A novel approach to COVID-19 Impact Analysis and Reporting for Utilities

COVID-19疫情正在影响个人、家庭及商业环境。对于北美的一些市政当局和城市来说，在封锁措施的第一周，住宅公用事业的使用量增加了12%。一般来说，公用事业公司在为紧急情况做准备方面有着良好的记录。作为关键基础设施的提供者，该行业为许多可预见的危害制定了计划，但在大多数情况下，没有为COVID-19危机等卫生紧急情况制定连续性计划。有必要支持公用事业公司为连续性计划提供适当的数据，这些计划可适用于全面应对COVID-19等疫情的快速变化和未知变量。该项目将回答以下研究问题：什么类型的数据分析系统可以开发，以提取数据从公用事业公司，将直观地说明模式和趋势的公用事业使用，可用于基础设施和服务需求的决策？来自Okanagan College和Langara College的教师研究人员和学生将开发系统，用于从公共来源自动获取COVID-19相关数据，将这些数据关联存储在关系数据库中，并配置用于可视化和查询的仪表板。该项目将通过提供Transformer负荷预测等关键信息，使公用事业服务提供商受益，从而做出可能降低故障率的决策。反过来，消费者将受益，因为该系统将帮助供应商识别高负载情况，这些情况可以通过提供有针对性的节能提示来减少。

The COVID-19 pandemic is impacting personal, family and business environments. For some municipalities and cities across North America, during the first week of lockdown practices, residential utility usage increased by as much as 12%. Generally, utility companies have a strong track record in preparing for emergencies. As providers of critical infrastructure, the industry plans for many foreseeable hazards, but in most cases continuity plans for health emergencies such as the COVID-19 crisis were not prepared. There is a need to support utilities in having the appropriate data available for continuity plans that are adaptable to fully address the fast-moving and unknown variables of an outbreak such as COVID-19. The project will answer the following research question: What type of data analysis system may be developed to extract data from utility meters for utility companies that will visually illustrate patterns and trends of utility usage that may be used for infrastructure and service needs decision making? Faculty researchers and students from Okanagan College and Langara College will develop systems for automated acquisition of COVID-19 related data from public sources, associated storage of this data in a relational database, and configuration of dashboards for visualizations and queries. The project will benefit utility service providers by providing critical information such as transformer load forecasts, enabling decisions that may decrease failure rates. In turn, consumers will benefit, as the system will help providers identify high load scenarios that can be diminished by providing targeted power saving tips.