Towards a Cleaner Environment: Smart Grid Management in the Presence of Electric Vehiecles, Renewable Energy Sources, and Storage

可再生能源是应对气候变化的主要技术之一。为了向更清洁的经济转型并减少温室气体排放，加拿大制定了到2050年通过更新基础设施和投资可再生能源发电实现净零排放的目标。可再生能源（如太阳能和风能）面临的一个重大挑战是缺乏持续的能源生产。因此，智能电网需要存储容量，而存储容量可以从电池中获得。电动汽车（ev）是确保连续配电运行的替代能源：由于电动汽车的利用率大多较低，因此存储的能量可以反馈到电网以支持高峰需求时段的配电服务。预计到2030年，电动汽车累计储能容量将达到7太瓦时。然而，电动汽车采用的广泛增长带来了挑战，例如，在考虑用户能源成本和可持续性指标的同时，如何安排电池向电网和电力消耗的能量注入。因此，该项目旨在设计和开发尖端数据分析，以管理智能电网，改善需求响应行动，并通过利用可再生能源和电动汽车减少温室气体排放。本研究的组成部分包括：1)预测能源消耗，可再生能源发电，以及将储存的能源注入电网。ii)通过客户聚类和特征来确定需求响应（DR）的目标用户，并制定定价策略框架以激励节能。制定一个绿色指数，为消费者的消费情况分配一个分数，考虑其与可持续性公用事业政策的一致性。iii)通过优化消费调度和将电动汽车和电池储存的电力注入电网，支持峰值需求，缓解可再生能源密集型电网的波动性。该项目将帮助伦敦水电和加拿大克服挑战，提供更稳定的服务，并利用可再生能源技术更好的社会经济和环境影响。

Renewable energy is one of the leading technologies used to fight climate change. To transition to a cleaner economy and reduce GHG emissions, Canada has set a goal to achieve net-zero emissions by 2050 by updating infrastructure and investing in renewable energy generation. A significant challenge with renewable energies, such as solar and wind power, is the lack of continuous energy production. Therefore, smart grids require storage capacity, which can be obtained from batteries. Electric vehicles (EVs) are an alternative source to ensure a continuous distribution operation: because EVs mostly have low utilization rates, the stored energy could be fed back to the grid to support distribution services during peak demand times. Accumulated EVs storage capacity has been estimated to reach 7 TWh by 2030. However, expansive growth in EV adoption presents challenges, such as scheduling energy injection from batteries into the grid and electricity consumption while accounting for users' energy costs and sustainability metrics. Consequently, this project aims to design and develop cutting-edge data analytics for managing smart grids, improving demand response actions, and reducing GHG emissions by leveraging renewable energy sources and EVs. The components of this proposed research are i) Forecast energy consumption, renewable generation, and injection of stored energy into the grid. ii) Target users for Demand-Response (DR) by customer clustering and characterization and develop a framework for pricing strategy to incentivize energy savings. Develop a green index that assigns a score to the consumer consumption profile concerning its accordance with the utility policy for sustainability. iii) Support peak demand and mitigate the volatility of renewable-intensive grids by optimizing the consumption scheduling and injection of electricity stored in EVs and batteries into the grid. The project will help London Hydro and Canada to overcome challenges in providing more stable services and leveraging renewable technology's better socio-economic and environmental impacts.