these servers and power system modeling and simulation software packages are becoming outdated and hence need urgent upgrade. Furthermore, the software versions currently available in the market have many advanced features that our existing versions are lacking. In fact, our oldest server has become rather slow in performing the required processing tasks because of its age and overuse, which is affecting the quality and quantity of our research output.
In view of the above major constraints, we are applying for the Research Tools and Instrument (RTI) funds to replace the aforementioned server with an up-to-date more advanced version, especially since we are starting to pursue research in artificial intelligence (AI), machine learning (ML), and big-data applications to power systems. This evolving new research direction being supported by upcoming grants and contracts would require a different type of server based on multiple Graphic Processing Units (GPUs), which are indispensable for executing AI-related software. GPUs are the best options for fast ML as data science model training involves calculations that are greatly enhanced by parallel computations.
大型互联电力系统对加拿大人的经济和社会福祉具有战略意义,因为社会比以往任何时候都更加依赖电力,因为我们的大部分能源需求,特别是热能和运输,正在以非常快的速度实现电气化。受气候变化以及与之相关的风能和太阳能发电等更廉价的可再生能源(RES)的整合所驱动。 这些大型复杂的电网被认为是人类发明的最复杂的系统,传统上是通过软件模拟而不是基于硬件的研究来研究和研究的。在这种情况下,我们在滑铁卢的研究小组一直专注于电力系统研究,主要是基于计算机建模和仿真的大型和小型电网的数学模型与RES的稳定性,控制,运行,经济,规划和电力市场研究。在过去的二十年里,我们的研究小组已经开发了一些最相关的数学模型,用于电网技术文献中的计算机模拟和研究,并获得了多个奖项和荣誉,被世界各地的研究人员和公用事业公司广泛引用和使用。
我们的研究是在4台服务器和各种软件包的帮助下完成的,我们的团队完全依赖于这些服务器和软件包。所有这些硬件和软件工具都是由NSERC,OCE,研究合同和滑铁卢基金开发,购买,维护和更新的,它们为我们提供了很好的服务,使我们能够与滑铁卢和其他加拿大大学的其他同事以及来自海外机构的研究人员建立合作关系。然而,这些服务器和电力系统建模和仿真软件包正在变得过时,因此迫切需要升级。此外,市场上现有的软件版本具有我们现有版本所缺乏的许多高级功能。事实上,我们最旧的服务器由于老化和过度使用,在执行所需的处理任务时变得相当缓慢,这影响了我们研究成果的质量和数量。
鉴于上述主要限制,我们正在申请研究工具和仪器(RTI)基金,以最新的更先进的版本取代上述服务器,特别是因为我们开始研究人工智能(AI),机器学习(ML)和大数据应用于电力系统。这一不断发展的新研究方向将得到即将到来的赠款和合同的支持,这将需要一种基于多个图形处理单元(GPU)的不同类型的服务器,这对于执行人工智能相关软件是必不可少的。GPU是快速ML的最佳选择,因为数据科学模型训练涉及通过并行计算大大增强的计算。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Cañizares, Claudio其他文献
Cañizares, Claudio的其他文献
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{{ truncateString('Cañizares, Claudio', 18)}}的其他基金
A Grid of Microgrids
微电网
- 批准号:
RGPIN-2017-04343 - 财政年份:2020
- 资助金额:
$ 7.46万 - 项目类别:
Discovery Grants Program - Individual
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