Data analytics for electric vehicle energy management
电动汽车能源管理的数据分析
基本信息
- 批准号:570760-2021
- 负责人:
- 金额:$ 2.19万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Alliance Grants
- 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:
- 关键词:
项目摘要
In recent years, Electric Vehicle (EV) popularity has been rapidly growing: in 2020 global EV registration increased 41% despite overall car sales falling 16%. Canada will be banning new internal combustion engine vehicles after 2035 and many other countries are announcing similar plans. Moreover, interest in sustainability is growing and many consumers are willing to pay a premium for sustainability. Meeting such aggressive objectives imposes many challenges. First, new services are needed for EV owners to encourage EV adoption and support energy consumption and cost management. Expansive growth in EV adoption will put a strain on the existing electrical grid and services are needed for distribution companies to estimate future grid load, understand EV charging patterns, predict local grid loads, and support decision making.Consequently, the main objective of this project is to design and develop EV data analytics solution for EV owners and electricity distributors in order to promote EV adoption, reduce the cost of ownership, understand the EV charging impact of the grid, and reduce the impact on the environment. The two main components are: the EV owner-facing and distributor-facing solutions. The EV owner-facing solution will help EV owners manage their charging cost, provide them personalized suggestions and range estimates. The distributor-facing solution will provide large-scale grid impact analysis to support decision-making in respect to grid expansion, renewable integration, and optimizing large-scale EV charging. The project will help London Hydro adapt to changing grid characteristics, provide additional services for its customers, improve demand-response programs, and ultimately reduce the impact on the environment.
近年来,电动汽车(EV)的普及率一直在迅速增长:2020年全球EV注册量增长了41%,尽管整体汽车销量下降了16%。加拿大将在2035年后禁止新的内燃机汽车,许多其他国家也宣布了类似的计划。此外,对可持续性的兴趣正在增长,许多消费者愿意为可持续性支付额外费用。实现如此激进的目标带来了许多挑战。首先,电动汽车车主需要新的服务,以鼓励电动汽车的采用,并支持能源消耗和成本管理。随着电动汽车普及率的不断提高,现有电网将面临越来越大的压力,因此,配电公司需要提供服务,以估计未来电网负荷,了解电动汽车充电模式,预测当地电网负荷,并支持决策。因此,本项目的主要目标是为电动汽车所有者和电力分销商设计和开发电动汽车数据分析解决方案,以促进电动汽车的普及,降低拥有成本,了解电动汽车充电对电网的影响,并减少对环境的影响。两个主要组成部分是:面向电动汽车所有者和面向经销商的解决方案。面向电动汽车车主的解决方案将帮助电动汽车车主管理他们的充电成本,为他们提供个性化的建议和范围估计。面向分销商的解决方案将提供大规模电网影响分析,以支持有关电网扩展,可再生能源整合和优化大规模电动汽车充电的决策。该项目将帮助伦敦水电适应不断变化的电网特性,为客户提供额外的服务,改善需求响应计划,并最终减少对环境的影响。
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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Grolinger, Katarina其他文献
Generating Energy Data for Machine Learning with Recurrent Generative Adversarial Networks
- DOI:
10.3390/en13010130 - 发表时间:
2020-01-01 - 期刊:
- 影响因子:3.2
- 作者:
Fekri, Mohammad Navid;Ghosh, Ananda Mohon;Grolinger, Katarina - 通讯作者:
Grolinger, Katarina
Edge-Cloud Computing for Internet of Things Data Analytics: Embedding Intelligence in the Edge With Deep Learning
- DOI:
10.1109/tii.2020.3008711 - 发表时间:
2021-03-01 - 期刊:
- 影响因子:12.3
- 作者:
Ghosh, Ananda Mohon;Grolinger, Katarina - 通讯作者:
Grolinger, Katarina
Energy Forecasting for Event Venues: Big Data and Prediction Accuracy
- DOI:
10.1016/j.enbuild.2015.12.010 - 发表时间:
2016-01-15 - 期刊:
- 影响因子:6.7
- 作者:
Grolinger, Katarina;L'Heureux, Alexandra;Seewald, Luke - 通讯作者:
Seewald, Luke
An ensemble learning framework for anomaly detection in building energy consumption
- DOI:
10.1016/j.enbuild.2017.02.058 - 发表时间:
2017-06-01 - 期刊:
- 影响因子:6.7
- 作者:
Araya, Daniel B.;Grolinger, Katarina;Bitsuamlak, Girma - 通讯作者:
Bitsuamlak, Girma
Machine Learning With Big Data: Challenges and Approaches
- DOI:
10.1109/access.2017.2696365 - 发表时间:
2017-01-01 - 期刊:
- 影响因子:3.9
- 作者:
L'Heureux, Alexandra;Grolinger, Katarina;Capretz, Miriam A. M. - 通讯作者:
Capretz, Miriam A. M.
Grolinger, Katarina的其他文献
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{{ truncateString('Grolinger, Katarina', 18)}}的其他基金
Edge-Cloud Computing for Internet of Things Data Analytics
用于物联网数据分析的边缘云计算
- 批准号:
RGPIN-2018-06222 - 财政年份:2022
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Edge-Cloud Computing for Internet of Things Data Analytics
用于物联网数据分析的边缘云计算
- 批准号:
RGPIN-2018-06222 - 财政年份:2021
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Edge-Cloud Computing for Internet of Things Data Analytics
用于物联网数据分析的边缘云计算
- 批准号:
RGPIN-2018-06222 - 财政年份:2020
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Edge-Cloud Computing for Internet of Things Data Analytics
用于物联网数据分析的边缘云计算
- 批准号:
RGPIN-2018-06222 - 财政年份:2019
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Edge-Cloud Computing for Internet of Things Data Analytics
用于物联网数据分析的边缘云计算
- 批准号:
RGPIN-2018-06222 - 财政年份:2018
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Grants Program - Individual
Edge-Cloud Computing for Internet of Things Data Analytics
用于物联网数据分析的边缘云计算
- 批准号:
DGECR-2018-00097 - 财政年份:2018
- 资助金额:
$ 2.19万 - 项目类别:
Discovery Launch Supplement
Anomaly Detection for Advanced Metering Infrastructure
高级计量基础设施的异常检测
- 批准号:
519910-2017 - 财政年份:2017
- 资助金额:
$ 2.19万 - 项目类别:
Engage Grants Program
Decreasing the risk and the timeframe of legacy database application migration
降低遗留数据库应用程序迁移的风险和时间范围
- 批准号:
392470-2010 - 财政年份:2012
- 资助金额:
$ 2.19万 - 项目类别:
Alexander Graham Bell Canada Graduate Scholarships - Doctoral
Decreasing the risk and the timeframe of legacy database application migration
降低遗留数据库应用程序迁移的风险和时间范围
- 批准号:
392470-2010 - 财政年份:2011
- 资助金额:
$ 2.19万 - 项目类别:
Alexander Graham Bell Canada Graduate Scholarships - Doctoral
Decreasing the risk and the timeframe of legacy database application migration
降低遗留数据库应用程序迁移的风险和时间范围
- 批准号:
392470-2010 - 财政年份:2010
- 资助金额:
$ 2.19万 - 项目类别:
Alexander Graham Bell Canada Graduate Scholarships - Doctoral
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