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

分布式能源预测和建模以及分布式系统运营商规划和运营模型

• 批准号: 572272-2022
• 负责人: Venkatesh, BalaB
• 金额: $ 20.18万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752540
• 关键词: Forecasting; Modeling; Distributed; Energy; Resources

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.

分布式能源（DER）的大规模整合，如可再生能源，存储和智能负载到配电系统中，是一条通往绿色能源系统和2050年零碳未来的道路。这是我们社会所期望的未来，有助于减缓气候变化。这也是一项具有挑战性的任务。电力公司需要综合方法来预测DER，综合稳态和综合瞬态DER模型-在馈线和变电站级别-以最好地管理其电力网络。此外，随着DER和其他客户之间的对等能源交易的潜力，迫切需要更好的经济技术模型，以便DER获得最佳价值，公用事业客户获得最佳优势。因此，所提出的工作是由这种迫切需要推动的绿色我们的能源供应，通过增加吸收的DERs。DER规模小，数量多。它们的间歇性和不确定性对公用事业公司监测、预测、建模、分析和运营其网络构成了挑战。总体目标是开发工具和框架，以支持可持续和无缝地将来自DER的各种形式的能源整合到HONI电网中，以最大限度地增加所有利益相关者（包括DER所有者和电力客户）的机会，接入电网和选择，这也将实现深度电气化。为了实现这一结果，我们提出了四个工作包（WP）来开发基于人工智能的、高分辨率的、聚合的DER预测工具、稳态DER模型、瞬时DER模型以及配电系统运营商（DSO）和配电网运营商（DNO）用于运营和规划的模型，包括算法和软件实施。加拿大需要将其清洁能源供应从目前的情况增加两到三倍。该项目的成果将通过增强供应可靠性、应对极端天气的弹性和经济可及性，为加拿大经济做出贡献，促进更多的DER采用，作为深度清洁电气化的途径。