Machine learning for anomaly detection in smart grid

Utilismart Corporation为公用事业、市政、工业、商业和住宅客户提供仪表数据管理软件解决方案和数据服务。该公司收集、验证、安全存储、分析和呈现来自智能电表、间隔电表或任何其他电力监控设备的数据。许多问题会影响这些收集/原始数据的质量，例如，通信问题、硬件问题和故障、不正确的设置等等。虽然验证、编辑和评估（VEE）过程纠正了许多这些问题，但是仍然存在一些不规范，并且它们的解决通常需要大量的手工工作。因此，该项目的目标是设计和开发一种基于机器学习的最先进的解决方案，用于识别这些异常，并设计一种新的技术来纠正这些异常。该解决方案将由两个主要组件组成i)异常检测组件将负责识别异常数据。虽然存在许多异常检测解决方案，但它们通常属于监督学习类别，并且需要大量已知的异常进行训练。相比之下，我们的技术将主要从正常数据中学习，并能够检测到新的异常类型。ii)异常解决组件将通过自动化或半自动化过程为解决已识别的异常提供支持。通过这个项目，加拿大有机会为智能电表数据分析奠定坚实的基础，并在智能电网领域建立实力。此外，机器学习和人工智能方面的培训将有助于推动加拿大在这些快速发展领域的能力。

Utilismart Corporation provides meter data management software solutions and data services for utilities, municipalities, industrial, commercial and residential customers. The company collects, validates, securely stores, analyzes, and presents data from smart meters, interval meters, or any other device monitoring electricity. Many issues can affect the quality of these collected/raw data, for example, communication issues, hardware problems and failures, improper setup, and many others. While the Validation, Editing, and Estimation (VEE) process remedies many of these issues, some irregularities still remain and their resolution typically requires significant manual effort. Consequently, the objective of this project is to design and develop a state-of-the-art solution for identifying these anomalies based on machine learning as well as to devise a novel technique for remedying those anomalies. The solution will consist of two main components i) Anomaly detection component will be responsible for identifying anomalous data. While many anomaly detection solutions exist, they typically belong to the supervised learning category and require a large number of known anomalies for training. In contrast, our technique will learn from predominantly normal data and will be able to detect new types of anomalies. ii) Anomaly resolution component will provide support for resolving the identified anomalies through automated or semiautomated processes. With this project, Canada has an opportunity to create a strong foundation for smart meter data analytics and build strenghth in the smart grid domain. Moreover, training in machine learning and artificial intelligence will help drive Canada's abilities in these fast-growing fields.