Forecasting and Modeling of Distributed Energy Resources, and Models for Distributed System Operator Planning and Operation

将分布式能源(DER)大规模集成到配电系统中，如可再生能源、存储和智能负载，是实现能源系统绿色化和2050年零碳未来的途径。这是我们的社会渴望并有助于缓解气候变化的未来。这也是一项具有挑战性的任务。电力公用事业公司需要综合预测DER的方法、综合稳态和综合暂态DER模型-在馈线和变电站级别-以最好地管理其电网。此外，随着电力系统和其他客户之间的点对点能源交易的潜力，迫切需要更好的经济技术模型，以便电力系统获得最大的价值，公用事业客户获得最大的利益。因此，拟议的工作是由这一迫切需要推动的，即通过增加对DERs的吸收来保护我们的能源供应。DER体积小，数量多。它们的间歇性和不确定性给公用事业公司监测、预测、建模、分析和运营其网络带来了挑战。总体目标是开发工具和框架，支持将各种形式的能源可持续地无缝集成到HONI电网中，最大限度地增加机会、最大限度地获得电网，并为所有利益相关者(包括DER所有者和电力客户)提供选择，这也将使深度电气化成为可能。为了实现这一结果，我们提出了四个工作包(WPS)来开发基于人工智能的、高分辨率的聚合DER预测工具、稳态DER模型、暂态DER模型以及用于运行和规划的配电系统运营商(DSO)和配电网络运营商(DNO)模型，包括算法和软件实施。加拿大需要在目前的基础上增加两三倍的清洁能源供应。该项目的成果将通过提高供应可靠性、应对极端天气的弹性和经济可获得性，为加拿大经济做出贡献，促进更多的人更多地参与到深度清洁电气化的道路上来。

Large scale integration of distributed energy resources (DERs), such as renewables, storage and smart loads into electric power distribution systems, is a path that leads to greening of our energy systems and a zero carbon 2050 future. This is a future that our society desires and helps to mitigate climate change. This is also a challenging task. Electric utilities require aggregate methods for forecasting of DERs, aggregate steady-state and aggregate transient DER models - at feeder and substation levels - to best manage their electric power networks. Further, with the potential of peer-to-peer energy transactions between DERs and other customers, better economic techno-models are a pressing need such that DERs derive best value and utility customers gain the best advantage. Accordingly, proposed work is driven by this urgent need to green our energy supply through increasing the uptake of DERs. DERs are small in size and numerous. Their intermittent and uncertain nature poses a challenge for utilities to monitor, forecast, model, analyse and operate their networks. The overarching goal is to develop tools and frameworks that support the sustainable and seamless integration of diverse forms of energy from DERs into the HONI grid in ways that maximize opportunity, access to the grid, and choice for all stakeholders (including DER owners and electricity customers), which will also enable deep electrification. To achieve this outcome, we are proposing four work packages (WPs) to develop AI-based, high-resolution, aggregate, DER forecasting tools, steady-state DER models, transient DER models, and distribution system operator (DSO) and distribution network operator (DNO) models for operation and planning, comprising algorithms and software implementation. Canada needs to increase its clean energy supply two or three folds from its current situation. The project's outcomes will contribute to the Canadian economy though enhanced supply reliability, resilience to face extreme weather, and economic accessibility, facilitating greater DER uptake as the pathway to deep clean electrification.