Computational Algorithms for Energy Efficiency and Cost Reduction

提高能源效率和降低成本的计算算法

• 批准号: 510601-2017
• 负责人: Feng, Wenying
• 金额: $ 1.82万
• 依托单位: Trent University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640137
• 关键词: Computational; Algorithms; Energy; Efficiency; Cost

Energy efficiency affects people's daily life, industry and social environment. For example, properly shiftingelectricity usage can significantly reduce its cost and the demand during periods of limited supply. As a leadingcompany in the market of energy efficiency, Lowfoot Inc. has been developing innovative tools for energy costreduction by Artificial Intelligence approaches.Supported by Lowfoot Inc., the project will introduce computational algorithms that are efficient in predictionof electricity usage and provide recommendations to minimize user's energy cost. New advancement inMachine Learning, big data and related areas will be investigated for effective solutions. With theoreticalfoundation in mathematical modeling and computing techniques, deep learning and cloud computing will beapplied. The objective is to improve the forecast accuracy of the system.The work will contribute directly to today's fast moving areas of data analytics by deep artificial intelligence ofwhich Canada is at the forefront. The results will benefit consumers and small business on energy managementand have the potential of creating new employment for the Canadian society.

能源效率影响着人们的日常生活、工业和社会环境。例如，适当地改变电力使用可以大大降低其成本和在有限供应期间的需求。作为能源效率市场的领先公司，Lowfoot Inc.一直致力于通过人工智能方法开发降低能源成本的创新工具。在Lowfoot Inc.的支持下，该项目将引入计算算法，有效地预测用电量，并提供建议，以尽量减少用户的能源成本。将研究机器学习，大数据和相关领域的新进展，以获得有效的解决方案。在数学建模和计算技术的理论基础上，深度学习和云计算将得到应用。目标是提高系统的预测准确性。这项工作将直接有助于当今快速发展的数据分析领域，通过深度人工智能，加拿大处于领先地位。研究结果将使消费者和小企业在能源管理方面受益，并有可能为加拿大社会创造新的就业机会。